jankneumann/improve-harness
skills/improve-harness/SKILL.md
Analyze capability-gap failure patterns from episodic memory and generate improvement reports with OpenSpec proposal stubs
$ install --global
skillsauthnpx skillsauth add jankneumann/agentic-coding-tools improve-harnessInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Jun 6, 2026, 7:12 AM121.8s6 files scanned
SKILL.md
- name:
- improve-harness
- description:
- Analyze capability-gap failure patterns from episodic memory and generate improvement reports with OpenSpec proposal stubs
- category:
- Git Workflow
- tags:
- [harness, self-improvement, capability-gaps, episodic-memory, analysis]
Improve Harness
Analyze capability-gap failure patterns recorded in episodic memory and generate structured improvement reports. Supports creating OpenSpec proposal stubs from high-priority findings.
Arguments
$ARGUMENTS - Optional flags:
--time-window <days>(default: 30)--create-proposal(create an OpenSpec proposal stub from the top finding)--output <path>(write report to file; default: stdout)
How It Works
- Queries the coordinator episodic memory for entries with
capability_gap:*tags - Groups findings by capability_gap value
- Ranks by (frequency x severity_weight) where severity weights: critical=4, high=3, medium=2, low=1
- Generates a markdown report with summary stats, ranked findings table, and recommendations
- Optionally creates an OpenSpec proposal stub from the top finding
Data Sources
The skill consumes capability-gap signals from four emitters via the shared D4 tag schema:
| Source | Tag | How it gets there |
|--------|-----|-------------------|
| Agent self-report | source:self-reported | Agent calls remember MCP tool during failure |
| Coordinator audit-triage | source:coordinator-emitted | LLM classifier over audit batches |
| Session-log | source:session-log | Agent fills ### Capability Gaps Observed at phase boundary |
| Transcript mining | source:transcript-mined | /collect-transcripts deep-analysis pass |
The skill also scans openspec/changes/**/session-log.md for ### Capability Gaps Observed sections to catch gaps not yet mirrored to memory.
Deduplication is keyed on (capability_gap, affected_skill, session_id). When the same gap appears from multiple sources, all sources are preserved — cross-source agreement is the strongest signal.
Prerequisites
- Python 3.11+
- Coordinator running at
COORDINATOR_URL(default: http://localhost:8000) - Falls back gracefully with a warning if the coordinator is unreachable
Steps
1. Analyze Failure Patterns
python3 <agent-skills-dir>/improve-harness/scripts/analyze_failures.py \
--time-window ${TIME_WINDOW:-30} \
--json
2. Generate Report
python3 <agent-skills-dir>/improve-harness/scripts/generate_report.py \
--time-window ${TIME_WINDOW:-30} \
${CREATE_PROPOSAL:+--create-proposal} \
${OUTPUT:+--output "$OUTPUT"}
3. Review and Act
- Review the ranked findings table
- For high-priority gaps, use
--create-proposalto generate an OpenSpec proposal stub - Refine the proposal with human guidance and submit via
/plan-feature
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