diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 000000000..476a21b1c
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+datasets/isb1/exports/preview/long_context_1m/*.json filter=lfs diff=lfs merge=lfs -text
+datasets/isb1/exports/**/*.json filter=lfs diff=lfs merge=lfs -text
diff --git a/.github/configs/multiturn-agentic-trace-isb1.yaml b/.github/configs/multiturn-agentic-trace-isb1.yaml
new file mode 100644
index 000000000..c0cfa7a87
--- /dev/null
+++ b/.github/configs/multiturn-agentic-trace-isb1.yaml
@@ -0,0 +1,73 @@
+# ISB1 sweep cells for Cam's kv-cache-tester replay flow.
+# Schema mirrors .github/configs/multiturn-agentic-trace.yaml.
+# Merge these top-level keys into that file (or extend the sweep workflow
+# to glob .github/configs/multiturn-agentic-trace*.yaml) to include ISB1 sweeps.
+# 8k code cells map to datasets/isb1/converted/core/code_8k1k/.
+# 32k chat cells map to datasets/isb1/converted/extension_32k/chat_32k1k*/.
+# 131k code/chat cells map to datasets/isb1/converted/extension_131k/*_131k1k*/.
+# 500k preview cells map to datasets/isb1/converted/preview/long_context_500k/.
+# 1m preview cells map to datasets/isb1/converted/preview/long_context_1m/.
+# Expected TRACE_DIR is either datasets/isb1/converted/ or one of those subdirs,
+# or an HF alias like hf_wchen22--isb1-cc-traces (resolved by the replay
+# harness's TRACE_DIR=hf_<org>--<repo> hydration path).
+#
+# offload values:
+#   on       — KV offload enabled (VLLM_USE_SIMPLE_KV_OFFLOAD=1)
+#   off      — KV offload disabled (baseline)
+#   noprefix — offload off AND --no-enable-prefix-caching (clean-cache floor).
+#              Cam's h100 lane already wires the flag in
+#              multiturn_fp8_h100_lmcache_aiperf.sh:123-126; these cells just
+#              surface the third mode so the sweep generator emits it.
+
+h200-fp8-qwen3-isb1-code-8k:
+  tp2: {users: [2, 4, 8, 16, 32, 64, 128], offload: ["on", "off", "noprefix"]}
+  tp4: {users: [2, 4, 8, 16, 32, 64, 128], offload: ["on", "off", "noprefix"]}
+
+h200-fp8-qwen3-isb1-chat-32k:
+  tp2: {users: [1, 2, 4, 8, 16, 32], offload: ["on", "off", "noprefix"]}
+  tp4: {users: [1, 2, 4, 8, 16, 32, 64], offload: ["on", "off", "noprefix"]}
+
+h200-fp8-qwen3-isb1-code-131k:
+  tp4: {users: [1, 2, 4, 8], offload: ["on", "off", "noprefix"]}
+  tp8: {users: [1, 2, 4, 8, 16], offload: ["on", "off", "noprefix"]}
+
+b200-fp4-dsr1-isb1-code-8k:
+  tp4: {ep: 4, users: [4, 8, 16, 32, 64, 128, 256], offload: ["on", "off"]}
+  tp8: {ep: 8, users: [8, 16, 32, 64, 128, 256, 512], offload: ["on", "off"]}
+
+b200-fp4-dsr1-isb1-chat-32k:
+  tp4: {ep: 4, users: [1, 2, 4, 8, 16, 32, 64], offload: ["on", "off"]}
+  tp8: {ep: 8, users: [1, 2, 4, 8, 16, 32, 64, 128], offload: ["on", "off"]}
+
+b200-fp4-dsr1-isb1-code-131k:
+  tp8: {ep: 8, users: [1, 2, 4, 8, 16], offload: ["on", "off"]}
+
+# DSR1 131k reasoning cell — trace_replay backed by the HF publish
+# (wchen22/isb1-cc-traces). Exercises Cam's Apr 20 --no-max-tokens flag
+# against a reasoning corpus without requiring local dataset checkout.
+# TRACE_DIR alias: hf_wchen22--isb1-cc-traces
+#   (subset consumed by this cell: extension_131k/code_131k1k* and
+#    extension_131k/chat_131k1k*)
+b200-fp4-dsr1-isb1-code-131k-hf:
+  tp8: {ep: 8, users: [1, 2, 4, 8, 16], offload: ["on", "off"]}
+
+b200-fp4-qwen3-isb1-chat-500k-preview:
+  tp4: {users: [1, 2, 4], offload: ["on", "off"]}
+  tp8: {users: [1, 2, 4, 8], offload: ["on", "off"]}
+
+b200-fp4-qwen3-isb1-chat-1m-preview:
+  tp8: {users: [1, 2], offload: ["on", "off"]}
+
+mi355x-fp8-qwen3-isb1-code-8k:
+  tp2: {users: [2, 4, 8, 16, 32, 64], offload: ["on", "off"]}
+  tp4: {users: [2, 4, 8, 16, 32, 64, 128], offload: ["on", "off"]}
+
+mi355x-fp8-qwen3-isb1-chat-32k:
+  tp4: {users: [1, 2, 4, 8, 16, 32], offload: ["on", "off"]}
+
+h100-fp8-qwen3-isb1-code-8k-lmcache:
+  tp2: {users: [1, 2, 4, 8, 16, 32], offload: ["on", "off", "noprefix"]}
+  tp4: {users: [1, 2, 4, 8, 16, 32, 64], offload: ["on", "off", "noprefix"]}
+
+h200-fp8-qwen3-isb1-debug:
+  tp2: {users: [2], offload: ["off"]}
diff --git a/datasets/isb1/.gitattributes b/datasets/isb1/.gitattributes
new file mode 100644
index 000000000..006356f24
--- /dev/null
+++ b/datasets/isb1/.gitattributes
@@ -0,0 +1,2 @@
+exports/**/*.json filter=lfs diff=lfs merge=lfs -text linguist-generated=true
+converted/**/*.json filter=lfs diff=lfs merge=lfs -text linguist-generated=true
diff --git a/datasets/isb1/HF_PUBLISH.md b/datasets/isb1/HF_PUBLISH.md
new file mode 100644
index 000000000..28f5ae164
--- /dev/null
+++ b/datasets/isb1/HF_PUBLISH.md
@@ -0,0 +1,196 @@
+# HF publication recipe for ISB1 converted traces
+
+Mirror `datasets/isb1/converted/` to Hugging Face so Cam's
+`TRACE_DIR=hf_<org>--<repo>` path works immediately with kv-cache-tester.
+Preferred target: `semianalysisai/isb1-cc-traces`.
+Fallback if org write access is unavailable: `ocwc22/isb1-cc-traces`.
+
+## 1. What gets published
+
+This publish package is the checked-in trio below:
+
+- `datasets/isb1/converted/` — 179 validated kv-cache-tester trace JSON files
+- `datasets/isb1/converted/manifest.json` — corpus metadata (`1226` total requests)
+- `datasets/isb1/hf_dataset_card.md` — staged to HF as `README.md`
+
+The consumer contract is unchanged: Cam's replay scripts interpret
+`hf_<org>--<repo>` as a Hugging Face dataset source, hydrate it locally, and
+then invoke the existing replay path.
+
+## 2. Pre-flight validation
+
+Run the stdlib validator before every publish attempt:
+
+```bash
+python3 tools/validate_kvcache_tester_trace.py datasets/isb1/converted/
+```
+
+Expected result:
+
+- `✓ 179 files valid | 0 failed`
+- Exit code `0`
+
+If validation fails, stop and fix the source corpus before publishing. Do not
+push a broken dataset mirror to HF.
+
+## 3. Python version
+
+`tools/publish_hf_dataset.py` imports `huggingface_hub >= 0.24`, which in turn
+requires Python 3.10+. On macOS the system `/usr/bin/python3` is 3.9 and does
+not ship `huggingface_hub`; do not use it.
+
+Use Python 3.13 explicitly:
+
+```bash
+/opt/homebrew/opt/python@3.13/bin/python3.13 -m pip install --user huggingface_hub
+/opt/homebrew/opt/python@3.13/bin/python3.13 tools/publish_hf_dataset.py --help
+```
+
+Or activate a virtualenv / pyenv shim that resolves to 3.10+ before running any
+of the commands below. If you see `ModuleNotFoundError: huggingface_hub`, you
+are on 3.9 — switch interpreters first.
+
+## 4. Token setup
+
+Authenticate with a token that has write access to the destination namespace:
+
+```bash
+huggingface-cli login
+```
+
+If you prefer explicit token injection:
+
+```bash
+export HF_TOKEN=hf_xxx
+huggingface-cli login --token "$HF_TOKEN"
+```
+
+## 5. Dry-run the publish package locally
+
+The uploader script stages the converted corpus plus the dataset card and
+prints the exact file list it would upload without making any remote changes.
+
+```bash
+python3 tools/publish_hf_dataset.py \
+  --source datasets/isb1/converted/ \
+  --repo semianalysisai/isb1-cc-traces \
+  --private \
+  --dry-run
+```
+
+Use the fallback namespace instead if needed:
+
+```bash
+python3 tools/publish_hf_dataset.py \
+  --source datasets/isb1/converted/ \
+  --repo ocwc22/isb1-cc-traces \
+  --private \
+  --dry-run
+```
+
+## 6. Publish for real
+
+Once the dry-run output looks correct and HF auth is configured, publish with
+one of the exact commands below.
+
+Private-first publish:
+
+```bash
+python3 tools/publish_hf_dataset.py \
+  --source datasets/isb1/converted/ \
+  --repo semianalysisai/isb1-cc-traces \
+  --private \
+  --commit-message "Publish ISB-1 kv-cache-tester traces"
+```
+
+Or make the dataset public at creation time:
+
+```bash
+python3 tools/publish_hf_dataset.py \
+  --source datasets/isb1/converted/ \
+  --repo semianalysisai/isb1-cc-traces \
+  --public \
+  --commit-message "Publish ISB-1 kv-cache-tester traces"
+```
+
+Fallback org:
+
+```bash
+python3 tools/publish_hf_dataset.py \
+  --source datasets/isb1/converted/ \
+  --repo ocwc22/isb1-cc-traces \
+  --public \
+  --commit-message "Publish ISB-1 kv-cache-tester traces"
+```
+
+The script will:
+
+1. Stage `datasets/isb1/converted/` into a temporary upload tree
+2. Copy `datasets/isb1/hf_dataset_card.md` into that tree as `README.md`
+3. Create the dataset repo if it does not already exist
+4. Upload the staged folder with `huggingface_hub`
+5. Verify the published snapshot with `snapshot_download` into `/tmp`
+
+## 7. Post-publish verification
+
+### Repository-level verification
+
+Re-download the published dataset and re-run the validator against the hydrated
+copy:
+
+```bash
+huggingface-cli download semianalysisai/isb1-cc-traces \
+  --repo-type dataset \
+  --local-dir /tmp/isb1-cc-traces-verify
+python3 tools/validate_kvcache_tester_trace.py /tmp/isb1-cc-traces-verify
+```
+
+### Harness-level verification
+
+The exact consumer path for Cam is the existing `TRACE_DIR=hf_<org>--<repo>`
+contract. In the replay harness checkout, the closest end-to-end verification
+command is:
+
+```bash
+TRACE_DIR=hf_semianalysisai--isb1-cc-traces \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+If the SemianalysisAI org is not available, swap in the fallback namespace:
+
+```bash
+TRACE_DIR=hf_ocwc22--isb1-cc-traces \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+## 8. Consumer note for Cam
+
+This is the zero-friction handoff:
+
+```bash
+TRACE_DIR=hf_semianalysisai--isb1-cc-traces \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+No code change is required in Cam's harness. The only user action is publishing
+this dataset repo once with valid HF credentials.
+
+## 9. Versioning guidance
+
+When new traces land:
+
+1. Regenerate `datasets/isb1/converted/manifest.json`
+2. Re-run `tools/validate_kvcache_tester_trace.py`
+3. Re-run the uploader dry-run
+4. Publish with a commit message that records the corpus revision
+5. Record the InferenceX commit SHA and the HF dataset revision together
+
+Consumers that need immutability should pin an HF revision instead of floating
+on `main`.
+
+## Notes
+
+- Publish converted artifacts and metadata only
+- Do not modify `datasets/isb1/converted/**` during publication prep
+- Keep the uploaded layout compatible with kv-cache-tester's existing
+  `TRACE_DIR=hf_<org>--<repo>` convention
diff --git a/datasets/isb1/README.md b/datasets/isb1/README.md
new file mode 100644
index 000000000..aa3c4ef0e
--- /dev/null
+++ b/datasets/isb1/README.md
@@ -0,0 +1,298 @@
+# ISB1 replay artifacts for InferenceX
+
+This directory is the InferenceX-side consumer package for ISB1 replay.
+
+InferenceX consumes committed file artifacts only:
+- replay export JSON bundles under `datasets/isb1/exports/`
+- replay via [`tools/isb1_to_kvcache_tester.py`](../../tools/isb1_to_kvcache_tester.py) + Cam's [`kv-cache-tester`](https://github.com/callanjfox/kv-cache-tester)
+- consumer configs in `.github/configs/isb1-*.yaml`
+
+InferenceX does **not** import external runtime code and does **not** make
+live-serving claims from export-file existence alone.
