learning-loop

Learning loop: consolidate, absorb, refine

The engine's session-side pipeline (spec: docs/superpowers/specs/2026-08-01-learning-engine-design.md §5–§10). Capture happens automatically (plugin hooks); this skill turns what was captured into observations, and observations into reviewable skill-edit PRs. The human gate is git merge.

When to use this skill

• Promoting queue flags and completing dated learnings entries ("consolidate", a Stop-hook nudge, end of a work block).
• Drafting skill edits from ready observations ("absorb", "update my skills", "run the loop"): output is always a PR branch, never a direct edit.
• Catalog hygiene passes ("refine the skills"): prune/dedup/staleness through the same delta pipeline, report-first.
• Contested or structural edits ("experiment", "A/B this edit", "try competing fixes"): description rewrites, restructures, competing fixes where the right answer isn't obvious enough for a single draft.
• Scheduled example verification ("deep verify", "verify the examples"): promoting pinned examples/references content from status: unverified once its evals.yaml fixture passes.
• Loop health ("learning loop status"): queue depth, unabsorbed backlog, eval-suite size, ledger totals.
• For distilling external repos, use the mining skill; for authoring a new skill from scratch, skill-author.

Key directives

• Delegation posture: embed; the workflows live here; the deterministic tools live at scripts/engine/ (apply_deltas.py, run_trigger_evals.py, ledger.py, mine_transcripts.py, skill_metrics.py, observations.py, placement.py, run_variants.py, deep_verify.py, run_task_checks.py) and in the plugin hooks (recall).
• Scripts hold the pen. LLM roles draft deltas and diagnose; apply_deltas.py applies them (snapshot, bump, changelog, sidecars). Never hand-edit a skill during absorb; never bypass the script's refusals; a refusal is a design signal, not an obstacle.
• Consolidation never touches skills/ content. Its write surface is learnings/, learnings/observations/, and the evidence/evals sidecars; that boundary is what makes it autonomous-safe.
• Absorb consumes status: ready only. The ready bar (proof ≥ 2 | user-correction | three-part evidence | external official) is enforced by the observations lint; do not absorb around it.
• Merge is the gate. Every absorb/refine run ends in a PR with the evidence table; no agent merges to main skills/**. Mid-build sessions capture; they never edit skills directly.
• Dedup against everything seen , including absorbed and rejected observations, or judged-rejected findings reappear forever.
• One self-check round on consolidator and absorber output: re-read the draft against the source transcript window for misattribution, missed dead-ends, wrong anchors, before writing.
• Variants are deltas, never rewrites. Full-file candidate rewrites are forbidden (context collapse); a variant that apply_deltas refuses is a broken candidate, not a contender.