Improve fix-issue and fix-issue-batch skills

.claude/skills/fix-issue-batch/SKILL.md

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+---
+name: fix-issue-batch
+description: Batch-fix [Model] or [Rule] issues from the GitHub Project board Backlog column — calls /fix-issue on each one sequentially
+---
+
+# Fix Issue Batch
+
+Iterate through `[Model]` or `[Rule]` issues **from the Backlog column of the GitHub Project board** and call `/fix-issue` on each one sequentially.
+
+## Invocation
+
+```
+/fix-issue-batch <model|rule>
+```
+
+## Constants
+
+GitHub Project board IDs (same as fix-issue / project-pipeline):
+
+| Constant | Value |
+|----------|-------|
+| `PROJECT_NUMBER` | `8` |
+| `PROJECT_OWNER` | `CodingThrust` |
+| `PROJECT_ID` | `PVT_kwDOBrtarc4BRNVy` |
+| `STATUS_FIELD_ID` | `PVTSSF_lADOBrtarc4BRNVyzg_GmQc` |
+| `STATUS_READY` | `61e4505c` |
+
+## Process
+
+```dot
+digraph fix_batch {
+    rankdir=TB;
+    "Parse argument" [shape=box];
+    "Fetch project board Backlog" [shape=box];
+    "Filter & sort" [shape=box];
+    "Print queue" [shape=box];
+    "Pick next issue" [shape=diamond];
+    "Call /fix-issue N" [shape=box];
+    "Done" [shape=doublecircle];
+
+    "Parse argument" -> "Fetch project board Backlog";
+    "Fetch project board Backlog" -> "Filter & sort";
+    "Filter & sort" -> "Print queue";
+    "Print queue" -> "Pick next issue";
+    "Pick next issue" -> "Call /fix-issue N" [label="remaining"];
+    "Pick next issue" -> "Done" [label="none left"];
+    "Call /fix-issue N" -> "Pick next issue";
+}
+```
+
+---
+
+## Step 1: Parse Argument
+
+Accept one argument: `model` or `rule` (case-insensitive).
+
+- `model` → filter for issues with `[Model]` in the title
+- `rule` → filter for issues with `[Rule]` in the title
+
+If no argument or invalid argument → stop with: "Usage: `/fix-issue-batch <model|rule>`"
+
+---
+
+## Step 2: Fetch Issues from Project Board Backlog
+
+Fetch all items from the GitHub Project board and filter to the **Backlog** column:
+
+```bash
+gh project item-list 8 --owner CodingThrust --format json --limit 500
+```
+
+From the JSON result:
+1. Filter items where `status == "Backlog"`
+2. Keep only items whose `content.title` starts with `[Model]` or `[Rule]` (matching the argument)
+3. For each item, extract: issue number (`content.number`), title (`content.title`), and project item ID (`id`)
+
+Then fetch labels for each matching issue (needed for categorization):
+
+```bash
+gh issue view <NUMBER> --repo CodingThrust/problem-reductions --json labels
+```
+
+Or batch-fetch with a single search query to avoid N+1:
+
+```bash
+gh issue list --repo CodingThrust/problem-reductions \
+  --state open --search "[Model] in:title" \
+  --json number,title,labels --limit 200
+```
+
+Cross-reference the board items with the label data to build the final list.
+
+---
+
+## Step 3: Filter and Sort
+
+From the Backlog issues:
+
+1. **Categorize by current label status:**
+   - `already-good` — has `Good` label
+   - `has-failures` — has at least one failure label (`PoorWritten`, `Wrong`, `Trivial`, `Useless`)
+   - `needs-check` — no check-issue comment yet (no `Good`/`PoorWritten`/`Wrong`/`Trivial`/`Useless` label)
+2. **Sort by priority then issue number:** `already-good` first, then `has-failures`, then `needs-check`. Within each group, sort by issue number ascending (oldest first). This prioritizes issues that already have a check report and are closest to being ready.
+
+---
+
+## Step 4: Print Queue
+
+Show the user what will be processed:
+
+```
+## Fix queue: [Model] issues (N total)
+
+| # | Issue | Title | Status |
+|---|-------|-------|--------|
+| 1 | #235 | [Model] SteinerTree | already-good |
+| 2 | #233 | [Model] StrongConnectivityAugmentation | has-failures (PoorWritten) |
+| 3 | #234 | [Model] FeedbackVertexSet | needs-check |
+| ... | ... | ... | ... |
+
+Priority: already-good → has-failures → needs-check.