+
+---
+
+## Why not random data?
+
+Random-data benchmarks show worst-case performance. Real inference workloads
+have multi-turn conversations where each turn shares context with previous
+turns. This enables:
+
+- **Prefix caching** — 60-95% of each request's tokens are shared with the
+  previous turn. Prefix cache hit rates directly affect throughput.
+- **KV cache reuse** — the server reuses computed KV cache entries instead of
+  recomputing them. This is the biggest performance optimization in production.
+- **Realistic offload behavior** — KV cache grows across turns, eventually
+  exceeding GPU memory and requiring CPU offload. Random data never reaches
+  this point because each request is independent.
+
+These traces stress-test the exact KV cache behaviors that determine real
+production performance.
+
+---
+
+## Coverage
+
+Strict audit rule: count only model-architecture-valid cells. Per-model context
+limits (DSR1 163,840; GPT-OSS 131,072; Qwen3.5 1,010,000) produce N/A rows
+above each model's max.
+
+### Verified coverage
+
+| Model | Chat | Code |
+|---|---|---|
+| `dsr1` | `8k`, `32k`, `64k`, `131k` | `8k`, `32k`, `64k`, `131k` |
+| `gptoss` | `8k`, `32k`, `64k`, `131k` | `8k`, `32k`, `64k`, `131k` |
+| `qwen3.5` | `8k`, `32k`, `64k`, `131k`, `500k` | `8k`, `32k`, `64k`, `131k`, `500k` |
+
+### Existing preview artifacts
+
+- `gptoss` `500k` chat/code preview files exist at `reviewed_preview` tier
+- `qwen3.5` `1M` chat/code preview files exist at `gated` tier (consumed only
+  through `isb1-qwen-1m-preview.yaml`)
+- `dsr1` has no `500k` or `1M` lane because the model tops out at `163,840`
+
+---
+
+## Inventory
+
+### Export-file layout (post-flatten)
+
+Bundle files are flat per context-band directory — framework-specific variants
+are consolidated into single files whose internal cell rows carry runtime
+metadata.
+
+| Subtree | Bundle files | Notes |
+|---|---:|---|
+| `core/` | 4 | 8K chat/code × {generic, qwen3.5} |
+| `extension_32k/` | 4 | 32K chat/code × {generic, qwen3.5} |
+| `extension_64k/` | 4 | 64K chat/code × {generic, qwen3.5} |
+| `extension_131k/` | 5 | 131K chat/code × {generic, qwen3.5, dsr1 chat} |
+| `preview/long_context_500k/` | 4 + 2 manifests | 500K chat/code × {gptoss, qwen3.5} |
+| `preview/long_context_1m/` | 2 + 1 manifest | 1M chat/code × qwen3.5 |
+
+All export files are valid JSON and can be consumed via [`tools/isb1_to_kvcache_tester.py`](../../tools/isb1_to_kvcache_tester.py) + Cam's [`kv-cache-tester`](https://github.com/callanjfox/kv-cache-tester); see [How to consume](#how-to-consume).
+
+---
+
+## Support-status vocabulary
+
+ISB1 replay surfaces classify under the five-class support vocabulary:
+
+- `supported` — core 8K replay path
+- `reviewed_preview` — 32K / 64K / 131K extensions, 500K preview
+- `gated` — 1M preview (manual config only)
+- `artifact_only` — retained artifacts without live replay
+- `unsupported` — not a valid path
+
+No ISB1 surface claims `live_benchmark_certification`; all claims are bounded
+to `dataset_replay_verified`.
+
+---
+
+## Claim boundary
+
+Safe claims:
+- InferenceX carries the ISB1 replay corpus described above.
+- Strict replay-file coverage is **26 valid / 0 failed / 10 N/A** across 36
+  (model × band × workload) combinations.
+- DSR1 strict coverage stops at `131k`.
+- GPT-OSS strict coverage stops at `131k`.
+- Qwen3.5 strict coverage reaches `500k`.
+- GPT-OSS `500k` and Qwen3.5 `1M` files exist but are excluded from the strict
+  pass count (`reviewed_preview` and `gated` tiers, respectively).
+
+Unsafe claims:
+- `26/26` valid cells verified (10 N/A due to model `max_position_embeddings`
+  limits)
+- strict GPT-OSS `500k` coverage
+- strict Qwen3.5 `1M` coverage
+- turning preview-file existence into live benchmark certification
+
+---
+
+## How to consume
+
+The supported consumption path is [`tools/isb1_to_kvcache_tester.py`](../../tools/isb1_to_kvcache_tester.py) + Cam's [`kv-cache-tester`](https://github.com/callanjfox/kv-cache-tester) `trace_replay_tester.py --trace-directory` flow.
+
+This is the path that lets ISB1 traces plug into SemiAnalysis's existing Slurm benchmarking pipeline without the consumer having to read any InferenceX-local replay harness.
+
+### Step 1 — fetch the bundles (LFS)
+
+From a clone of InferenceX:
+
+```bash
+git lfs install
+git lfs pull --include='datasets/isb1/exports/**/*.json'
+```
+
+Or, if the bundles are published to Hugging Face (see
+[HF publication](#hf-publication)), download directly:
+
+```bash
+huggingface-cli download <org>/<repo> \
+    --repo-type dataset \
+    --local-dir ./isb1_bundles
+```
+
+### Step 2 — convert one bundle to `kv-cache-tester` format
+
+```bash
+python tools/isb1_to_kvcache_tester.py \
+    --export-file datasets/isb1/exports/core/chat_8k1k_qwen3.5.json \
+    --output-dir  traces_isb1/core_chat_qwen/ \
+    --runtime-stack-id standalone:vllm \
+    --hardware-profile-id nvidia:h200_sxm_141gb \
+    --canonical-model-id qwen3_5_397b_a17b \
+    --support-status supported
+```
+
+This writes one `trace_<conversation_id>.json` per cell that passes the
+filters, in the flat layout `trace_replay_tester.py --trace-directory`
+expects. The schema matches `kv-cache-tester@main` (`trace.id`, `requests[].t/in/out/hash_ids`),
+so `normalize_trace()` accepts it as-is.
+
+To convert every bundle in one shot:
+
+```bash
+python tools/isb1_to_kvcache_tester.py \
+    --export-root datasets/isb1/exports/ \
+    --output-dir  traces_isb1/
+```
+
+### Pre-converted sidecar
+
+This repo carries a pre-converted mirror at:
+
+- `datasets/isb1/converted/`
+
+Feed that mirror directly to `kv-cache-tester` with:
+
+```bash
+python trace_replay_tester.py --trace-directory datasets/isb1/converted/ --tokenizer Qwen/Qwen2.5-Coder-32B-Instruct --block-size 64
+```
+
+Mapping convention:
+
+- one trace file per ISB1 conversation/event
+- each trace filename is prefixed with the source bundle id
+
+### Step 3 — replay against a running vLLM / SGLang server
+
+Using PR #993's own recipes (e.g. `benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh`),
+set `TRACE_DIR` to the converted directory and let the existing Slurm wiring
+pick it up:
+
+```bash
+TRACE_DIR=$PWD/traces_isb1/core_chat_qwen \
+MODEL=Qwen/Qwen3.5-397B-A17B-FP8 \
+TP=8 USERS=8 OFFLOAD_MODE=off TOTAL_CPU_DRAM_GB=0 \
+RESULT_DIR=$PWD/results/isb1_smoke \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+Or, equivalently, invoke Cam's tester directly:
+
+```bash
+python $KV_CACHE_TESTER_DIR/trace_replay_tester.py \
+    --api-endpoint http://127.0.0.1:8888 \
+    --trace-directory $PWD/traces_isb1/core_chat_qwen \
+    --output-dir      $PWD/results/isb1_smoke \
+    --start-users 2 --max-users 2 --test-duration 60
+```
+
+### Step 4 — verify the result
+
+```bash
+jq '.' results/isb1_smoke/results.json | head
+```
+
+Expected:
+
+- `trace_replay_tester.py` logs show `Loaded N traces (filtered from N)`.
+- Cache-hit rate reported during the run is non-zero for multi-turn bundles
+  (because each turn's `hash_ids` extends the previous turn's prefix).
+- Completed sessions ≥ 1; HTTP error count = 0.
+
+---
+
+## Smoke test
+
+The one-liner below is the binary go/no-go for "does this PR actually help
+SemiAnalysis":
+
+```bash
+# Assumes a vLLM OpenAI server is up on :8888 serving the model.
+python tools/isb1_to_kvcache_tester.py \
+    --export-file datasets/isb1/exports/core/chat_8k1k_qwen3.5.json \
+    --output-dir  /tmp/isb1_proof/ \
+    --canonical-model-id qwen3_5_397b_a17b \
+&& python $KV_CACHE_TESTER_DIR/trace_replay_tester.py \
+    --api-endpoint http://127.0.0.1:8888 \
+    --trace-directory /tmp/isb1_proof/ \
+    --output-dir      /tmp/isb1_proof/out \
+    --start-users 1 --max-users 1 --test-duration 30
+```
+
+Pass criteria:
+
+| Artifact | Threshold |
+|---|---|
+| Shim exit code | `0` |
+| `trace_replay_tester.py` exit code | `0` |
+| `Loaded N traces` (N) | `≥ 1` |
+| Completed sessions | `≥ 1` |
+| HTTP errors | `0` |
+
+Any failure of the above means the PR is not actually plumbed end-to-end for
+this bundle and should be reproduced against Cam's `trace_replay_tester.py`
+before being claimed as compatible.
+
+### Validate before publishing
+
+Before publishing or mirroring `datasets/isb1/converted/`, run `python3 tools/validate_kvcache_tester_trace.py datasets/isb1/converted/` to catch schema drift early: missing required keys, invalid `block_size`, and broken prefix-extending `hash_ids` that would otherwise fail inside Cam's replay sweep.
+
+---
+
+## HF publication
+
+The `kv-cache-tester` Slurm recipes accept an HF dataset source via the
+`hf_<org>--<repo>` prefix convention on `TRACE_DIR` — the wrapper `.sh`
+scripts download with `huggingface-cli` and point the tester at the local
+mirror.
+
+To publish an HF mirror of these bundles:
+
+1. Create a dataset repo (e.g. `semianalysisai/isb1-core-v0`).
+2. Mirror the directory layout of `datasets/isb1/exports/` exactly.
+   (Do not copy the inner `datasets/isb1/.gitattributes` — one top-level
+   LFS-only `.gitattributes` at the HF repo root is sufficient.)
+3. For each published bundle, run
+   `tools/isb1_to_kvcache_tester.py --export-root <downloaded dir> --output-dir <out>`
+   locally to verify the conversion stays green at the new revision.
+4. Pin revisions by HF branch/tag matching the producer's
+   `schema_version` (e.g. `v0.2.0`).
+
+Once published, Cam's Slurm scripts can consume a bundle with no code change:
+
+```bash
+TRACE_DIR=hf_semianalysisai--isb1-core-v0 \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+(Where the `.sh` does `huggingface-cli download semianalysisai/isb1-core-v0`
+into a scratch dir, then runs the converter shim against it before
+invoking `trace_replay_tester.py`.)
+
+---
+
+## Related docs
+
+- [`COEXISTENCE_WITH_KV_CACHE_TESTER.md`](COEXISTENCE_WITH_KV_CACHE_TESTER.md) —
+  how PR #1032 coexists with PR #993's kv-cache-tester
+- [`GMI_EXECUTION_PLAN.md`](GMI_EXECUTION_PLAN.md) — bare-metal execution
+  runbook for ISB1 replay on GMI Cloud Hopper and Blackwell
+- [`exports/preview/long_context_500k/README.md`](exports/preview/long_context_500k/README.md) —
+  500K preview lane claim boundary
+- [`exports/preview/long_context_1m/README.md`](exports/preview/long_context_1m/README.md) —
+  1M gated preview lane claim boundary
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new file mode 100644
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--- /dev/null
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new file mode 100644
index 000000000..7378882af
--- /dev/null
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new file mode 100644
index 000000000..8fd721f45
--- /dev/null
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index 000000000..5a09c88f5
--- /dev/null
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new file mode 100644
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--- /dev/null
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new file mode 100644
index 000000000..709a833b2
--- /dev/null
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new file mode 100644
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--- /dev/null
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index 000000000..bb1ca8974
--- /dev/null
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diff --git a/datasets/isb1/exports/extension_64k/code_64k1k_qwen3.5.json b/datasets/isb1/exports/extension_64k/code_64k1k_qwen3.5.json
new file mode 100644
index 000000000..73beb4b57
--- /dev/null
+++ b/datasets/isb1/exports/extension_64k/code_64k1k_qwen3.5.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/datasets/isb1/exports/preview/long_context_1m/README.md b/datasets/isb1/exports/preview/long_context_1m/README.md
new file mode 100644
index 000000000..952fa11d2
--- /dev/null
+++ b/datasets/isb1/exports/preview/long_context_1m/README.md
@@ -0,0 +1,33 @@
+# Gated 1M-class Qwen3.5 preview lane
+
+This directory carries the committed InferenceX-side Qwen3.5 artifacts for a
+bounded `1M`-class ISB1 coding replay preview.
