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meta-apply

Apply staged improvements to skill files after explicit user selection and a fresh review by a different model family. Each applied change includes a backup, review records, and provenance details for later inspection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Privileged applier that LANDS meta-optimize / corpus-audit patches the user approved — the ONLY skill permitted to mutate the skill corpus from a self-modification proposal, with cross-model jury and human approval at landing. Use when the user says "meta apply", "/meta-apply", "land the staged patches", "应用优化", after a /meta-optimize run.

설치 방법 보기

이럴 때 유용합니다

  • Apply selected patches after reviewing an optimization report
  • Require a fresh model review before changing skill files
  • Keep backups and review records for skill updates

포함된 파일(1)

  • SKILL.md8.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Meta-Apply: the privileged landing gate for self-modification patches

Before each reviewer slot, follow Selectable Reviewers: resolve invocation → .aris/reviewer.json → Claude Code default (Codex MCP) with reviewer_route.py through the canonical helper resolver, preserving this slot's tier, fresh contexts, source/image inputs and deterministic gates. Codex examples/pins below apply only to backend=codex; other routes use their own first-call/reply contract. Save the route and actual returned identity; unavailable selections are REVIEW_UNAVAILABLE. Classify acceptance from actual families/completion/scope. Forward invocation reviewer/model/effort overrides to reviewer-bearing children. Generation workers are unchanged.

This skill exists to enforce a privilege boundary. Producers like /meta-optimize (and, later, corpus-audit) are read-only — no Write/Edit, no apply step; they can only stage candidate patches under .aris/meta/pending/. This skill is the only place a staged patch becomes a real change to the corpus. Splitting "propose" from "land" across two skills with different tool grants is what makes "a loop cannot apply its own patch" structural rather than a sentence the producer is asked to obey.

It is human-invoked only. It runs when the user explicitly types /meta-apply after reading the producer's REPORT. That invocation IS the landing authorization (the locked 2026-05-30 decision: the human stays at the landing gate).

The acquittal is generated HERE, not relayed

The earlier design trusted a jury_verdict: pass field in the producer's manifest. That is forgeable — the producer writes that field, so a buggy/misaligned producer could stage a killed patch labelled "pass." So this skill does not trust any producer-written verdict. It runs the cross-model jury itself, at landing time, on the actual staged diff (fresh thread, paths-only). The verdict is produced where it is consumed, by the privileged human-invoked skill — nothing to forge.

The non-negotiable rules (jury-at-landing, reject-default)

For each staged patch the user asks to land, in order — any failure ⇒ skip & report, never silently apply:

  1. The human named THIS patch. Apply only patches the user listed (/meta-apply 1,3 or all); default to applying nothing.
  2. Fresh cross-model jury PASS, obtained now. Run mcp__codex__codex (fresh thread, NOT codex-reply; model: gpt-6-astra, config: {"model_reasoning_effort": "ultra"}, sandbox: read-only, paths-only per reviewer-independence.md) on the staged .diff + its target. Ask: does this change improve the harness without regressions; PASS or KILL + one-line reason. Include the scope-limits block from review-scope-limits.md in that prompt: this jury judges ARIS's own mechanism, so an over-defensive KILL permanently blocks a good patch. Note the block bans proposing new hash binding — it is not a reason to KILL a patch that touches the existing provenance stamp. KILL ⇒ refuse. The human cannot override a KILL — they may only pick among jury-PASSED survivors. (A loop can DRIVE; only the cross-model jury can ACQUIT.)
  3. Author ≠ reviewer family. The author is the producer's executor model; the reviewer is the actual returned model that just judged it. Run provenance.py assert_cross_family — if it raises (same family / unknown), refuse. Use actual author/reviewer identities, never infer the family from the host or transport. This strict landing gate remains mandatory.

