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Command

/cs-skill-retro

Grade the agent setup from real local session history — rubric-scored, evidence-gated, rendered as one local shareable report.

From plugin
claude-skills
30k169 skills127 agents169 commands2 MCP
$ npx -y skills add alirezarezvani/claude-skills --agent claude-code

Command definition

cs-skill-retro.md
disable-model-invocation: true
description: Grade the agent setup from real local session history — rubric-scored, evidence-gated, rendered as one local shareable report.
argument-hint: "[optional: --repo PATH | --days N | --harness claude|codex | a question about the setup]"

/cs-skill-retro

Run the skill-retro pass with `$ARGUMENTS` (pass any `--repo`, `--days`, `--harness`, `--include-subagents` flags through to the collector).

Load `engineering/skill-retro/skills/skill-retro/SKILL.md` and follow it exactly. Summary of the contract:

Pre-flight

1. **Confirm the target repo** — the report is scoped to one repo's skills and the sessions that ran inside it. Run from that repo or pass `--repo`. 2. **State the privacy contract up front**: everything runs locally, transcripts are redacted before they touch disk, nothing is uploaded. 3. Create the scratch dir: `RUN="$(mktemp -d "${TMPDIR:-/tmp}/skill-retro-XXXXXXXX")"`.

Pipeline

python ${CLAUDE_PLUGIN_ROOT}/skills/skill-retro/scripts/collect_sessions.py --out "$RUN" $ARGUMENTS
python ${CLAUDE_PLUGIN_ROOT}/skills/skill-retro/scripts/score_aggregator.py --inventory "$RUN/inventory.json" --emit-template > "$RUN/session_scores.json"
# ... judge each transcript against scorers/, fill the template, draft suggestions ...
python ${CLAUDE_PLUGIN_ROOT}/skills/skill-retro/scripts/score_aggregator.py --inventory "$RUN/inventory.json" --scores "$RUN/session_scores.json" --suggestions "$RUN/suggestions.json"
python ${CLAUDE_PLUGIN_ROOT}/skills/skill-retro/scripts/render_report.py --report "$RUN/report.json"

If `sessions_sampled` is 0, stop and tell the user (suggest `--days 90`). If the aggregator exits 4, fix what it names and re-run — never bypass it. Report every non-zero exit code as a finding, not an error to swallow.

Output

Tell the user, in text: the letter grade, the three top findings, how many secrets were redacted, and the suggestion count (zero is a valid success — say why per finding). Then link the local report:

  • Your quality report: `file://$RUN/report.html` (print to PDF to share)

Finally ask: **"Want me to apply any of these proposed diffs to your real skills?"** — and apply only on an explicit per-skill yes.

Read more
@alirezarezvani
Ships withclaude-skills

411 production-ready skills for Claude Code and 12 other coding agents, covering engineering, product, marketing, compliance, finance and the C-suite. We test whether each skill loads when you ask in plain words, and publish the results.

30k200 skills127 agents2 MCP
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