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Retrospection

Skill GhostlyGawd/recursive-harness/skills/retrospection

Portable, evidence-driven agent development harness for Codex, Claude Code, and generic Agent Skills. Active beta v0.1.2.

Install
npx -y skills add GhostlyGawd/recursive-harness --skill retrospection

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

The learning-extraction procedure behind /retro and /meta-retro. Use when a significant task completes, when the Stop gate or 3-corrections nudge fires, when the user expresses frustration or strong approval, or when you finish anything you'd handle differently next time. Converts session experience into reviewed harness diffs — this is the ONLY mechanism by which the system improves, so under-triggering it means not learning.

SKILL.md

3.2 KB, as published. Nobody here has run it

Retrospection

A retro that produces prose produced nothing. The output unit is a DIFF.

Procedure (also encoded in commands/retro.md)

  1. Gather signal, cheapest first:

    • harness corrections list for this session (gold)
    • prediction misses (harness stats, this session's ids)
    • strike-2/3 events from stuck-detection
    • anything the user re-explained twice (you made them pay twice) Then backfill skill VALUE tags for skills that visibly fired this session: harness skill-fired <name> --outcome helped|neutral|hurt — evidence-based only (the skill changed/failed to change the outcome; unsure ⇒ don't tag). Fire counts alone can't catch a high-fire/low-value skill; /meta-retro prunes on hurt>helped, so untagged noise directly corrupts pruning. (provenance: roadmap item 9, session 975732da, 2026-07-05)

  2. Select <= 3. The highest-signal events only. A retro that proposes ten changes is noise wearing a process costume; three reviewed diffs beat ten unreviewed ones every time.

  3. Spawn the retro-miner agent with the transcript path + correction log. Fresh context matters: it reads what happened, not what you remember happening. Take its top events as candidates; you may veto with a reason.

  4. Route each via skill routing-learnings → write the artifact on a branch retro/YYYY-MM-DD-slug in the HARNESS repo (never the project repo, unless the routing verdict was "project fact").

  5. Self-lint: python3 lint/lint_harness.py. Fix violations now.

  6. Audit: spawn harness-auditor on the diff. It checks for the four sins: weakening enforcement, duplicating an existing artifact, missing provenance, unfalsifiable claims. Address verdicts before proposing.

  7. Propose: git push the branch and gh pr create with the provenance template (commands/harness-pr.md). Auto-merge only if autonomy.json says this category has graduated — check, don't assume.

  8. Mark done — TWO records (resolve $HARNESS per /retro step 1):

    • ephemeral Stop-gate flag (silences this session's nudge; deleted at session end): touch "$HARNESS/state/retro_gate_<session_id>" — use the ABSOLUTE trunk path; a relative state/... lands in the active worktree's CWD, not the trunk, so the flag (and any backlog tracking) silently misses (forensic finding, session 9856a41f).
    • durable completion ledger (persists; /retro-backlog reads it to skip done sessions): "$HARNESS/bin/harness" retro-done add <session_id> --slug <slug>.

What good output looks like

"User corrected import-sorting twice (sessions a1b2, c3d4) → PR adds PostToolUse format hook proposal + user-model entry (evidence: 2)." One sentence of why, one diff, one provenance line. That's a learning.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.