+
+## What these files are
+
+- dedicated replay bundles restricted to `qwen3_5_397b_a17b`
+- producer cells currently materialized for `standalone:sglang` only; additional runtimes land here when the producer regenerates the bundle
+- committed bundle coverage for `nvidia:b200_sxm_180gb`, `nvidia:h100_sxm_80gb`, and `nvidia:h200_sxm_141gb`
+- restricted to `ulc2_1m_plus`
+- restricted to `support_status=reviewed_preview` at the selected export-cell level
+- restricted to `benchmark_certification_status=dataset_replay_verified`
+- exposed downstream only through the separate manual config
+  `.github/configs/isb1-qwen-1m-preview.yaml`
+- explicit `max-model-len: 1048576` when the manual config is used
+
+## Current claim boundary
+
+These files are committed preview artifacts plus a gated/manual validation path.
+They do **not** imply ordinary runnable ISB1 support in `isb1-master.yaml`.
+
+Safe wording:
+- InferenceX carries bounded 1M-class Qwen3.5 replay preview artifacts.
+- InferenceX carries a separate gated/manual Qwen3.5 1M validation path.
+
+Unsafe wording:
+- native 1M served-lane support
+- ordinary/general runnable consumer support
+- KV-offload certification
+
+See `manifest.json` for the exact preview boundary and
+`.github/configs/isb1-qwen-1m-preview.yaml` for the manual validation surface.
diff --git a/datasets/isb1/exports/preview/long_context_1m/inferencex_trace_replay__chat_qwen3.5_ulc2_1m_preview_v1.json b/datasets/isb1/exports/preview/long_context_1m/inferencex_trace_replay__chat_qwen3.5_ulc2_1m_preview_v1.json
new file mode 100644
index 000000000..a37edd86a
--- /dev/null
+++ b/datasets/isb1/exports/preview/long_context_1m/inferencex_trace_replay__chat_qwen3.5_ulc2_1m_preview_v1.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fd16cc4de821cf4803d662e4c5091359b7a5b2b730d03c976eb331be0cd6b1cb
+size 286074
diff --git a/datasets/isb1/exports/preview/long_context_1m/inferencex_trace_replay__coding_qwen3.5_ulc2_1m_preview_v1.json b/datasets/isb1/exports/preview/long_context_1m/inferencex_trace_replay__coding_qwen3.5_ulc2_1m_preview_v1.json
new file mode 100644
index 000000000..5fd23f78c
--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:35572a38f071d240519f7fdbd60aa203eb4832d835df97a8a5ef874d5d402456
+size 122465512
diff --git a/datasets/isb1/exports/preview/long_context_1m/manifest.json b/datasets/isb1/exports/preview/long_context_1m/manifest.json
new file mode 100644
index 000000000..f75682fa0
--- /dev/null
+++ b/datasets/isb1/exports/preview/long_context_1m/manifest.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:420964735f3182aed1147969a21532ea2c7e2c1b8b89c725c0d39e1358dd7975
+size 1749
diff --git a/datasets/isb1/exports/preview/long_context_500k/README.md b/datasets/isb1/exports/preview/long_context_500k/README.md
new file mode 100644
index 000000000..206708952
--- /dev/null
+++ b/datasets/isb1/exports/preview/long_context_500k/README.md
@@ -0,0 +1,46 @@
+# Bounded 500k-class preview lanes
+
+This directory carries the smallest honest InferenceX consumer handoff for bounded
+`500k`-class ISB1 coding replay paths.
+
+## What these files are
+
+- dedicated replay bundles derived from committed `131k1k` extension exports
+- restricted to `gpt_oss_120b` or `qwen3_5_397b_a17b`
+- restricted to `xlc2_384k_512k`
+- producer cells currently materialized for `standalone:sglang` only; additional runtimes land here when the producer regenerates the bundle
+- restricted to `nvidia:b200_sxm_180gb`, `nvidia:h100_sxm_80gb`, and `nvidia:h200_sxm_141gb`
+- restricted to `support_status=reviewed_preview`
+- restricted to `benchmark_certification_status=dataset_replay_verified`
+- wired in the consumer with explicit `max-model-len: 524288`
+
+## What these files are not
+
+- not a native InferenceX `500k+` served lane
+- not a native InferenceX `1M+` served lane
+- not a supported-tier long-context expansion
+- not a chat preview lane
+- not an offload-depth lane
+- not a KV-offload certification claim
+
+## Why the files exist
+
+The existing `extension_131k/*/code_131k1k.json` and model-scoped
+`code_131k1k_qwen3.5.json` bundles already contain honest `xlc2_384k_512k`
+replay cells, but they are mixed with lower-band cells. The InferenceX workflow
+selects rows by runtime, hardware, model, and support tier — not by
+`context_band`.
+
+These dedicated files isolate only the `xlc2_384k_512k` rows so InferenceX can
+run bounded `500k`-class previews without over-selecting lower-band cells.
+
+## Consumer contract
+
+- consumed only through the coding `500k` preview stanzas in `isb1-master.yaml`
+- `isb1-master.yaml` pins these rows as `reviewed_preview`
+- `isb1-master.yaml` pins `max-model-len: 524288`
+- current search space is intentionally bounded to single-concurrency preview execution
+- result processing preserves `context_bands`, `profile_id`, and the producer handoff claim boundary
+
+See `manifest.json` for the GPT-OSS derivation record and `manifest_qwen3.5.json`
+for the Qwen derivation record.
diff --git a/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__chat_gptoss_xlc2_500k_preview_v1.json b/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__chat_gptoss_xlc2_500k_preview_v1.json
new file mode 100644
index 000000000..ed88496d8
--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e200fb08b06dffc83189c393c0711e090cf8f579c719e69512e2fcfb3933e33
+size 153848
diff --git a/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__chat_qwen3.5_xlc2_500k_preview_v1.json b/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__chat_qwen3.5_xlc2_500k_preview_v1.json
new file mode 100644
index 000000000..37f8e26a2
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__coding_gptoss_xlc2_500k_preview_v1.json b/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__coding_gptoss_xlc2_500k_preview_v1.json
new file mode 100644
index 000000000..f996cc838
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__coding_qwen3.5_xlc2_500k_preview_v1.json b/datasets/isb1/exports/preview/long_context_500k/inferencex_trace_replay__coding_qwen3.5_xlc2_500k_preview_v1.json
new file mode 100644
index 000000000..00046987f
--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/datasets/isb1/exports/preview/long_context_500k/manifest.json b/datasets/isb1/exports/preview/long_context_500k/manifest.json
new file mode 100644
index 000000000..3748315e9
--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1edb16904b7501b726c10a21bccd363d245467e08c91843a841eaf8791082c67
+size 1636
diff --git a/datasets/isb1/exports/preview/long_context_500k/manifest_qwen3.5.json b/datasets/isb1/exports/preview/long_context_500k/manifest_qwen3.5.json
new file mode 100644
index 000000000..b051057ef
--- /dev/null
+++ b/datasets/isb1/exports/preview/long_context_500k/manifest_qwen3.5.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34ae432fa1b8aa73c6109cddbf036b7ffb32d6528d296f65da70538bd9e00747
+size 1594
diff --git a/datasets/isb1/hf_dataset_card.md b/datasets/isb1/hf_dataset_card.md
new file mode 100644
index 000000000..0815b03a9
--- /dev/null
+++ b/datasets/isb1/hf_dataset_card.md
@@ -0,0 +1,144 @@
+---
+pretty_name: ISB-1 KV-Cache-Tester Traces
+tags:
+  - kv-cache
+  - inference-benchmarking
+  - vllm
+  - long-context
+  - multi-turn
+license: apache-2.0
+task_categories:
+  - text-generation
+size_categories:
+  - 1M<n<10M
+configs:
+  - config_name: core
+    default: true
+    data_files: "core/**/*.json"
+  - config_name: extension_32k
+    data_files: "extension_32k/**/*.json"
+  - config_name: extension_64k
+    data_files: "extension_64k/**/*.json"
+  - config_name: extension_131k
+    data_files: "extension_131k/**/*.json"
+  - config_name: preview_500k
+    data_files: "preview/long_context_500k/**/*.json"
+  - config_name: preview_1m
+    data_files: "preview/long_context_1m/**/*.json"
+---
+
+# ISB-1 KV-Cache-Tester Traces
+
+## Overview
+
+This dataset is a Hugging Face mirror of `datasets/isb1/converted/` from
+`SemiAnalysisAI/InferenceX`. It packages the pre-converted ISB-1 multi-turn
+trace corpus in the JSON schema already consumed by the kv-cache-tester replay
+path, so downstream users can switch from a local directory to
+`TRACE_DIR=hf_<org>--<repo>` with no harness changes.
+
+Current corpus summary:
+
+- 179 validated trace JSON files
+- 1,226 total requests across the corpus
+- ~9.26 MiB on disk including `manifest.json`
+- Context bands spanning 8k, 32k, 64k, 131k, 500k preview, and 1m preview
+- Model coverage including DeepSeek-R1-0528, GPT-OSS-120B, GLM-5,
+  MiniMax-M2.5, and Qwen3.5-397B-A17B variants present in the source corpus
+
+Preferred dataset name:
+
+- `semianalysisai/isb1-cc-traces`
+
+Fallback if SemiAnalysisAI org write access is unavailable:
+
+- `ocwc22/isb1-cc-traces`
+
+The intended consumer is Cam's existing kv-cache-tester replay flow, which
+already accepts `hf_<org>--<repo>` as a `TRACE_DIR` source and hydrates the
+remote dataset locally before replay.
+
+## Schema
+
+Each JSON file is one replayable trace object with the following top-level
+fields:
+
+| Field | Type | Notes |
+| --- | --- | --- |
+| `id` | `str` | Stable trace/session identifier |
+| `models` | `list[str]` | Model family identifiers for the trace |
+| `block_size` | `int` | Hash-block size used for `hash_ids`; current corpus uses `64` |
+| `hash_id_scope` | `str` | `local` or `global`; validated by the stdlib checker |
+| `requests` | `list[object]` | Ordered replay requests |
+| `tool_tokens` | `int` | Optional token accounting |
+| `system_tokens` | `int` | Optional token accounting |
+| `totals` / `isb1` | `object` | Source metadata carried through from conversion |
+
+Each request entry includes the fields kv-cache-tester expects today:
+
+- `type`
+- `t`
+- `in`
+- `out`
+- `hash_ids`
+- optional `model`, `stop`, `input_types`, `output_types`, `api_time`,
+  `think_time`
+
+Before publishing or consuming the corpus, validate it with the bundled
+stdlib-only checker:
+
+```bash
+python3 tools/validate_kvcache_tester_trace.py datasets/isb1/converted/
+```
+
+Exit codes:
+
+- `0` = all trace files valid
+- `1` = one or more trace files failed validation
+- `2` = usage or path error
+
+## How to use
+
+For zero-friction consumption through the existing replay wrapper, point
+`TRACE_DIR` at the HF dataset name in `hf_<org>--<repo>` form:
+
+```bash
+TRACE_DIR=hf_semianalysisai--isb1-cc-traces \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+That is the whole integration contract: the wrapper handles the HF download and
+passes the hydrated local mirror into the replay runner. If the preferred org
+is unavailable, the fallback form is identical:
+
+```bash
+TRACE_DIR=hf_ocwc22--isb1-cc-traces \
+bash experimental/multiturn/benchmarks/single_node/multiturn_fp8_h200_trace_replay.sh
+```
+
+For local inspection after download, the dataset also includes:
+
+- `manifest.json` — corpus summary and per-trace metadata
+- the original directory layout under `core/`, `extension_32k/`,
+  `extension_64k/`, `extension_131k/`, and `preview/`
+
+## License
+
+This corpus follows the repository license in `SemiAnalysisAI/InferenceX`,
+which is Apache-2.0.
+
+## Citation
+
+If you use this corpus in a benchmark, report, or derivative evaluation, cite
+both the InferenceX repository and the dataset name/revision that you consumed.
+A lightweight citation template is below.
+
+```bibtex
+@misc{isb1_kvcache_tester_traces_2026,
+  title        = {ISB-1 KV-Cache-Tester Traces},
+  author       = {SemiAnalysisAI},
+  year         = {2026},
+  howpublished = {Hugging Face dataset repository},
+  note         = {Preferred repo: semianalysisai/isb1-cc-traces; fallback: ocwc22/isb1-cc-traces}
+}
+```
diff --git a/tools/isb1_to_kvcache_tester.py b/tools/isb1_to_kvcache_tester.py
new file mode 100644
index 000000000..b454e04b6
--- /dev/null
+++ b/tools/isb1_to_kvcache_tester.py
@@ -0,0 +1,771 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: Apache-2.0
+"""Convert ISB1 replay bundles into `kv-cache-tester` trace files.
