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 experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. A secondary Codex agent evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.
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。
Codex assurance: deterministic evidence existence can be accepted, while the base semantic claim judgment records
review_independence: same-familyandacceptance_status: provisional. Cross-family overlays may record accepted; reviewer failure emits BLOCKED.
Experiments produce numbers; this gate decides what those numbers mean. Collect results from available sources, get a secondary Codex judgment, then auto-route based on the verdict.
Gather experiment data from whatever sources are available in the project:
wandb.Api().run("<entity>/<project>/<run_id>").history() — metrics, training curves, comparisonsssh server "tail -100 /path/to/training.log" if no other sourceidea-stage/docs/research_contract.md (legacy fallback: docs/research_contract.md): intended claims and experiment designAssemble the key information:
Before the reviewer call, resolve and run evidence_check.py per
evidence-precheck.md:
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills-codex.txt ]; then
ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills-codex.txt 2>/dev/null) || true
fi
EVIDENCE_CHECK=""
[ -n "${ARIS_REPO:-}" ] && [ -f "$ARIS_REPO/tools/evidence_check.py" ] && EVIDENCE_CHECK="$ARIS_REPO/tools/evidence_check.py"
[ -z "$EVIDENCE_CHECK" ] && [ -f tools/evidence_check.py ] && EVIDENCE_CHECK="tools/evidence_check.py"
mkdir -p .aris
if [ -n "$EVIDENCE_CHECK" ]; then
python3 "$EVIDENCE_CHECK" . --batch .aris/claims.json \
> .aris/evidence_precheck.json 2>.aris/evidence_precheck.err || true
else
echo "WARN: evidence_check.py unresolved; semantic review will still run" >&2
fi
Treat path_missing and value_not_found as unsupported evidence before the
semantic review. verified means only that the cited value exists; it does not
prove the claim. Pass the pre-check JSON path to the fresh reviewer. The Codex
reviewer's positive result remains review_independence: same-family and
acceptance_status: provisional; a deterministic evidence check never upgrades
a semantic claim to accepted by itself.
Send the collected results to a secondary Codex agent for objective evaluation:
spawn_agent:
model: gpt-6-astra
reasoning_effort: ultra
message: |
RESULT-TO-CLAIM EVALUATION
I need you to judge whether experimental results support the intended claim.
Intended claim: [the claim these experiments test]
Experiments run:
[list experiments with method, dataset, metrics]
Results:
[paste key numbers, comparison deltas, significance]
Baselines:
[baseline numbers and sources — reproduced or from paper]
Known caveats:
[any confounding factors, limited datasets, missing comparisons]
Please evaluate:
1. claim_supported: yes | partial | no
2. what_results_support: what the data actually shows
3. what_results_dont_support: where the data falls short of the claim
4. missing_evidence: specific evidence gaps
5. suggested_claim_revision: if the claim should be strengthened, weakened, or reframed
6. next_experiments_needed: specific experiments to fill gaps (if any)
7. confidence: high | medium | low
Be honest. Do not inflate claims beyond what the data supports.
A single positive result on one dataset does not support a general claim.
Extract structured fields from the secondary Codex response:
- claim_supported: yes | partial | no
- what_results_support: "..."
- what_results_dont_support: "..."
- missing_evidence: "..."
- suggested_claim_revision: "..."
- next_experiments_needed: "..."
- confidence: high | medium | low
Skip this step if EXPERIMENT_AUDIT.json does not exist.
if EXPERIMENT_AUDIT.json exists:
read integrity_status from file
attach to verdict output:
integrity_status: pass | warn | fail
if integrity_status == "fail":
append to verdict: "[INTEGRITY CONCERN] — audit found issues, see EXPERIMENT_AUDIT.md"
downgrade confidence to "low" regardless of Codex judgment
if integrity_status == "warn":
append to verdict: "[INTEGRITY: WARN] — audit flagged potential issues"
else:
integrity_status = "unavailable"
verdict is labeled "provisional — no integrity audit run"
(this does NOT block anything — pipeline continues normally)
See shared-references/experiment-integrity.md for the full integrity protocol.
no — Claim not supportedAGENTS.md or project notespartial — Claim partially supportedpartial on the same claim → record analysis in findings.md, consider whether to narrow the claim scope or switch ideasyes — Claim supported/ablation-plannerSkip this step entirely if research-wiki/ does not exist.