+Processing N issues total.
+```
+
+Then ask the user to confirm before starting:
+
+> Ready to start? I'll process each issue with `/fix-issue`, one at a time.
+>
+> 1. **Start** — begin processing from the first issue
+> 2. **Start from #N** — skip to a specific issue number
+> 3. **Cancel**
+
+---
+
+## Step 5: Process Each Issue
+
+**CRITICAL:** Each issue MUST be dispatched as a **subagent** for analysis, giving it a fresh context window to prevent cutting corners. The subagent does NOT interact with the human — it returns a structured report, then the main agent presents it for human decisions.
+
+For each issue in the queue (priority order: `already-good` → `has-failures` → `needs-check`):
+
+### 5a: Check prerequisite
+
+If no comment starting with `## Issue Quality Check` exists, run `/check-issue <NUMBER>` first.
+
+### 5b: Dispatch analysis subagent
+
+```
+Agent tool:
+  subagent_type: "general-purpose"
+  description: "Analyze issue #<NUMBER>"
+  prompt: |
+    Analyze GitHub issue #<NUMBER> for fix-issue.
+    1. Fetch the issue: gh issue view <NUMBER> --json title,body,labels,comments
+    2. Find the most recent "## Issue Quality Check" comment
+    3. Parse all Fail and Warn results (warnings are NOT ignorable)
+    4. For each issue, classify as mechanical or substantive
+    5. For mechanical issues: apply the fix to a draft body
+    6. For substantive issues: prepare 2-3 concrete options with your recommendation
+
+    Return EXACTLY this format:
+
+    ## Analysis for #<NUMBER>: <title>
+
+    ### Auto-fixes applied
+    | # | Section | Issue | Fix |
+    |---|---------|-------|-----|
+    | 1 | ... | ... | ... |
+
+    ### Questions for human
+    **Q1: <topic>**
+    <description of the problem>
+    - (a) <option 1> ← recommended
+    - (b) <option 2>
+    - (c) <option 3>
+
+    **Q2: ...**
+
+    ### Draft body
+    <full updated issue body with mechanical fixes applied, substantive issues marked as `[PENDING Q1]`>
+```
+
+### 5c: Present to human
+
+Print the subagent's report and ask the human to answer all questions at once:
+
+```
+## Issue #<NUMBER> (<current>/<total>): <title>
+
+<auto-fixes table from subagent>
+
+<questions from subagent>
+
+Please answer the questions above (e.g. "Q1: a, Q2: b"), or type "skip" to skip this issue.
+```
+
+### 5d: Apply answers and finalize
+
+After human responds:
+- If **"skip"**: move to next issue
+- Otherwise: apply the human's choices to the draft body, re-check (run 4 quality checks inline), then finalize on GitHub (edit body, post changelog comment, update labels, move to Ready — see fix-issue Steps 6–8)
+
+### 5e: Continue
+
+Print progress and ask whether to continue:
+
+```
+Done #<NUMBER>. (<current>/<total> complete, <remaining> remaining)
+Next: #<NEXT_NUMBER> <next_title>
+```
+
+> 1. **Continue** — process the next issue
+> 2. **Skip next** — skip the next issue and continue to the one after
+> 3. **Stop** — end the batch here and print summary
+
+---
+
+## Step 6: Summary
+
+After all issues are processed, print a summary:
+
+```
+## Batch fix complete
+
+| Result | Count | Issues |
+|--------|-------|--------|
+| Fixed & moved to Ready | 7 | #233, #234, #235, #236, #237, #238, #240 |
+| Skipped (by user) | 1 | #239 |
+| Total | 8 | |
+```
+
+---
+
+## Common Mistakes
+
+| Mistake | Fix |
+|---------|-----|
+| Fetching all open issues instead of board | Only process issues from the **Backlog** column of GitHub Project #8 |
+| Skipping already-good issues | Process ALL Backlog issues; `already-good` are processed first (highest priority) |
+| Not running check-issue first | If no check report exists, run `/check-issue` before `/fix-issue` |
+| Processing in random order | Always sort by issue number ascending within priority groups |
+| Continuing after user cancels | Respect cancel/skip requests immediately |
+| Missing project scopes | Run `gh auth refresh -s read:project,project` if board access fails |