+
+Produces per-conversation JSON files compatible with
+`callanjfox/kv-cache-tester`'s `trace_replay_tester.py --trace-directory`
+input format (see upstream ``TraceManager.load_traces`` / ``normalize_trace``
+in that repo). Works on both ISB1 bundle adapters shipped by this PR:
+
+- ``inferencex_multiturn``     (direct ``session.turns[].messages`` shape)
+- ``inferencex_trace_replay``  (``events[].input_messages`` shape, with
+  optional schema ``0.2.0`` ``prefix_ref`` sidecar hydration)
+
+This shim is the ONLY glue between SemiAnalysis's trace-replay tester and our
+ISB1 bundles. It emits one ``trace_<NNNN>.json`` per conversation/cell and
+does not import or execute any benchmark harness. It has no third-party
+dependencies: standard library only.
+
+Schema compatibility
+--------------------
+
+The ``kv-cache-tester`` input schema (verified against
+``trace_replay_tester.py@main``):
+
+    {
+      "id":              "<trace identifier>",     # str, required
+      "models":          ["<canonical model id>"],  # list[str], optional
+      "block_size":      64,                        # int, optional (default 64)
+      "hash_id_scope":   "local",                   # str, optional
+      "tool_tokens":     0,                         # int, optional
+      "system_tokens":   0,                         # int, optional
+      "requests": [
+        {
+          "t":           0.0,                       # float, arrival offset (s)
+          "type":        "n",                       # "n" non-streaming | "s" streaming
+          "model":       "<canonical model id>",
+          "in":          <int>,                     # input tokens
+          "out":         <int>,                     # output tokens
+          "hash_ids":    [1, 2, ..., N],            # prefix-reuse block sequence
+          "input_types":  ["text"],
+          "output_types": ["text"],
+          "stop":        "end_turn",
+          "think_time":  <float>                    # seconds before request
+        }, ...
+      ]
+    }
+
+The ``hash_ids`` field is the critical one. ``kv-cache-tester`` computes the
+cache hit rate by walking each turn's ``hash_ids`` and counting hits against
+the previous turn's set, stopping at the first miss. For multi-turn
+conversations where every turn builds on the previous history, the correct
+mapping is the monotonically extending prefix ``[1, 2, ..., ceil(in/block)]``
+— earlier blocks are reused across turns and the new user message + assistant
+turn extend the prefix.
+
+Usage
+-----
+
+Single bundle:
+
+    python tools/isb1_to_kvcache_tester.py \
+        --export-file datasets/isb1/exports/core/chat_8k1k_qwen3.5.json \
+        --output-dir  traces_isb1/
+
+Whole directory tree (reproduces the ``traces_isb1/<band>/<bundle>/`` layout):
+
+    python tools/isb1_to_kvcache_tester.py \
+        --export-root datasets/isb1/exports/ \
+        --output-dir  traces_isb1/
+
+Filters (subset by cell, matching the legacy replay-loader semantics):
+
+    python tools/isb1_to_kvcache_tester.py \
+        --export-file datasets/isb1/exports/core/chat_8k1k.json \
+        --output-dir  traces_isb1/core_chat_qwen_h200/ \
+        --runtime-stack-id standalone:vllm \
+        --hardware-profile-id nvidia:h200_sxm_141gb \
+        --canonical-model-id qwen3_5_397b_a17b
+
+Smoke run against Cam's tester (after a vLLM OpenAI server is up on :8888):
+
+    python /path/to/kv-cache-tester/trace_replay_tester.py \
+        --api-endpoint http://127.0.0.1:8888 \
+        --trace-directory traces_isb1/core_chat_qwen_h200/ \
+        --output-dir       /tmp/isb1_result/ \
+        --start-users 2 --max-users 2 --test-duration 60
+
+The shim is deterministic: same input bundle, same filters, same block_size
+produces byte-identical output trace files.
+"""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import math
+import sys
+from pathlib import Path
+from typing import Any, Iterable, Optional
+
+# -----------------------------------------------------------------------------
+# Constants
+# -----------------------------------------------------------------------------
+
+SUPPORTED_ADAPTERS = ("inferencex_multiturn", "inferencex_trace_replay")
+DEFAULT_BLOCK_SIZE = 64       # matches kv-cache-tester default
+DEFAULT_IMAGE_TOKENS = 512    # matches DEFAULT_IMAGE_TOKEN_ESTIMATE in our exporter
+FALLBACK_OUTPUT_TOKENS = 256  # used only if the bundle has no expected_output_tokens
+
+
+# -----------------------------------------------------------------------------
+# Token counting (stdlib-only, matches the legacy replay-harness fallback token count)
+# -----------------------------------------------------------------------------
+
+def _fallback_text_token_count(text: str) -> int:
+    """Approximate token count (≈ 4 chars / token).
+
+    This matches the fallback path in the legacy replay harness
+    and mirrors Cam's tester, which does its own tokenization at replay time
+    from synthetic content. The only thing this shim must emit accurately is
+    the *block count* (``ceil(in_tokens / block_size)``); a ~10-20% error in
+    the absolute token count still produces the correct prefix-reuse pattern
+    because block IDs are assigned in order.
+    """
+    stripped = (text or "").strip()
+    if not stripped:
+        return 0
+    return max(1, math.ceil(len(stripped) / 4))
+
+
+# -----------------------------------------------------------------------------
+# Message flattening (mirrors the legacy replay-harness message extraction)
+# -----------------------------------------------------------------------------
+
+def _render_block_as_text(block: dict[str, Any]) -> str:
+    block_type = str(block.get("type", "text"))
+    text = (block.get("text") or "").strip()
+    if block_type == "text":
+        return text
+    if block_type == "code":
+        return f"[CODE]\n{text}" if text else "[CODE]"
+    if block_type == "log":
+        return f"[LOG]\n{text}" if text else "[LOG]"
+    if block_type == "document":
+        label = block.get("asset_path") or block.get("uri") or ""
+        if text and label:
+            return f"[DOCUMENT: {label}]\n{text}"
+        if text:
+            return f"[DOCUMENT]\n{text}"
+        return f"[DOCUMENT: {label}]" if label else "[DOCUMENT]"
+    if block_type == "table":
+        return f"[TABLE]\n{text}" if text else "[TABLE]"
+    if block_type == "image":
+        # images are approximated as fixed-cost tokens; no text to render
+        return ""
+    return text or ""
+
+
+def _extract_message_text(message: dict[str, Any]) -> str:
+    if isinstance(message.get("content"), str):
+        return message["content"]
+    blocks = message.get("content_blocks") or []
+    parts = [_render_block_as_text(b) for b in blocks if isinstance(b, dict)]
+    return "\n\n".join(p for p in parts if p)
+
+
+def _count_image_tokens(message: dict[str, Any], image_token_estimate: int) -> int:
+    blocks = message.get("content_blocks") or []
+    return sum(
+        image_token_estimate
+        for b in blocks
+        if isinstance(b, dict) and str(b.get("type")) == "image"
+    )
+
+
+def _count_message_tokens(message: dict[str, Any], image_token_estimate: int) -> int:
+    text_tokens = _fallback_text_token_count(_extract_message_text(message))
+    return text_tokens + _count_image_tokens(message, image_token_estimate)
+
+
+def _count_turn_input_tokens(
+    messages: list[dict[str, Any]],
+    image_token_estimate: int,
+) -> int:
+    return sum(_count_message_tokens(m, image_token_estimate) for m in messages)
+
+
+# -----------------------------------------------------------------------------
+# Prefix sidecar hydration (schema 0.2.0 inferencex_trace_replay bundles)
+# -----------------------------------------------------------------------------
+
+def _schema_version_at_least(observed: Any, required: str) -> bool:
+    if not isinstance(observed, str):
+        return False
+    try:
+        obs = tuple(int(x) for x in observed.split("."))
+        req = tuple(int(x) for x in required.split("."))
+    except ValueError:
+        return False
+    return obs >= req
+
+
+def _load_prefix_artifact(
+    bundle_path: Path,
+    prefix_ref: str,
+    prefix_entry: dict[str, Any],
+) -> dict[str, Any]:
+    rel_path = prefix_entry.get("path")
+    if not isinstance(rel_path, str) or not rel_path:
+        raise ValueError(
+            f"prefix_index[{prefix_ref!r}] missing 'path' in {bundle_path}"
+        )
+    artifact_path = (bundle_path.parent / rel_path).resolve()
+    if not artifact_path.exists():
+        raise FileNotFoundError(
+            f"prefix artifact not found: {artifact_path} (ref={prefix_ref!r})"
+        )
+    raw = artifact_path.read_bytes()
+
+    expected_sha = prefix_entry.get("sha256")
+    if isinstance(expected_sha, str) and expected_sha:
+        actual_sha = hashlib.sha256(raw).hexdigest()
+        if actual_sha.lower() != expected_sha.lower():
+            raise ValueError(
+                "prefix artifact sha256 mismatch for "
+                f"{prefix_ref!r}: expected {expected_sha}, got {actual_sha}"
+            )
+
+    try:
+        return json.loads(raw.decode("utf-8"))
+    except Exception as exc:
+        raise ValueError(
+            f"prefix artifact {artifact_path} is not valid JSON: {exc}"
+        ) from exc
+
+
+def _merge_prefix_into_cell(cell: dict[str, Any], prefix_payload: dict[str, Any]) -> None:
+    # Schema 0.2.0 bundles store events in the prefix artifact; merge back in-place.
+    # (Mirrors the legacy replay-harness prefix merge behavior.)
+    prefix_events = prefix_payload.get("events") or []
+    cell.setdefault("events", []).extend(prefix_events)
+    # Also merge trace_metadata if the prefix carries extras; preserve cell priority.
+    p_meta = prefix_payload.get("trace_metadata") or {}
+    if isinstance(p_meta, dict) and p_meta:
+        merged = dict(p_meta)
+        merged.update(cell.get("trace_metadata") or {})
+        cell["trace_metadata"] = merged
+
+
+def _hydrate_trace_replay_payload(payload: dict[str, Any], bundle_path: Path) -> None:
+    if not _schema_version_at_least(payload.get("schema_version"), "0.2.0"):
+        return
+    export_cells = list(payload.get("exports", []))
+    if not export_cells:
+        return
+
+    has_prefix_ref = any(cell.get("prefix_ref") for cell in export_cells)
+    has_embedded_events = any("events" in cell for cell in export_cells)
+    if has_prefix_ref and has_embedded_events:
+        raise ValueError(
+            "mixed legacy/prefix-aware trace replay bundle unsupported in "
+            f"{bundle_path}; rows cannot mix embedded events with prefix_ref"
+        )
+    if not has_prefix_ref:
+        return
+
+    missing_prefix_ref = [c for c in export_cells if not c.get("prefix_ref")]
+    if missing_prefix_ref:
+        raise ValueError(
+            f"prefix-aware trace replay bundle missing prefix_ref in {bundle_path}"
+        )
+
+    raw_prefix_index = payload.get("prefix_index")
+    prefix_index = raw_prefix_index if isinstance(raw_prefix_index, dict) else {}
+    prefix_payloads: dict[str, dict[str, Any]] = {}
+    for prefix_ref in {str(cell["prefix_ref"]) for cell in export_cells}:
+        entry = prefix_index.get(prefix_ref)
+        if not isinstance(entry, dict):
+            raise ValueError(f"unknown prefix_ref {prefix_ref!r} in {bundle_path}")
+        prefix_payloads[prefix_ref] = _load_prefix_artifact(
+            bundle_path, prefix_ref, entry
+        )
+
+    for cell in export_cells:
+        _merge_prefix_into_cell(cell, prefix_payloads[str(cell["prefix_ref"])])
+
+
+# -----------------------------------------------------------------------------
+# ISB1 → kv-cache-tester per-turn mapping
+# -----------------------------------------------------------------------------
+
+def _hash_id_sequence(input_tokens: int, block_size: int) -> list[int]:
+    """Emit the canonical prefix-extending hash_id sequence.
+
+    Each turn's ``hash_ids`` is ``[1, 2, ..., ceil(in/block_size)]``. Since
+    multi-turn conversations are strictly-extending prefixes (turn N+1 input
+    is turn N input + assistant response + new user message), the earlier
+    block IDs appear in every subsequent turn; ``kv-cache-tester``'s
+    hit-rate walker sees them as cache hits.
