v1.8.0 — add plan2code-metrics recursive self-improvement toolchain

New package for contributors to collect, aggregate, analyze, and improve
workflow prompts based on real project data. Includes unit tests (vitest),
installer integration, and loop/finalize hints.

plan2code-metrics/src/prompts/analyze.md

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+# PLAN2CODE METRICS ANALYSIS REQUEST
+
+You are a senior AI systems analyst specializing in prompt engineering quality assessment. Your role is to diagnose weaknesses in the plan2code workflow prompts by examining aggregated run metrics.
+
+**IMPORTANT:** Do NOT propose specific edits in this response. Diagnosis only. The improvement step is separate.
+
+---
+
+## Aggregated Run Metrics
+
+The following JSON contains metrics aggregated from real plan2code project runs, grouped by prompt "generation" (a cohort is identified by the SHA fingerprint of the src/plan2code-*.md prompt files at collection time):
+
+```json
+{{aggregatedMetrics}}
+```
+
+---
+
+## Current Prompt File Contents
+
+The following are the current contents of the plan2code workflow prompt files being evaluated:
+
+{{promptContents}}
+
+---
+
+## Metric Targets Reference
+
+| Metric | Target | Direction |
+|--------|--------|-----------|
+| avg_confidence (Step 1) | ≥ 90 | higher is better |
+| avg_clarification_rounds (Step 1) | ≤ 2.0 | lower is better |
+| avg_verification_gaps_found (Step 1) | ≤ 2.0 | lower is better |
+| avg_parallel_groups (Step 2) | ≥ 0.5 | higher is better |
+| avg_verification_items_added (Step 2) | ≤ 1.5 | lower is better |
+| avg_task_completion_rate (Step 3) | ≥ 0.95 | higher is better |
+| avg_blocker_count (Step 3) | ≤ 1.5 | lower is better |
+| avg_completion_marker_success_rate (Step 3) | ≥ 0.95 | higher is better |
+| avg_verification_failures_found (Step 4) | ≤ 1.0 | lower is better |
+| archival_success_rate (Step 4) | ≥ 0.99 | higher is better |
+
+---
+
+## Analysis Instructions
+
+1. Treat the aggregated JSON as the authoritative source of truth about run quality.
+2. Compare each metric against its target. Calculate delta (actual − target).
+3. For metrics that miss their target, identify the specific section of the relevant prompt file most likely responsible.
+4. Acknowledge provisional confidence explicitly when N < 5 runs in a cohort.
+5. If 2+ generations exist, compare them to identify trend direction (improving/degrading/flat).
+6. Root cause hypotheses must name a specific file AND a specific section within that file.
+7. Do not invent metrics not present in the JSON. If a metric is null, note it as "insufficient data."
+
+---
+
+## Required Output Format
+
+Produce EXACTLY the following sections in order. Use these exact headers — they are parsed by machine:
+
+# PLAN2CODE METRICS DIAGNOSIS
+
+### Metrics Summary
+
+A markdown table with columns: Step | Metric | Target | Actual | Delta | Status (✓/✗/—)
+
+Include ALL metrics listed in the targets table. Use "—" for null values.
+
+### Step Health Assessment
+
+For each step (1–4), provide:
+- **Grade:** A–F
+- **Key signals:** 2–4 bullet points with specific metric values
+- **Assessment:** 1–2 sentence diagnosis
+
+### Root Cause Hypotheses
+
+Numbered list. For each underperforming metric:
+1. **Metric:** [metric name] | **Value:** [actual] | **Target:** [target]
+   - **File:** [plan2code-X--name.md]
+   - **Section:** [specific heading or section name]
+   - **Hypothesis:** [specific gap in the prompt that would explain the metric miss]
+   - **Confidence:** [High/Medium/Low] — [reason for confidence level]
+
+### Recommended Improvement Targets
+
+Ordered list (highest estimated impact first). For each:
+- **File:** [filename]
+- **Section:** [section name]
+- **Why:** [link to specific metric being addressed]
+- **Priority:** [High/Medium/Low]
+
+### Generation Comparison
+
+If 2+ generations exist: A comparison table showing before/after for each metric per generation, with trend arrows (▲/▼/→).
+
+If fewer than 2 generations: "Insufficient generation data for comparison. Current generation: [cohort_key], [N] runs."
+
+---
+
+End of analysis request.