sneg55/agent-starter/reflect
Claude Code and agent skill by sneg55/agent-starter
- community
Checking that the SKILL.md file is still in the repository.
Per-project self-improvement - reads the .harness ledger and feedback memories, then proposes gated rule/threshold/ADR changes so the project stops repeating mistakes. Run periodically.
Install
npx vskill@latest install sneg55/agent-starter/reflectSKILL.md
Reflect: Per-Project Self-Improvement
You are performing a reflection - turning the signal this project has captured into durable improvements. Nothing is applied without the developer's approval.
Phase 1 - Orient (gather signal)
- Run the stats script over the ledger:
~/.claude/hooks/harness-ledger-stats.sh --ledger .harness/ledger.jsonl --min-recurr 3 If that path doesn't exist, the hooks aren't installed at ~/.claude/hooks/ - run the copy from wherever this project keeps them. If the script prints all zeros there is no ledger yet (no signal captured) - stop; there is nothing to reflect on.
- Read the current project rules in
CLAUDE.mdso you improve them rather than duplicate. - Read recent
feedback-type memory files - these are the developer's explicit
corrections and are the highest-value signal. Locate the memory directory first (it sits next to MEMORY.md; find . -name MEMORY.md if unsure), then grep -l 'type: feedback' <memory-dir>/*.md.
- Read the most recent
.harness/reflections/*.mdreport (if any) to recall the last
metric snapshot and what was already changed.
Phase 2 - Cluster
From the stats output and feedback memories, identify recurring problems:
- Each
recurring <rule> <prefix> <count>line is a friction cluster - the same check
keeps firing in the same area.
- Group related feedback corrections by theme.
- Ignore one-off events; focus on what repeats.
Phase 3 - Propose (one candidate per cluster)
For each cluster, draft exactly one proposed change, choosing the fitting type:
| Type | When | Where it lands | |
|---|---|---|---|
| Project rule | a convention would stop the repeat | append to CLAUDE.md project-specific section | |
| Threshold change | a guardrail is too strict/loose | a diff to .claude/settings.json or the hook - shown, never auto-applied | |
| Lint rule | the mistake is mechanically catchable | a diff to eslint.config.mjs / biome.jsonc | |
| ADR / knowledge | durable "why" worth keeping | a new memory file or docs/adr/ note |
Present all proposals together as a numbered list with the concrete change for each.
Phase 4 - Gate & Record
- Ask the developer to approve, edit, or reject each proposal (like
/remember). - Apply only the approved ones, then commit them (use
/commit). - Create
.harness/reflections/if needed (mkdir -p .harness/reflections), then write a
reflection report to .harness/reflections/YYYY-MM-DD.md containing:
- the full stats output (the metric snapshot, so the next reflection can compare),
- the clusters you found,
- which proposals were approved / rejected and why.
The report is committed; the raw .harness/ledger.jsonl stays gitignored. Signal is private; wisdom is shared.
Measuring success
The headline metric is recurring_events from the stats output. Compare it to the value in the previous reflection report. If a rule you promoted last time worked, the cluster it targeted should have shrunk. Note the trend explicitly in the new report.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/reflect/SKILL.md
Popularity
- Repository stars
- 75
- Repository forks
- 4
- 7-day trend score
- 22
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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