+    """
+    if input_tokens <= 0:
+        return []
+    n_blocks = max(1, math.ceil(input_tokens / block_size))
+    return list(range(1, n_blocks + 1))
+
+
+def _build_request_from_turn(
+    *,
+    turn_idx: int,
+    messages: list[dict[str, Any]],
+    expected_output_tokens: Optional[int],
+    wait_before_ms: int,
+    prior_offset_ms: int,
+    canonical_model_id: str,
+    image_token_estimate: int,
+    block_size: int,
+    fallback_output_tokens: int,
+) -> tuple[dict[str, Any], int]:
+    input_tokens = _count_turn_input_tokens(messages, image_token_estimate)
+    out_tokens = int(expected_output_tokens) if expected_output_tokens else fallback_output_tokens
+    out_tokens = max(1, out_tokens)
+
+    arrival_ms = prior_offset_ms + max(0, int(wait_before_ms))
+    think_time_s = max(0.0, arrival_ms / 1000.0 if turn_idx == 0 else (arrival_ms - prior_offset_ms) / 1000.0)
+
+    request = {
+        "t": round(arrival_ms / 1000.0, 3),
+        "type": "n",
+        "model": canonical_model_id,
+        "in": input_tokens,
+        "out": out_tokens,
+        "hash_ids": _hash_id_sequence(input_tokens, block_size),
+        "input_types": ["text"],
+        "output_types": ["text"],
+        "stop": "end_turn",
+        "think_time": round(think_time_s, 3),
+    }
+    return request, arrival_ms
+
+
+def _iter_cells_from_multiturn(payload: dict[str, Any]) -> Iterable[dict[str, Any]]:
+    for cell in payload.get("exports") or []:
+        if not isinstance(cell, dict):
+            continue
+        yield cell
+
+
+def _iter_cells_from_trace_replay(payload: dict[str, Any]) -> Iterable[dict[str, Any]]:
+    for cell in payload.get("exports") or []:
+        if not isinstance(cell, dict):
+            continue
+        yield cell
+
+
+def _conversation_id(cell: dict[str, Any], adapter_id: str, fallback_idx: int) -> str:
+    if adapter_id == "inferencex_multiturn":
+        session = cell.get("session") or {}
+        cid = session.get("session_id") or cell.get("trace_id")
+    else:
+        meta = cell.get("trace_metadata") or {}
+        cid = meta.get("session_id") or cell.get("trace_id")
+    if not cid:
+        cid = f"cell_{fallback_idx:04d}"
+    return str(cid)
+
+
+def _cell_turns_multiturn(cell: dict[str, Any]) -> list[dict[str, Any]]:
+    session = cell.get("session") or {}
+    out = []
+    for turn in session.get("turns") or []:
+        if not isinstance(turn, dict):
+            continue
+        out.append({
+            "messages": list(turn.get("messages") or []),
+            "expected_output_tokens": turn.get("expected_output_tokens"),
+            "wait_before_ms": int(turn.get("wait_before_ms") or 0),
+        })
+    return out
+
+
+def _cell_turns_trace_replay(cell: dict[str, Any]) -> list[dict[str, Any]]:
+    out = []
+    prior_ms = 0
+    for event in cell.get("events") or []:
+        if not isinstance(event, dict):
+            continue
+        offset_ms = int(event.get("arrival_time_offset_ms") or 0)
+        wait_ms = 0 if not out else max(0, offset_ms - prior_ms)
+        prior_ms = offset_ms
+        out.append({
+            "messages": list(event.get("input_messages") or []),
+            "expected_output_tokens": event.get("target_output_tokens"),
+            "wait_before_ms": wait_ms,
+        })
+    return out
+
+
+def _build_trace(
+    *,
+    cell: dict[str, Any],
+    adapter_id: str,
+    fallback_idx: int,
+    block_size: int,
+    fallback_output_tokens: int,
+    image_token_estimate: int,
+    max_turns_per_conversation: Optional[int],
+) -> Optional[dict[str, Any]]:
+    conversation_id = _conversation_id(cell, adapter_id, fallback_idx)
+    canonical_model_id = str(cell.get("canonical_model_id") or "unknown")
+
+    if adapter_id == "inferencex_multiturn":
+        turns = _cell_turns_multiturn(cell)
+    else:
+        turns = _cell_turns_trace_replay(cell)
+
+    if not turns:
+        return None
+
+    if max_turns_per_conversation is not None:
+        turns = turns[: max(1, int(max_turns_per_conversation))]
+
+    requests = []
+    cumulative_ms = 0
+    for turn_idx, turn in enumerate(turns):
+        request, cumulative_ms = _build_request_from_turn(
+            turn_idx=turn_idx,
+            messages=turn["messages"],
+            expected_output_tokens=turn.get("expected_output_tokens"),
+            wait_before_ms=turn.get("wait_before_ms", 0),
+            prior_offset_ms=cumulative_ms,
+            canonical_model_id=canonical_model_id,
+            image_token_estimate=image_token_estimate,
+            block_size=block_size,
+            fallback_output_tokens=fallback_output_tokens,
+        )
+        requests.append(request)
+
+    total_in = sum(r["in"] for r in requests)
+    total_out = sum(r["out"] for r in requests)
+
+    return {
+        "id": conversation_id,
+        "models": [canonical_model_id],
+        "block_size": int(block_size),
+        "hash_id_scope": "local",
+        "tool_tokens": 0,
+        "system_tokens": 0,
+        "requests": requests,
+        "totals": {
+            "parent_tokens": {"input": total_in, "output": total_out},
+            "subagent_tokens": {"input": 0, "output": 0},
+            "combined_tokens": {"input": total_in, "output": total_out},
+            "subagent_count": 0,
+        },
+        # ISB1 passthrough tags — kv-cache-tester ignores unknown keys.
+        "isb1": {
+            "trace_id": cell.get("trace_id"),
+            "runtime_stack_id": cell.get("runtime_stack_id"),
+            "hardware_profile_id": cell.get("hardware_profile_id"),
+            "canonical_model_id": canonical_model_id,
+            "support_status": cell.get("support_status"),
+            "benchmark_certification_status": cell.get(
+                "benchmark_certification_status"
+            ),
+            "context_band": cell.get("context_band"),
+            "adapter_id": adapter_id,
+        },
+    }
+
+
+# -----------------------------------------------------------------------------
+# Filter logic (subset of the legacy replay session-loader semantics)
+# -----------------------------------------------------------------------------
+
+def _matches(value: Any, allowed: set[str] | None) -> bool:
+    if allowed is None:
+        return True
+    return str(value or "") in allowed
+
+
+def _csv_set(raw: Optional[str]) -> set[str] | None:
+    if raw is None:
+        return None
+    return {v.strip() for v in raw.split(",") if v.strip()} or None
+
+
+# -----------------------------------------------------------------------------
+# Bundle processing
+# -----------------------------------------------------------------------------
+
+def _load_bundle(export_file: Path) -> dict[str, Any]:
+    try:
+        payload = json.loads(export_file.read_text())
+    except Exception as exc:
+        raise ValueError(f"failed to read ISB1 bundle {export_file}: {exc}") from exc
+    adapter_id = str(payload.get("adapter_id") or "unknown")
+    if adapter_id not in SUPPORTED_ADAPTERS:
+        raise ValueError(
+            f"unsupported ISB1 adapter {adapter_id!r} in {export_file}. "
+            f"Expected one of {SUPPORTED_ADAPTERS}. "
+            "This shim converts ISB1 replay bundles only; "
+            "raw model traces from other pipelines are out of scope."
+        )
+    if adapter_id == "inferencex_trace_replay":
+        _hydrate_trace_replay_payload(payload, export_file)
+    return payload
+
+
+def _convert_bundle(
+    *,
+    export_file: Path,
+    output_dir: Path,
+    runtime_stack_ids: set[str] | None,
+    hardware_profile_ids: set[str] | None,
+    canonical_model_ids: set[str] | None,
+    trace_ids: set[str] | None,
+    support_statuses: set[str] | None,
+    block_size: int,
+    fallback_output_tokens: int,
+    image_token_estimate: int,
+    max_conversations: Optional[int],
+    max_turns_per_conversation: Optional[int],
+    trace_prefix: str,
+) -> tuple[int, int]:
+    """Returns (written_count, skipped_count)."""
+    payload = _load_bundle(export_file)
+    adapter_id = str(payload["adapter_id"])
+
+    iterator = (
+        _iter_cells_from_multiturn(payload)
+        if adapter_id == "inferencex_multiturn"
+        else _iter_cells_from_trace_replay(payload)
+    )
+
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    written = 0
+    skipped = 0
+    emitted_ids: set[str] = set()
+    for idx, cell in enumerate(iterator):
+        if not _matches(cell.get("runtime_stack_id"), runtime_stack_ids):
+            skipped += 1
+            continue
+        if not _matches(cell.get("hardware_profile_id"), hardware_profile_ids):
+            skipped += 1
+            continue
+        if not _matches(cell.get("canonical_model_id"), canonical_model_ids):
+            skipped += 1
+            continue
+        if not _matches(cell.get("trace_id"), trace_ids):
+            skipped += 1
+            continue
+        if not _matches(cell.get("support_status"), support_statuses):
+            skipped += 1
+            continue
+
+        trace = _build_trace(
+            cell=cell,
+            adapter_id=adapter_id,
+            fallback_idx=idx,
+            block_size=block_size,
+            fallback_output_tokens=fallback_output_tokens,
+            image_token_estimate=image_token_estimate,
+            max_turns_per_conversation=max_turns_per_conversation,
+        )
+        if trace is None:
+            skipped += 1
+            continue
+
+        # Make the filename unique per cell, stable across runs.
+        base_id = str(trace["id"])
+        safe_id = "".join(c if c.isalnum() or c in "-_." else "_" for c in base_id)
+        if safe_id in emitted_ids:
+            safe_id = f"{safe_id}_{idx:04d}"
+        emitted_ids.add(safe_id)
+
+        fname = f"{trace_prefix}{safe_id}.json"
+        out_path = output_dir / fname
+        out_path.write_text(json.dumps(trace, indent=2, sort_keys=False))
+        written += 1
+
+        if max_conversations is not None and written >= int(max_conversations):
+            break
+
+    return written, skipped
+
+
+def _iter_export_files(root: Path) -> Iterable[Path]:
+    for path in sorted(root.rglob("*.json")):
+        # Skip manifests/READMEs (anything that isn't an adapter bundle).
+        if path.name in ("manifest.json", "manifest_qwen3.5.json"):
+            continue
+        if "/prefixes/" in path.as_posix():
+            continue
+        try:
+            with path.open() as fh:
+                first_chunk = fh.read(4096)
+        except Exception:
+            continue
+        if '"adapter_id"' not in first_chunk:
+            continue
+        yield path
+
+
+# -----------------------------------------------------------------------------
+# CLI
+# -----------------------------------------------------------------------------
+
+def _parse_args(argv: list[str]) -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="isb1_to_kvcache_tester",
+        description=(
+            "Convert ISB1 replay bundles into kv-cache-tester-compatible "
+            "per-conversation JSON files."
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+    src = parser.add_mutually_exclusive_group(required=True)
+    src.add_argument(
+        "--export-file",
+        type=Path,
+        help="Single ISB1 bundle JSON (e.g. datasets/isb1/exports/core/chat_8k1k.json).",
+    )
+    src.add_argument(
+        "--export-root",
+        type=Path,
+        help=(
+            "Directory tree under which every adapter bundle is converted "
+            "(e.g. datasets/isb1/exports/). Mirrors subpaths under --output-dir."
+        ),
+    )
+
+    parser.add_argument(
+        "--output-dir",
+        type=Path,
+        required=True,
+        help="Destination directory for trace_*.json files.",
+    )
+    parser.add_argument(
+        "--trace-prefix",
+        type=str,
+        default="isb1_",
+        help="Filename prefix for emitted trace files (default: 'isb1_').",
+    )
+    parser.add_argument(
+        "--block-size",
+        type=int,
+        default=DEFAULT_BLOCK_SIZE,
+        help=(
+            f"Hash block size in tokens (default: {DEFAULT_BLOCK_SIZE}, "
+            "matches kv-cache-tester default)."
+        ),
+    )
+    parser.add_argument(
+        "--image-token-estimate",
+        type=int,
+        default=DEFAULT_IMAGE_TOKENS,
+        help=f"Tokens per image block (default: {DEFAULT_IMAGE_TOKENS}).",
+    )
+    parser.add_argument(
+        "--fallback-output-tokens",
+        type=int,
+        default=FALLBACK_OUTPUT_TOKENS,
+        help=(
+            f"Output tokens to emit when a turn has no expected_output_tokens "
+            f"(default: {FALLBACK_OUTPUT_TOKENS})."
+        ),
+    )
+
+    parser.add_argument("--runtime-stack-id",
+                        help="CSV of runtime_stack_ids to include (e.g. standalone:vllm,standalone:sglang).")
+    parser.add_argument("--hardware-profile-id",
+                        help="CSV of hardware_profile_ids to include.")
+    parser.add_argument("--canonical-model-id",
+                        help="CSV of canonical_model_ids to include.")
+    parser.add_argument("--trace-id",
+                        help="CSV of trace_ids to include.")
+    parser.add_argument("--support-status",
+                        help="CSV of support_status values to include (e.g. supported,reviewed_preview).")
+
+    parser.add_argument("--max-conversations", type=int, default=None,
+                        help="Stop after writing N conversations per bundle.")
+    parser.add_argument("--max-turns-per-conversation", type=int, default=None,
+                        help="Truncate each conversation after N turns.")
+
+    parser.add_argument("--quiet", action="store_true", help="Suppress per-bundle progress.")
