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+---
+description: Guidelines for creating agentic workflows that generate charts and trend visualizations using Python scientific computing libraries with persistent historical data.
+---
+
+# Data Science & Chart Generation
+
+Use when creating a workflow that generates charts, trend visualizations, dashboards, or any Python-based metric output.
+
+## Frontmatter Template
+
+```yaml
+---
+network:
+  allowed:
+    - defaults
+    - python
+safe-outputs:
+  upload-asset:
+  create-issue:          # or create-discussion
+    title-prefix: "📊 [Report Name]:"
+    labels: [report]
+    close-older-issues: true
+    expires: 30
+steps:
+  - name: setup
+    run: |
+      mkdir -p /tmp/gh-aw/python/{data,charts}
+      mkdir -p /tmp/gh-aw/cache-memory/trending
+      pip install --user --quiet numpy pandas matplotlib seaborn scipy
+---
+```
+
+## Agent Prompt Structure
+
+Write the agent prompt as five ordered steps:
+
+1. **Load history** — read `/tmp/gh-aw/cache-memory/trending/<metric>/history.jsonl` into a DataFrame if it exists; otherwise start empty.
+2. **Collect data** — fetch metrics from the GitHub API (or generate with NumPy). Save to `/tmp/gh-aw/python/data/<metric>.csv` — **never inline data in Python code**.
+3. **Append & prune** — append a JSON Lines record `{"timestamp": "<iso8601>", "metric": "...", "value": ...}` to `history.jsonl`; drop records older than 90 days.
+4. **Chart** — if ≥ 2 history points exist, generate a time-series line chart with 7-day moving average; otherwise use a bar/distribution chart. Save to `/tmp/gh-aw/python/charts/` at DPI 300.
+5. **Report** — upload each chart with `upload asset`, then create an issue/discussion embedding the URLs. Call `noop` if there is nothing to report.
+
+## Python Patterns
+
+### History: load → append → prune
+
+```python
+import json, os, pandas as pd
+from datetime import datetime, timedelta
+
+HISTORY = '/tmp/gh-aw/cache-memory/trending/issues/history.jsonl'
+
+# Load
+df = pd.read_json(HISTORY, lines=True) if os.path.exists(HISTORY) else pd.DataFrame()
+if not df.empty:
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+    df = df.sort_values('timestamp')
+
+# Append
+with open(HISTORY, 'a') as f:
+    f.write(json.dumps({"timestamp": datetime.now().isoformat(), "metric": "issue_count", "value": 42}) + '\n')
+
+# Prune to 90 days
+if not df.empty:
+    df = df[df['timestamp'] >= pd.Timestamp.now() - timedelta(days=90)]
+    df.to_json(HISTORY, orient='records', lines=True)
+```
+
+### Chart: trend with moving average
+
+```python
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+sns.set_style("whitegrid"); sns.set_palette("husl")
+fig, ax = plt.subplots(figsize=(12, 7), dpi=300)
+
+df['rolling'] = df['value'].rolling(window=7, min_periods=1).mean()
+ax.plot(df['timestamp'], df['value'], label='Actual', alpha=0.5, marker='o')
+ax.plot(df['timestamp'], df['rolling'], label='7-day avg', linewidth=2.5)
+ax.fill_between(df['timestamp'], df['value'], df['rolling'], alpha=0.2)
+ax.set_title('Metric Trend', fontsize=16, fontweight='bold')
+ax.set_xlabel('Date', fontsize=12); ax.set_ylabel('Value', fontsize=12)
+ax.legend(); ax.grid(True, alpha=0.3); plt.xticks(rotation=45); plt.tight_layout()
+plt.savefig('/tmp/gh-aw/python/charts/trend.png', dpi=300, bbox_inches='tight', facecolor='white')
+```
+
+**Chart standards**: 300 DPI · 12×7 in · labeled axes and title · legend for multi-series · `husl` palette
+
+### Multiple metrics
+
+```python
+for metric in metrics:
+    sub = df[df['metric'] == metric]
+    ax.plot(sub['timestamp'], sub['value'], marker='o', label=metric, linewidth=2)
+```
+
+## Report Template
+
+```markdown
+# 📊 [Title] — [Date]
+
+## Summary
+[2–3 sentences on trends and key findings]
+
+### [Metric] Trend
+![chart](https://github.com/OWNER/REPO/blob/assets/WORKFLOW/chart.png?raw=true)
+[direction, moving average, notable events]
+
+## Data Details
+- **Source**: … | **Points**: … | **Range**: … | **Period**: …N days
+- **Cache**: `/tmp/gh-aw/cache-memory/trending/`
+```
+
+Use `###` and deeper for all headers inside the report body.
+
+## Use Cases
+
+| Intent | Trigger | Notes |
+|---|---|---|
+| Weekly GitHub activity chart | `schedule` weekly | track issues, PRs, commits |
+| Test coverage trends | `push`/`pull_request` | append per-run |
+| Workflow run durations | `schedule` daily | GitHub Actions API |
+| Stale repo aging distribution | `workflow_dispatch` | no cache needed |
+| Contributor growth | `schedule` monthly | 365-day retention |