Workflow

Step 0: Load staging + resolve the helper

PENDING=".aris/meta/pending"
[ -d "$PENDING" ] || { echo "Nothing staged. Run /meta-optimize first."; exit 0; }
echo "Staged:"; cat "$PENDING/manifest.jsonl"

Resolve provenance.py via the 4-layer chain in integration-contract.md §2 (.aris/tools/ → tools/ → $ARIS_REPO/tools/ → $ARIS_REPO/tools/ via ~/.aris/repo).

Step 1: Jury-at-landing for each requested patch

For every patch the user asked to land, read its staged .diff and target, then run the fresh codex jury (Rule 2) — paths-only, no producer reasoning, no prior-round context. Record {patch, jury_verdict, jury_thread_id, one_line_reason}. Print a one-line result per patch (PASS → eligible / KILL → refused: <reason>).

The producer may have written an advisory pre-screen into the manifest to help the human read the REPORT — ignore it for the landing decision. Only this fresh verdict counts.

Step 2: Land the survivors (Write/Edit only — never Bash)

For each patch that PASSED Step 1 and was named by the user:

  1. Back up the target to .aris/meta/backups/<date>/<target> (use the Write tool to copy contents; corpus paths are not Bash-writable when corpus_write_guard is active — and the applier should use Write/Edit for corpus mutation anyway).
  2. Apply the diff by Edit/Write on the target corpus file.
  3. Stamp provenance on the changed file:
    python3 "$PROVENANCE" stamp "$TARGET" --author "$AUTHOR" \
      --reviewer "$JURY_MODEL" --verdict-id "$JURY_THREAD_ID"
    
    stamp() re-asserts cross-family and refuses on same-family — the structural backstop at the moment the authorization record is written. The stamp is a process receipt (who authored, who acquitted-at-landing, content hash) — NOT a claim the change is correct.
  4. Log to .aris/meta/optimizations.jsonl: {ts, patch, target, author_model, reviewer_model, jury_thread_id, applied: true}.

Step 3: Report

Per patch: LANDED <target> (+ backup path + provenance sidecar) or REFUSED <patch>: <reason>. Remove landed patches from .aris/meta/pending/. Remind the user a landed patch is revertable from its backup, and to test the changed skill next run.

Provenance is a receipt, not an acquittal of correctness

A stamp records that a change passed a process (cross-model jury at landing + human landing), not that it is correct. To prevent "approved-but-wrong with a stamp that vouches for it" (false-authority laundering — worse than no stamp, because a later auto-curator reads it as evidence):

  • The stamp carries verdict_id (auditable review) + content_hash (a later hand-edit invalidates it).
  • Recommended (not yet built): a TTL forcing re-review of long-lived auto-authored artifacts, and a behavioral auditor that REVOKES a stamp when a landed skill misbehaves. Track as follow-up; never treat a stamp as permanent truth.

Key Rules

  • Human-invoked only. Never run as a side-effect of another skill or a hook.
  • Jury-at-landing, reject-default, no override. The binding verdict is produced HERE on the staged diff; never trust a producer-written verdict; the human picks among survivors, never resurrects a KILL.
  • Cross-family or refuse. assert_cross_family must not raise. A deterministic:<verifier> reviewer is valid per skill-governance.md.
  • Corpus mutation goes through Write/Edit (reviewable, attributable), not Bash. The corpus_write_guard hook (if installed) additionally denies Bash corpus writes — it does NOT gate Write/Edit, so it does not by itself stop this skill from editing the corpus; the jury-at-landing + stamp discipline above is what governs Write/Edit mutations (that discipline is procedure, not a hook-enforced mechanism).
  • Back up before every mutation. Reversible by construction.
  • Only land staged patches. Applies what producers staged in .aris/meta/pending/; invents nothing of its own.

Review Tracing

Save each landing-jury codex call's trace per review-tracing.md to .aris/traces/meta-apply/<date>_run<NN>/ — the acquittal that landed a corpus change must be forensically recoverable.

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