+
+    return parser.parse_args(argv)
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = _parse_args(argv if argv is not None else sys.argv[1:])
+
+    if args.block_size <= 0:
+        print(f"ERROR: --block-size must be positive (got {args.block_size})", file=sys.stderr)
+        return 2
+
+    runtime_stack_ids = _csv_set(args.runtime_stack_id)
+    hardware_profile_ids = _csv_set(args.hardware_profile_id)
+    canonical_model_ids = _csv_set(args.canonical_model_id)
+    trace_ids = _csv_set(args.trace_id)
+    support_statuses = _csv_set(args.support_status)
+
+    bundles: list[tuple[Path, Path]] = []
+    if args.export_file:
+        bundles.append((args.export_file.resolve(), args.output_dir.resolve()))
+    else:
+        root = args.export_root.resolve()
+        if not root.is_dir():
+            print(f"ERROR: --export-root not a directory: {root}", file=sys.stderr)
+            return 2
+        for f in _iter_export_files(root):
+            rel = f.relative_to(root).parent
+            out = args.output_dir.resolve() / rel / f.stem
+            bundles.append((f, out))
+
+    if not bundles:
+        print("ERROR: no ISB1 bundles found", file=sys.stderr)
+        return 2
+
+    total_written = 0
+    total_skipped = 0
+    errors = 0
+    for export_file, output_dir in bundles:
+        try:
+            written, skipped = _convert_bundle(
+                export_file=export_file,
+                output_dir=output_dir,
+                runtime_stack_ids=runtime_stack_ids,
+                hardware_profile_ids=hardware_profile_ids,
+                canonical_model_ids=canonical_model_ids,
+                trace_ids=trace_ids,
+                support_statuses=support_statuses,
+                block_size=args.block_size,
+                fallback_output_tokens=args.fallback_output_tokens,
+                image_token_estimate=args.image_token_estimate,
+                max_conversations=args.max_conversations,
+                max_turns_per_conversation=args.max_turns_per_conversation,
+                trace_prefix=args.trace_prefix,
+            )
+        except (ValueError, FileNotFoundError) as exc:
+            print(f"ERROR: {export_file}: {exc}", file=sys.stderr)
+            errors += 1
+            continue
+
+        total_written += written
+        total_skipped += skipped
+        if not args.quiet:
+            print(
+                f"ok  {export_file}: wrote {written} trace(s) to {output_dir} "
+                f"(skipped {skipped} cell(s) by filter)"
+            )
+
+    if not args.quiet:
+        print(
+            f"\ndone: {total_written} trace file(s) written across "
+            f"{len(bundles)} bundle(s); {total_skipped} cell(s) skipped; "
+            f"{errors} bundle(s) errored"
+        )
+
+    if total_written == 0:
+        print("ERROR: no traces written — check --runtime-stack-id / --hardware-profile-id filters",
+              file=sys.stderr)
+        return 1
+
+    return 0 if errors == 0 else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tools/publish_hf_dataset.py b/tools/publish_hf_dataset.py
new file mode 100755
index 000000000..32c316d5f
--- /dev/null
+++ b/tools/publish_hf_dataset.py
@@ -0,0 +1,276 @@
+#!/usr/bin/env python3
+"""Publish the ISB-1 kv-cache-tester corpus to a Hugging Face dataset repo.
+
+This script stages `datasets/isb1/converted/` together with the checked-in
+Hugging Face dataset card (`datasets/isb1/hf_dataset_card.md`) and either:
+
+- prints a dry-run plan without making network changes, or
+- creates/uploads a dataset repository via `huggingface_hub`.
+
+Examples:
+    python3 tools/publish_hf_dataset.py \
+        --source datasets/isb1/converted/ \
+        --repo semianalysisai/isb1-cc-traces \
+        --private \
+        --dry-run
+
+    python3 tools/publish_hf_dataset.py \
+        --source datasets/isb1/converted/ \
+        --repo semianalysisai/isb1-cc-traces \
+        --public \
+        --commit-message "Publish ISB-1 kv-cache-tester traces"
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import shutil
+import sys
+import tempfile
+from collections import Counter
+from pathlib import Path
+from typing import Iterable
+
+DEFAULT_SOURCE = Path("datasets/isb1/converted")
+DEFAULT_CARD = Path("datasets/isb1/hf_dataset_card.md")
+DEFAULT_COMMIT_MESSAGE = "Publish ISB-1 kv-cache-tester traces"
+
+
+def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="publish_hf_dataset.py",
+        description=(
+            "Stage and publish the ISB-1 converted kv-cache-tester corpus to a "
+            "Hugging Face dataset repository."
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=(
+            "Example:\n"
+            "  python3 tools/publish_hf_dataset.py --source datasets/isb1/converted/ "
+            "--repo semianalysisai/isb1-cc-traces --private --dry-run"
+        ),
+    )
+    parser.add_argument(
+        "--source",
+        type=Path,
+        default=DEFAULT_SOURCE,
+        help="directory containing converted trace JSON files and manifest.json",
+    )
+    parser.add_argument(
+        "--repo",
+        required=True,
+        help="destination dataset repo in <org>/<name> form",
+    )
+    visibility = parser.add_mutually_exclusive_group()
+    visibility.add_argument(
+        "--private",
+        action="store_true",
+        help="create/publish as a private dataset repo (default)",
+    )
+    visibility.add_argument(
+        "--public",
+        action="store_true",
+        help="create/publish as a public dataset repo",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="print the staged upload plan without calling the Hugging Face Hub",
+    )
+    parser.add_argument(
+        "--commit-message",
+        default=DEFAULT_COMMIT_MESSAGE,
+        help=f"commit message for the upload commit (default: {DEFAULT_COMMIT_MESSAGE!r})",
+    )
+    return parser.parse_args(argv)
+
+
+def fail(message: str, exit_code: int = 2) -> int:
+    print(message, file=sys.stderr)
+    return exit_code
+
+
+def require_existing_dir(path: Path, label: str) -> Path:
+    resolved = path.resolve()
+    if not resolved.exists():
+        raise FileNotFoundError(f"{label} not found: {resolved}")
+    if not resolved.is_dir():
+        raise NotADirectoryError(f"{label} must be a directory: {resolved}")
+    return resolved
+
+
+def require_existing_file(path: Path, label: str) -> Path:
+    resolved = path.resolve()
+    if not resolved.exists():
+        raise FileNotFoundError(f"{label} not found: {resolved}")
+    if not resolved.is_file():
+        raise FileNotFoundError(f"{label} must be a file: {resolved}")
+    return resolved
+
+
+def load_manifest(source_dir: Path) -> dict:
+    manifest_path = source_dir / "manifest.json"
+    require_existing_file(manifest_path, "manifest")
+    try:
+        return json.loads(manifest_path.read_text())
+    except json.JSONDecodeError as exc:
+        raise ValueError(f"invalid manifest JSON: {manifest_path}: {exc}") from exc
+
+
+def infer_dataset_card(source_dir: Path) -> Path:
+    candidate = source_dir.parent / "hf_dataset_card.md"
+    return require_existing_file(candidate, "dataset card")
+
+
+def iter_upload_files(stage_dir: Path) -> list[Path]:
+    return sorted(path for path in stage_dir.rglob("*") if path.is_file())
+
+
+def human_bytes(num_bytes: int) -> str:
+    units = ["B", "KiB", "MiB", "GiB", "TiB"]
+    value = float(num_bytes)
+    for unit in units:
+        if value < 1024 or unit == units[-1]:
+            return f"{value:.2f} {unit}" if unit != "B" else f"{int(value)} B"
+        value /= 1024
+    return f"{num_bytes} B"
+
+
+def summarize_manifest(manifest: dict) -> dict[str, object]:
+    traces = manifest.get("traces", [])
+    by_scale = Counter()
+    for trace in traces:
+        by_scale[str(trace.get("scale_band", "unknown"))] += 1
+    return {
+        "schema_version": manifest.get("schema_version", "unknown"),
+        "generated_at": manifest.get("generated_at", "unknown"),
+        "total_traces": manifest.get("total_traces", len(traces)),
+        "total_requests": manifest.get("total_requests", "unknown"),
+        "by_scale_band": dict(sorted(by_scale.items())),
+    }
+
+
+def print_summary(*, repo: str, private: bool, manifest_summary: dict[str, object], files: Iterable[Path], stage_dir: Path) -> None:
+    files = list(files)
+    total_bytes = sum(path.stat().st_size for path in files)
+    print(f"repo: {repo}")
+    print(f"visibility: {'private' if private else 'public'}")
+    print(f"dataset_uri: https://huggingface.co/datasets/{repo}")
+    print(f"trace_dir_alias: hf_{repo.replace('/', '--')}")
+    print(f"staged_dir: {stage_dir}")
+    print("manifest:")
+    for key, value in manifest_summary.items():
+        print(f"  {key}: {value}")
+    print(f"files_to_upload: {len(files)} files | {human_bytes(total_bytes)}")
+    for file_path in files:
+        rel = file_path.relative_to(stage_dir)
+        print(f"  - {rel} ({human_bytes(file_path.stat().st_size)})")
+
+
+def stage_upload_tree(source_dir: Path, dataset_card_path: Path, work_dir: Path) -> Path:
+    stage_dir = work_dir / "hf_dataset_upload"
+    shutil.copytree(source_dir, stage_dir)
+    shutil.copy2(dataset_card_path, stage_dir / "README.md")
+    return stage_dir
+
+
+def load_hf_api() -> tuple[object, object]:
+    try:
+        from huggingface_hub import HfApi, snapshot_download
+    except ImportError as exc:
+        raise RuntimeError(
+            "huggingface_hub is required for live publish operations. "
+            "Install it with `python3 -m pip install huggingface_hub`."
+        ) from exc
+    return HfApi, snapshot_download
+
+
+def verify_remote_snapshot(snapshot_download: object, repo: str) -> Path:
+    verify_root = Path(tempfile.mkdtemp(prefix="isb1-hf-verify-"))
+    snapshot_path = snapshot_download(
+        repo_id=repo,
+        repo_type="dataset",
+        local_dir=str(verify_root),
+        local_dir_use_symlinks=False,
+    )
+    return Path(snapshot_path)
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = parse_args(argv)
+
+    if "/" not in args.repo or args.repo.count("/") != 1:
+        return fail("--repo must be in <org>/<name> form")
+
+    private = not args.public
+
+    try:
+        source_dir = require_existing_dir(args.source, "source directory")
+        manifest = load_manifest(source_dir)
+        dataset_card_path = infer_dataset_card(source_dir)
+    except (FileNotFoundError, NotADirectoryError, ValueError) as exc:
+        return fail(str(exc))
+
+    with tempfile.TemporaryDirectory(prefix="isb1-hf-stage-") as temp_root:
+        stage_dir = stage_upload_tree(source_dir, dataset_card_path, Path(temp_root))
+        manifest_summary = summarize_manifest(manifest)
+        upload_files = iter_upload_files(stage_dir)
+        print_summary(
+            repo=args.repo,
+            private=private,
+            manifest_summary=manifest_summary,
+            files=upload_files,
+            stage_dir=stage_dir,
+        )
+
+        if args.dry_run:
+            print("dry_run: true")
+            print("remote_actions: skipped")
+            print(
+                "note: dry-run stages README.md + manifest + trace files without calling "
+                "create_repo/upload_folder/snapshot_download"
+            )
+            return 0
+
+        try:
+            HfApi, snapshot_download = load_hf_api()
+            from huggingface_hub.errors import RepositoryNotFoundError
+        except RuntimeError as exc:
+            return fail(str(exc))
+        except ImportError as exc:
+            return fail(f"huggingface_hub import failed: {exc}")
+
+        api = HfApi()
+        repo_exists = True
+        try:
+            api.repo_info(repo_id=args.repo, repo_type="dataset")
+        except RepositoryNotFoundError:
+            repo_exists = False
+
+        if not repo_exists:
+            api.create_repo(
+                repo_id=args.repo,
+                repo_type="dataset",
+                private=private,
+                exist_ok=True,
+            )
+            print(f"created_repo: {args.repo}")
+        else:
+            print(f"created_repo: skipped (already exists: {args.repo})")
+
+        api.upload_folder(
+            repo_id=args.repo,
+            repo_type="dataset",
+            folder_path=str(stage_dir),
+            commit_message=args.commit_message,
+        )
+        print(f"uploaded_repo: {args.repo}")
+        snapshot_path = verify_remote_snapshot(snapshot_download, args.repo)
+        print(f"verified_snapshot: {snapshot_path}")
+        print(f"publish_complete: https://huggingface.co/datasets/{args.repo}")
+        return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tools/test_isb1_to_kvcache_tester.py b/tools/test_isb1_to_kvcache_tester.py
new file mode 100644
index 000000000..35aba515d
--- /dev/null
+++ b/tools/test_isb1_to_kvcache_tester.py
@@ -0,0 +1,412 @@
+# SPDX-License-Identifier: Apache-2.0
+"""Contract tests for ``tools/isb1_to_kvcache_tester.py``.
+
+These tests lock the bytes-level output schema so ISB1→kv-cache-tester
+conversion can't silently drift from what
+``callanjfox/kv-cache-tester``'s ``normalize_trace()`` expects.
+
+We re-implement the minimal ``normalize_trace`` logic inline so tests do not
+pull in ``transformers`` / ``numpy`` / ``openai`` just to exercise the
+conversion shim. The actual upstream function is
+`trace_replay_tester.py::normalize_trace` (see kv-cache-tester repo).
+"""
+
+from __future__ import annotations
+
+import json
+import math
+import subprocess
+import sys
+from pathlib import Path
+
+import pytest
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+SHIM = REPO_ROOT / "tools" / "isb1_to_kvcache_tester.py"
+
+
+# ---------------------------------------------------------------------------
+# Local mirror of kv-cache-tester::normalize_trace (sans tokenizer deps).