if research-wiki/ exists:
# Resolve the helper (Codex chain). If unavailable, skip wiki writes; still report verdict.
ARIS_REPO="${ARIS_REPO:-$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills-codex.txt 2>/dev/null)}"
WIKI_SCRIPT=""
[ -n "$ARIS_REPO" ] && [ -f "$ARIS_REPO/tools/research_wiki.py" ] && WIKI_SCRIPT="$ARIS_REPO/tools/research_wiki.py"
[ -z "$WIKI_SCRIPT" ] && [ -f tools/research_wiki.py ] && WIKI_SCRIPT="tools/research_wiki.py"
[ -z "$WIKI_SCRIPT" ] && [ -f ~/.codex/skills/research-wiki/research_wiki.py ] && WIKI_SCRIPT="$HOME/.codex/skills/research-wiki/research_wiki.py"
[ -n "$WIKI_SCRIPT" ] || echo "WARN: research_wiki.py unreachable; skipping wiki writes (verdict still reported)." >&2
# 1. Create/refresh the experiment node FIRST (verdict OWNER → --update-on-exist so a
# re-judge overwrites the stale verdict). The supports/invalidates edges in #2 point
# FROM exp:<id> and add_edge does NOT verify node existence, so only add them if the
# experiment node was born (EXP_NODE_OK); otherwise skip the wiki edges.
EXP_NODE_OK=0
[ -n "$WIKI_SCRIPT" ] && python3 "$WIKI_SCRIPT" add_experiment research-wiki/ \
--slug "<exp_id>" --idea "idea:<active_idea>" \
--verdict "<yes|partial|no>" --confidence "<high|medium|low>" \
--date "<date>" --hardware "<hw>" --duration "<dur>" \
--metrics "<key metrics>" --reasoning "<one-line why this verdict>" \
--provenance "<EXPERIMENT_AUDIT.md / run dir>" --update-on-exist && EXP_NODE_OK=1
# 2. Record empirical support as EDGES ONLY, and ONLY if EXP_NODE_OK. NEVER edit a
# claim page's `status`: that is the PROOF axis (verified / refuted / unproven /
# sound-modulo-imports / drafted / retracted), owned by /proof-checker (the claim
# birth point) — the ARIS helper REJECTS "supported"/"partial"/"invalidated".
if [ "$EXP_NODE_OK" = 1 ]:
for each claim resolved by this verdict:
if verdict == "yes":
python3 "$WIKI_SCRIPT" add_edge research-wiki/ --from "exp:<id>" --to "claim:<cid>" --type supports --evidence "<metric>"
elif verdict == "partial":
python3 "$WIKI_SCRIPT" add_edge research-wiki/ --from "exp:<id>" --to "claim:<cid>" --type supports --evidence "partial: <metric>"
else:
python3 "$WIKI_SCRIPT" add_edge research-wiki/ --from "exp:<id>" --to "claim:<cid>" --type invalidates --evidence "<why>"
# 3. Update idea outcome (raw markdown, helper-free — preserves the rich idea body)
Update research-wiki/ideas/<idea_id>.md:
- outcome: positive | mixed | negative
- If negative: fill "Failure / Risk Notes" and "Lessons Learned"
- If positive: fill "Actual Outcome" and "Reusable Components"
# 4. Rebuild + log (reflect the new edges; only if WIKI_SCRIPT resolved)
[ -n "$WIKI_SCRIPT" ] && python3 "$WIKI_SCRIPT" rebuild_query_pack research-wiki/
[ -n "$WIKI_SCRIPT" ] && python3 "$WIKI_SCRIPT" log research-wiki/ "result-to-claim: exp:<id> verdict=<verdict> for idea:<idea_id>"
# 5. Re-ideation suggestion
Count failed/partial ideas since last /idea-creator run.
If >= 3: print "💡 3+ ideas tested since last ideation. Consider re-running /idea-creator — the wiki now knows what doesn't work."
confidence is low, treat the judgment as inconclusive and add experiments rather than committing to a claim.reviewer-routing.md (gpt-6-astra + ultra → gpt-6-astra + xhigh
→ gpt-5.5 + xhigh), and never downgrade on timeout, rate-limit, auth,
transport, server, or context errors. If no allowed pair succeeds, write a
traced BLOCKED review record with the unavailable route and evidence paths, write
CLAIMS_FROM_RESULTS.md containing only verdict: REVIEW_UNAVAILABLE, record
the same in findings.md, and stop. Do not emit a local PASS/WARN substitute or
advance a submission-facing claim; only an explicitly non-submission
evidence-gathering phase may continue.After the secondary Codex judgment, save a trace following ../shared-references/review-tracing.md. Write files directly to .aris/traces/result-to-claim/<date>_run<NN>/ and include the prompt, raw reviewer response, parsed verdict, routing action, and whether the result is [pending external review]. Respect the --- trace: parameter when present (default: full).
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 Gemini review through gemini-review MCP → 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。