SuperAPI AI Directory

reflect-feedback

Agents & models

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Updated 10-15 20:12

About this skill

Reflect Feedback

Reflection without feedback just accumulates. This skill closes the loop: it checks whether the improvements reflect made are earning their keep, and removes the ones that are not. Prefer a smaller ledger of verified improvements over a large ledger of hopeful ones.

Inputs

  • .reflect/applied.md in the current project (or ~/.reflect/ when run outside one). If it does not exist, stop and suggest running reflect.
  • Optionally, recent session transcripts or the current conversation as evidence of what fired.

Workflow

  1. Read the ledger. List every row with status applied or verified. Rows already pruned are skipped; rows proposed are surfaced at the end as a reminder queue.
  1. Check existence. For each entry, confirm the target still exists and still contains the change (the rule line is present in AGENTS.md, the skill/command/script file exists). Missing → mark pruned with reason "target removed externally".

  2. Look for firing evidence. For each surviving entry, gather what evidence is available:

    • Rules: did recent sessions follow the rule without being corrected? Was the friction it targeted absent?
    • Skills/commands: any sign of invocation (mentions in recent transcripts, session state, or the user's account)?
    • Scripts: executed recently, referenced by rules, or imported anywhere?
    • Delegation/context rules: did the pattern they encode show up (smaller outputs, sub-agent use)?

    Be honest about evidence quality. Label each judgment as observed (concrete evidence), inferred (indirect), or unknown (no evidence either way). Never invent usage.

  3. Grade.

    • verified — observed or strongly inferred to fire and help.
    • keep as applied — unknown, but young (< ~30 days or < ~10 sessions).
    • pruned — unused past its window, superseded, or actively causing friction (e.g., a rule the user now contradicts). Remove the change from its target file when pruning a rule reflect itself added; for skills/commands/scripts, propose deletion rather than deleting.
  4. Update and report. Rewrite the affected Status cells in applied.md, add a dated feedback note at the top of the file, and report:

## Reflect Feedback

**Verified** (n) — working, keep
**Still watching** (n) — no evidence yet, within window
**Pruned** (n) — removed or proposed for removal, with reasons
**Proposal queue** (n) — proposed rows still awaiting a decision

Evidence quality: n observed / n inferred / n unknown

Boundaries

  • Edit only .reflect/ state and content reflect itself added (per the ledger). Anything else is propose-only.
  • Pruning removes a change and keeps its ledger row with the reason — the history of what did not work is itself a learning.
  • If evidence is thin across the board, say so and recommend the cheapest instrumentation that would fix it (e.g., a rule that scripts log a line to .reflect/ when run), rather than guessing.