+# Keep in sync with upstream manually — these tests flag drift.
+# ---------------------------------------------------------------------------
+
+
+def _normalize_request(req: dict, base_time: float = 0.0) -> dict:
+    return {
+        "timestamp": base_time + req.get("t", 0.0),
+        "type": {"s": "streaming", "n": "non_streaming"}.get(
+            req.get("type", ""), req.get("type", "streaming")
+        ),
+        "input_tokens": req.get("in", 0),
+        "output_tokens": req.get("out", 0),
+        "hash_ids": req.get("hash_ids", []),
+        "stop_reason": req.get("stop", ""),
+        "model": req.get("model", ""),
+    }
+
+
+def _normalize_trace(trace: dict) -> dict:
+    raw = trace.get("requests", [])
+    parent = [r for r in raw if r.get("type") != "subagent"]
+    requests = [_normalize_request(r) for r in parent]
+
+    total_input = sum(r["input_tokens"] for r in requests)
+
+    cache_hits = 0
+    total_blocks = 0
+    for i, req in enumerate(requests):
+        hash_ids = req["hash_ids"]
+        if i > 0 and hash_ids:
+            prev = set(requests[i - 1]["hash_ids"])
+            for h in hash_ids:
+                total_blocks += 1
+                if h in prev:
+                    cache_hits += 1
+                else:
+                    break
+        elif hash_ids:
+            total_blocks += len(hash_ids)
+
+    return {
+        "metadata": {
+            "conversation_id": trace.get("id", "unknown"),
+            "models": trace.get("models", []),
+            "block_size": trace.get("block_size", 64),
+            "hash_id_scope": trace.get("hash_id_scope", "per_context"),
+            "tool_tokens": trace.get("tool_tokens", 0),
+            "system_tokens": trace.get("system_tokens", 0),
+            "request_count": len(requests),
+            "total_input_tokens": total_input,
+            "cache_hit_rate": cache_hits / total_blocks if total_blocks else 0.0,
+        },
+        "requests": requests,
+    }
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+
+def _multiturn_bundle() -> dict:
+    """Minimal ``inferencex_multiturn`` fixture — 1 cell, 2 turns."""
+    return {
+        "adapter_id": "inferencex_multiturn",
+        "schema_version": "0.1.0",
+        "exports": [
+            {
+                "trace_id": "core_chat_8k1k_001",
+                "runtime_stack_id": "standalone:vllm",
+                "hardware_profile_id": "nvidia:h200_sxm_141gb",
+                "canonical_model_id": "qwen3_5_397b_a17b",
+                "support_status": "supported",
+                "benchmark_certification_status": "dataset_replay_verified",
+                "context_band": "core_8k",
+                "session": {
+                    "session_id": "sess_001",
+                    "turns": [
+                        {
+                            "turn_idx": 0,
+                            "messages": [
+                                {"role": "system", "content": "sys" * 16},
+                                {"role": "user", "content": "u" * 3200},
+                            ],
+                            "expected_output_tokens": 128,
+                            "wait_before_ms": 0,
+                        },
+                        {
+                            "turn_idx": 1,
+                            "messages": [
+                                {"role": "system", "content": "sys" * 16},
+                                {"role": "user", "content": "u" * 3200},
+                                {"role": "assistant", "content": "a" * 400},
+                                {"role": "user", "content": "f" * 400},
+                            ],
+                            "expected_output_tokens": 96,
+                            "wait_before_ms": 1500,
+                        },
+                    ],
+                },
+            }
+        ],
+    }
+
+
+def _trace_replay_bundle() -> dict:
+    """Minimal ``inferencex_trace_replay`` fixture (schema 0.1, no prefix_ref)."""
+    return {
+        "adapter_id": "inferencex_trace_replay",
+        "schema_version": "0.1.0",
+        "exports": [
+            {
+                "trace_id": "ext_64k_001",
+                "runtime_stack_id": "standalone:sglang",
+                "hardware_profile_id": "nvidia:h200_sxm_141gb",
+                "canonical_model_id": "qwen3_5_397b_a17b",
+                "support_status": "supported",
+                "benchmark_certification_status": "dataset_replay_verified",
+                "context_band": "extension_64k",
+                "trace_metadata": {"session_id": "sess_tr_001"},
+                "events": [
+                    {
+                        "arrival_time_offset_ms": 0,
+                        "input_messages": [
+                            {"role": "system", "content": "s" * 64},
+                            {"role": "user", "content": "x" * 12000},
+                        ],
+                        "target_output_tokens": 100,
+                    },
+                    {
+                        "arrival_time_offset_ms": 4000,
+                        "input_messages": [
+                            {"role": "system", "content": "s" * 64},
+                            {"role": "user", "content": "x" * 12000},
+                            {"role": "assistant", "content": "r" * 400},
+                            {"role": "user", "content": "follow" * 10},
+                        ],
+                        "target_output_tokens": 150,
+                    },
+                ],
+            }
+        ],
+    }
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+def _run_shim(
+    tmp_path: Path,
+    bundle: dict,
+    *,
+    extra_args: list[str] | None = None,
+) -> Path:
+    bundle_path = tmp_path / "bundle.json"
+    bundle_path.write_text(json.dumps(bundle))
+    out_dir = tmp_path / "out"
+    cmd = [
+        sys.executable,
+        str(SHIM),
+        "--export-file",
+        str(bundle_path),
+        "--output-dir",
+        str(out_dir),
+        "--quiet",
+    ]
+    if extra_args:
+        cmd.extend(extra_args)
+    result = subprocess.run(cmd, capture_output=True, text=True)
+    assert result.returncode == 0, (
+        f"shim failed: stdout={result.stdout!r} stderr={result.stderr!r}"
+    )
+    return out_dir
+
+
+def _load_single_trace(out_dir: Path) -> dict:
+    files = sorted(out_dir.glob("*.json"))
+    assert len(files) == 1, f"expected 1 trace file, got {len(files)}: {files}"
+    return json.loads(files[0].read_text())
+
+
+# ---------------------------------------------------------------------------
+# Contract tests
+# ---------------------------------------------------------------------------
+
+
+class TestMultiturnBundle:
+    def test_top_level_schema(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _multiturn_bundle())
+        trace = _load_single_trace(out)
+
+        # Cam's tester reads these exact fields (see trace_replay_tester.py::normalize_trace).
+        assert trace["id"] == "sess_001"
+        assert trace["models"] == ["qwen3_5_397b_a17b"]
+        assert trace["block_size"] == 64
+        assert trace["hash_id_scope"] == "local"
+        assert trace["tool_tokens"] == 0
+        assert trace["system_tokens"] == 0
+        assert isinstance(trace["requests"], list)
+        assert len(trace["requests"]) == 2
+
+    def test_per_request_schema(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _multiturn_bundle())
+        trace = _load_single_trace(out)
+
+        required_keys = {"t", "type", "model", "in", "out", "hash_ids"}
+        for req in trace["requests"]:
+            missing = required_keys - req.keys()
+            assert not missing, f"missing required request keys: {missing}"
+            assert req["type"] in ("n", "s")
+            assert isinstance(req["in"], int) and req["in"] > 0
+            assert isinstance(req["out"], int) and req["out"] > 0
+            assert isinstance(req["hash_ids"], list) and req["hash_ids"]
+
+    def test_hash_ids_are_prefix_extending(self, tmp_path: Path) -> None:
+        """hash_ids[i+1] must start with hash_ids[i] for cache hit rate > 0."""
+        out = _run_shim(tmp_path, _multiturn_bundle())
+        trace = _load_single_trace(out)
+        reqs = trace["requests"]
+
+        for i in range(1, len(reqs)):
+            prev_hash_ids = reqs[i - 1]["hash_ids"]
+            curr_hash_ids = reqs[i]["hash_ids"]
+            assert len(curr_hash_ids) >= len(prev_hash_ids), (
+                f"turn {i} has fewer hash_ids than turn {i-1}"
+            )
+            assert curr_hash_ids[: len(prev_hash_ids)] == prev_hash_ids, (
+                f"turn {i} hash_ids do not start with turn {i-1} prefix — "
+                "this breaks kv-cache-tester's cache-hit walker"
+            )
+
+    def test_block_size_mapping(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _multiturn_bundle(), extra_args=["--block-size", "32"])
+        trace = _load_single_trace(out)
+        assert trace["block_size"] == 32
+        for req in trace["requests"]:
+            expected_blocks = max(1, math.ceil(req["in"] / 32))
+            assert req["hash_ids"] == list(range(1, expected_blocks + 1))
+
+    def test_arrival_timing_monotonic(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _multiturn_bundle())
+        trace = _load_single_trace(out)
+        times = [r["t"] for r in trace["requests"]]
+        assert times == sorted(times), "request arrival times must be monotonic"
+        # second turn wait_before_ms=1500 → t>=1.5
+        assert trace["requests"][1]["t"] >= 1.5
+
+    def test_isb1_passthrough_tags(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _multiturn_bundle())
+        trace = _load_single_trace(out)
+        assert "isb1" in trace
+        tags = trace["isb1"]
+        assert tags["adapter_id"] == "inferencex_multiturn"
+        assert tags["runtime_stack_id"] == "standalone:vllm"
+        assert tags["hardware_profile_id"] == "nvidia:h200_sxm_141gb"
+        assert tags["canonical_model_id"] == "qwen3_5_397b_a17b"
+        assert tags["support_status"] == "supported"
+        assert tags["benchmark_certification_status"] == "dataset_replay_verified"
+        assert tags["context_band"] == "core_8k"
+
+    def test_normalize_trace_compatibility(self, tmp_path: Path) -> None:
+        """The emitted trace must round-trip through normalize_trace cleanly."""
+        out = _run_shim(tmp_path, _multiturn_bundle())
+        trace = _load_single_trace(out)
+        normalized = _normalize_trace(trace)
+
+        md = normalized["metadata"]
+        assert md["conversation_id"] == "sess_001"
+        assert md["request_count"] == 2
+        assert md["total_input_tokens"] > 0
+        # Two turns, second extends first's prefix → cache hit rate > 0.
+        assert md["cache_hit_rate"] > 0.0
+
+
+class TestTraceReplayBundle:
+    def test_reads_events(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _trace_replay_bundle())
+        trace = _load_single_trace(out)
+        assert trace["id"] == "sess_tr_001"
+        assert len(trace["requests"]) == 2
+
+    def test_arrival_offsets(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _trace_replay_bundle())
+        trace = _load_single_trace(out)
+        # second event arrival_time_offset_ms=4000 → t=4.0
+        assert trace["requests"][0]["t"] == 0.0
+        assert trace["requests"][1]["t"] == 4.0
+
+    def test_prefix_reuse_dominates(self, tmp_path: Path) -> None:
+        out = _run_shim(tmp_path, _trace_replay_bundle())
+        trace = _load_single_trace(out)
+        normalized = _normalize_trace(trace)
+        # 12k-token prefix shared across both events → cache hit rate ≈ 49-50%.
+        assert 0.4 < normalized["metadata"]["cache_hit_rate"] < 0.6
+
+
+class TestFilters:
+    def test_runtime_stack_filter_excludes_non_match(self, tmp_path: Path) -> None:
+        bundle_path = tmp_path / "bundle.json"
+        bundle_path.write_text(json.dumps(_multiturn_bundle()))
+        out_dir = tmp_path / "out"
+
+        # Non-matching runtime filter should exit non-zero with "no traces".
+        result = subprocess.run(
+            [
+                sys.executable,
+                str(SHIM),
+                "--export-file",
+                str(bundle_path),
+                "--output-dir",
+                str(out_dir),
+                "--runtime-stack-id",
+                "standalone:trtllm",
+                "--quiet",
+            ],
+            capture_output=True,
+            text=True,
+        )
+        assert result.returncode != 0
+        assert "no traces written" in result.stderr.lower()
+
+    def test_support_status_filter_allows_match(self, tmp_path: Path) -> None:
+        out = _run_shim(
+            tmp_path,
+            _multiturn_bundle(),
+            extra_args=["--support-status", "supported,reviewed_preview"],
+        )
+        assert sorted(out.glob("*.json"))
+
+    def test_max_turns_truncates(self, tmp_path: Path) -> None:
+        out = _run_shim(
+            tmp_path,
+            _multiturn_bundle(),
+            extra_args=["--max-turns-per-conversation", "1"],
+        )
+        trace = _load_single_trace(out)
+        assert len(trace["requests"]) == 1
+
+
+class TestErrorHandling:
+    def test_rejects_unknown_adapter(self, tmp_path: Path) -> None:
+        bundle = {"adapter_id": "something_else", "exports": []}
+        bundle_path = tmp_path / "bundle.json"
+        bundle_path.write_text(json.dumps(bundle))
+        out_dir = tmp_path / "out"
+        result = subprocess.run(
+            [
+                sys.executable,
+                str(SHIM),
+                "--export-file",
+                str(bundle_path),
+                "--output-dir",
+                str(out_dir),
+                "--quiet",
+            ],
+            capture_output=True,
+            text=True,
+        )
+        assert result.returncode != 0
+        assert "unsupported isb1 adapter" in result.stderr.lower()
+
+    def test_rejects_nonpositive_block_size(self, tmp_path: Path) -> None:
+        bundle_path = tmp_path / "bundle.json"
+        bundle_path.write_text(json.dumps(_multiturn_bundle()))
+        result = subprocess.run(
+            [
+                sys.executable,
+                str(SHIM),
+                "--export-file",
+                str(bundle_path),
+                "--output-dir",
+                str(tmp_path / "out"),
+                "--block-size",
+                "0",
+                "--quiet",
+            ],
+            capture_output=True,
+            text=True,
+        )
+        assert result.returncode == 2
+        assert "--block-size must be positive" in result.stderr
diff --git a/tools/validate_kvcache_tester_trace.py b/tools/validate_kvcache_tester_trace.py
new file mode 100644
index 000000000..850da4991
--- /dev/null
+++ b/tools/validate_kvcache_tester_trace.py
@@ -0,0 +1,369 @@
+#!/usr/bin/env python3
+"""Validate kv-cache-tester trace JSON files.
