Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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 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.
For each staged patch the user asks to land, in order — any failure ⇒ skip & report, never silently apply:
/meta-apply 1,3
or all); default to applying nothing.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.)provenance.py assert_cross_family — if it
raises (same family / unknown), refuse. (Here it always holds: producer=Claude,
jury=codex. The check is the structural backstop.)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/ → $ARIS_REPO/tools/ via
~/.aris/repo).
For every patch the user asked to land, read its staged .diff and target, then run the
fresh codex jury (Rule 2) — paths-only, no producer reasoning, no prior-round context.
Record {patch, jury_verdict, jury_thread_id, one_line_reason}. Print a one-line result
per patch (PASS → eligible / KILL → refused: <reason>).
The producer may have written an advisory pre-screen into the manifest to help the human read the REPORT — ignore it for the landing decision. Only this fresh verdict counts.
For each patch that PASSED Step 1 and was named by the user:
.aris/meta/backups/<date>/<target> (use the Write tool
to copy contents; corpus paths are not Bash-writable when corpus_write_guard is
active — and the applier should use Write/Edit for corpus mutation anyway).python3 "$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..aris/meta/optimizations.jsonl:
{ts, patch, target, author_model, reviewer_model, jury_thread_id, applied: true}.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.
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):
verdict_id (auditable review) + content_hash (a later hand-edit
invalidates it).assert_cross_family must not raise. A
deterministic:<verifier> reviewer is valid per skill-governance.md.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)..aris/meta/pending/;
invents nothing of its own.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.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
日本語の概要は準備中です。原文の説明を表示しています。
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
日本語の概要は準備中です。原文の説明を表示しています。
Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes an arXiv/AlphaXiv URL, or provides a bare arXiv ID for quick understanding - not for broad literature search.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.
日本語の概要は準備中です。原文の説明を表示しています。
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
日本語の概要は準備中です。原文の説明を表示しています。