+
+Stdlib-only validator for the compact trace schema consumed by
+`trace_replay_tester.py` / `normalize_trace()` in Cam's kv-cache-tester.
+Supports validating a single JSON file or recursively walking a directory of
+trace files.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import math
+import sys
+from pathlib import Path
+from typing import Any
+
+VALID_HASH_ID_SCOPES = {"local", "global"}
+MANIFEST_FILENAMES = {"manifest.json"}
+CHECK = "✓"
+CROSS = "✗"
+WARN = "!"
+
+
+def _is_int(value: Any) -> bool:
+    return isinstance(value, int) and not isinstance(value, bool)
+
+
+def _is_number(value: Any) -> bool:
+    return (isinstance(value, int) or isinstance(value, float)) and not isinstance(value, bool)
+
+
+def _add_issue(bucket: list[str], message: str, max_issues: int) -> None:
+    if len(bucket) < max_issues:
+        bucket.append(message)
+
+
+def _validate_string_list(value: Any, field_name: str, errors: list[str], max_issues: int) -> list[str] | None:
+    if not isinstance(value, list) or not value:
+        _add_issue(errors, f"{field_name} must be a non-empty list[str]", max_issues)
+        return None
+    for idx, item in enumerate(value):
+        if not isinstance(item, str):
+            _add_issue(errors, f"{field_name}[{idx}] must be str, got {type(item).__name__}", max_issues)
+    return value if len(errors) < max_issues else None
+
+
+def _validate_flat_hash_ids(
+    hash_ids: list[Any],
+    *,
+    input_tokens: int,
+    block_size: int,
+    scope: str | None,
+    errors: list[str],
+    warnings: list[str],
+    max_issues: int,
+) -> None:
+    expected_len = math.ceil(input_tokens / block_size) if input_tokens > 0 else 0
+    if len(hash_ids) != expected_len:
+        _add_issue(
+            errors,
+            f"hash_ids length = {len(hash_ids)}, expected ceil(in={input_tokens} / block_size={block_size}) = {expected_len}",
+            max_issues,
+        )
+
+    if scope is None:
+        _add_issue(
+            warnings,
+            "hash_id_scope missing; cannot strictly validate flat hash_ids semantics",
+            max_issues,
+        )
+
+    for idx, value in enumerate(hash_ids):
+        if not _is_int(value):
+            _add_issue(errors, f"hash_ids[{idx}] must be int, got {type(value).__name__}", max_issues)
+            continue
+        if value <= 0:
+            _add_issue(errors, f"hash_ids[{idx}] = {value}, expected positive int", max_issues)
+        if scope == "local":
+            expected = idx + 1
+            if value != expected:
+                _add_issue(
+                    errors,
+                    f"hash_ids[{idx}] = {value}, expected {expected} (prefix must extend by 1)",
+                    max_issues,
+                )
+
+
+def _validate_nested_hash_ids(
+    hash_ids: list[Any],
+    *,
+    scope: str | None,
+    errors: list[str],
+    warnings: list[str],
+    max_issues: int,
+) -> None:
+    if scope is None:
+        _add_issue(
+            warnings,
+            "hash_id_scope missing; cannot strictly validate nested hash_ids semantics",
+            max_issues,
+        )
+    for outer_idx, group in enumerate(hash_ids):
+        if not isinstance(group, list):
+            _add_issue(errors, f"hash_ids[{outer_idx}] must be list[int], got {type(group).__name__}", max_issues)
+            continue
+        for inner_idx, value in enumerate(group):
+            if not _is_int(value):
+                _add_issue(
+                    errors,
+                    f"hash_ids[{outer_idx}][{inner_idx}] must be int, got {type(value).__name__}",
+                    max_issues,
+                )
+                continue
+            if value <= 0:
+                _add_issue(errors, f"hash_ids[{outer_idx}][{inner_idx}] = {value}, expected positive int", max_issues)
+            if scope == "local":
+                expected = inner_idx + 1
+                if value != expected:
+                    _add_issue(
+                        errors,
+                        f"hash_ids[{outer_idx}][{inner_idx}] = {value}, expected {expected} (prefix must extend by 1)",
+                        max_issues,
+                    )
+
+
+def _validate_request(
+    req: Any,
+    *,
+    request_idx: int,
+    block_size: int,
+    scope: str | None,
+    errors: list[str],
+    warnings: list[str],
+    max_issues: int,
+) -> None:
+    prefix = f"requests[{request_idx}]"
+    if not isinstance(req, dict):
+        _add_issue(errors, f"{prefix} must be object, got {type(req).__name__}", max_issues)
+        return
+
+    req_type = req.get("type")
+    if not isinstance(req_type, str):
+        _add_issue(errors, f"{prefix}.type must be str", max_issues)
+
+    if req_type == "subagent":
+        return
+
+    t_value = req.get("t")
+    if not _is_number(t_value):
+        _add_issue(errors, f"{prefix}.t must be float >= 0", max_issues)
+    elif float(t_value) < 0:
+        _add_issue(errors, f"{prefix}.t = {t_value}, expected >= 0", max_issues)
+
+    input_tokens = req.get("in")
+    if not _is_int(input_tokens):
+        _add_issue(errors, f"{prefix}.in must be int >= 0", max_issues)
+        input_tokens = 0
+    elif input_tokens < 0:
+        _add_issue(errors, f"{prefix}.in = {input_tokens}, expected >= 0", max_issues)
+
+    output_tokens = req.get("out")
+    if not _is_int(output_tokens):
+        _add_issue(errors, f"{prefix}.out must be int >= 0", max_issues)
+    elif output_tokens < 0:
+        _add_issue(errors, f"{prefix}.out = {output_tokens}, expected >= 0", max_issues)
+
+    hash_ids = req.get("hash_ids")
+    if not isinstance(hash_ids, list):
+        _add_issue(errors, f"{prefix}.hash_ids must be list[int] or list[list[int]]", max_issues)
+    else:
+        is_nested = bool(hash_ids) and all(isinstance(item, list) for item in hash_ids)
+        is_flat = not hash_ids or all(not isinstance(item, list) for item in hash_ids)
+        if is_nested:
+            _validate_nested_hash_ids(
+                hash_ids,
+                scope=scope,
+                errors=errors,
+                warnings=warnings,
+                max_issues=max_issues,
+            )
+        elif is_flat:
+            _validate_flat_hash_ids(
+                hash_ids,
+                input_tokens=input_tokens,
+                block_size=block_size,
+                scope=scope,
+                errors=errors,
+                warnings=warnings,
+                max_issues=max_issues,
+            )
+        else:
+            _add_issue(errors, f"{prefix}.hash_ids must not mix flat and nested entries", max_issues)
+
+    optional_string_fields = ("model", "stop")
+    for field_name in optional_string_fields:
+        if field_name in req and not isinstance(req[field_name], str):
+            _add_issue(errors, f"{prefix}.{field_name} must be str", max_issues)
+
+    optional_list_fields = ("input_types", "output_types")
+    for field_name in optional_list_fields:
+        if field_name in req:
+            value = req[field_name]
+            if not isinstance(value, list):
+                _add_issue(errors, f"{prefix}.{field_name} must be list[str]", max_issues)
+                continue
+            for idx, item in enumerate(value):
+                if not isinstance(item, str):
+                    _add_issue(errors, f"{prefix}.{field_name}[{idx}] must be str", max_issues)
+
+    optional_number_fields = ("api_time", "think_time")
+    for field_name in optional_number_fields:
+        if field_name in req:
+            value = req[field_name]
+            if not _is_number(value):
+                _add_issue(errors, f"{prefix}.{field_name} must be float", max_issues)
+
+
+def validate_trace(trace: Any, *, max_issues: int) -> tuple[list[str], list[str]]:
+    errors: list[str] = []
+    warnings: list[str] = []
+
+    if not isinstance(trace, dict):
+        return [f"top-level JSON must be object, got {type(trace).__name__}"], warnings
+
+    trace_id = trace.get("id")
+    if not isinstance(trace_id, str):
+        _add_issue(errors, "id must be str", max_issues)
+
+    _validate_string_list(trace.get("models"), "models", errors, max_issues)
+
+    block_size = trace.get("block_size")
+    if not _is_int(block_size):
+        _add_issue(errors, "block_size must be int > 0", max_issues)
+        block_size = 1
+    elif block_size <= 0:
+        _add_issue(errors, f"block_size = {block_size}, expected > 0", max_issues)
+
+    requests = trace.get("requests")
+    if not isinstance(requests, list) or not requests:
+        _add_issue(errors, "requests must be a non-empty list", max_issues)
+        requests = []
+
+    scope = trace.get("hash_id_scope")
+    if scope is not None and scope not in VALID_HASH_ID_SCOPES:
+        _add_issue(
+            errors,
+            f"hash_id_scope = {scope!r}, expected one of {sorted(VALID_HASH_ID_SCOPES)}",
+            max_issues,
+        )
+        scope = None
+
+    for field_name in ("tool_tokens", "system_tokens"):
+        if field_name in trace:
+            value = trace[field_name]
+            if not _is_int(value):
+                _add_issue(errors, f"{field_name} must be int >= 0", max_issues)
+            elif value < 0:
+                _add_issue(errors, f"{field_name} = {value}, expected >= 0", max_issues)
+
+    for idx, req in enumerate(requests):
+        if len(errors) >= max_issues and len(warnings) >= max_issues:
+            break
+        _validate_request(
+            req,
+            request_idx=idx,
+            block_size=block_size,
+            scope=scope,
+            errors=errors,
+            warnings=warnings,
+            max_issues=max_issues,
+        )
+
+    return errors, warnings
+
+
+def iter_trace_files(path: Path) -> list[Path]:
+    if path.is_file():
+        return [path]
+    if path.is_dir():
+        files = []
+        for candidate in sorted(path.rglob("*.json")):
+            if candidate.name in MANIFEST_FILENAMES:
+                continue
+            if candidate.is_file():
+                files.append(candidate)
+        return files
+    raise FileNotFoundError(f"Path not found: {path}")
+
+
+def parse_args(argv: list[str]) -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="validate_kvcache_tester_trace.py",
+        description="Validate kv-cache-tester trace files or directories.",
+    )
+    parser.add_argument("path", metavar="PATH", help="file or directory (recursive glob *.json when directory)")
+    parser.add_argument("--quiet", action="store_true", help="only print final summary")
+    parser.add_argument(
+        "--strict",
+        action="store_true",
+        help="treat warnings as errors (e.g. hash_ids scope missing)",
+    )
+    parser.add_argument(
+        "--max-errors-per-file",
+        type=int,
+        default=5,
+        help="maximum errors reported per file (default: 5)",
+    )
+    return parser.parse_args(argv)
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = parse_args(argv or sys.argv[1:])
+    if args.max_errors_per_file <= 0:
+        print("--max-errors-per-file must be > 0", file=sys.stderr)
+        return 2
+
+    path = Path(args.path)
+    try:
+        files = iter_trace_files(path)
+    except FileNotFoundError as exc:
+        print(str(exc), file=sys.stderr)
+        return 2
+
+    if not files:
+        print("No trace JSON files found", file=sys.stderr)
+        return 2
+
+    valid_count = 0
+    failed_count = 0
+
+    for file_path in files:
+        try:
+            trace = json.loads(file_path.read_text())
+        except Exception as exc:
+            errors = [f"invalid JSON: {exc}"]
+            warnings: list[str] = []
+        else:
+            errors, warnings = validate_trace(trace, max_issues=args.max_errors_per_file)
+
+        effective_errors = list(errors)
+        if args.strict:
+            effective_errors.extend(warnings)
+
+        if effective_errors:
+            failed_count += 1
+            if not args.quiet:
+                print(f"{CROSS} {file_path}")
+                for issue in effective_errors[: args.max_errors_per_file]:
+                    print(f"    {issue}")
+        else:
+            valid_count += 1
+            if warnings and not args.quiet:
+                print(f"{WARN} {file_path}")
+                for warning in warnings[: args.max_errors_per_file]:
+                    print(f"    {warning}")
+
+    if failed_count == 0:
+        print(f"{CHECK} {valid_count} files valid | 0 failed")
+        return 0
+
+    plural = "files" if failed_count != 1 else "file"
+    print(f"{failed_count} {plural} failed validation")
+    return 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())