Best for
- Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
wanshuiyin/Auto-claude-code-research-in-sleep/skills/skills-codex/research-review/SKILL.md
Get a deep critical review of research from GPT using a secondary Codex agent. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
Decision brief
Codex assurance: the fresh base reviewer is same-family. Record reviewindependence: same-family and acceptancestatus: provisional in traces and deliverables. A Claude/Gemini overlay may record cross-family accepted; an unavailable reviewer is BLOCKED, never a fabricated PASS.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Declared | Source record | Install path and trigger |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill "skills/skills-codex/research-review"Inspect the Agent Skill "research-review" from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/blob/a5fcc6970f08d45f6a2100abef4d5d234a1cef25/skills/skills-codex/research-review/SKILL.md at commit a5fcc6970f08d45f6a2100abef4d5d234a1cef25. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Before calling the external reviewer, compile a comprehensive briefing: 1. Read project narrative documents (e.g., STORY.md, README.md, paper drafts) 2. Read any memory/notes files for key findings and experiment history 3. Identify: core claims, methodology, key results, known…
Before calling the external reviewer, compile a comprehensive briefing: 1. Read project narrative documents (e.g., STORY.md, README.md, paper drafts) 2. Read any memory/notes files for key findings and experiment history 3. Identify: core claims, methodology, key results, known…
Send a detailed prompt with ultra reasoning:
Use sendinput with the returned agent id to continue the conversation:
Stop iterating when: - Both sides agree on the core claims and their evidence requirements - A concrete experiment plan is established - The narrative structure is settled
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 86/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 14,225 | Source | Repository attention, not individual Skill quality |
| Compatibility | 1 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Codex assurance: the fresh base reviewer is same-family. Record
review_independence: same-familyandacceptance_status: provisionalin traces and deliverables. A Claude/Gemini overlay may record cross-family accepted; an unavailable reviewer is BLOCKED, never a fabricated PASS.
Get a multi-round critical review of research work from an external LLM with maximum reasoning depth.
gpt-5.6-sol — Model used via a secondary Codex agent, reasoning effort ultra (deep-audit tier). Must be an OpenAI model (e.g., gpt-5.6-sol, gpt-5.5, o3)codex — Default: Codex ultra reviewer (deep-audit tier). Use --reviewer: oracle-pro only when explicitly requested; if Oracle is unavailable, warn and fall back to Codex at this skill's declared tier (ultra). Same-family note: this default reviewer is a second Codex/GPT agent — valid for Type-A completeness/drive review, but not a cross-family Type-B verdict; install a skills-codex-claude-review / skills-codex-gemini-review overlay for a cross-family acquittal (see shared-references/reviewer-routing.md).spawn_agent and send_input when the user has explicitly allowed delegation or subagents.Before calling the external reviewer, compile a comprehensive briefing:
Send a detailed prompt with ultra reasoning:
spawn_agent:
model: gpt-5.6-sol
reasoning_effort: ultra
message: |
[Full research context + specific questions]
Please act as a senior ML reviewer (NeurIPS/ICML level). Start from the
assumption that the work is broken somewhere — your job is to find where.
Be adversarial. Trust nothing the author tells you — verify everything
yourself. Identify:
1. Logical gaps or unjustified claims
2. Missing experiments that would strengthen the story
3. Narrative weaknesses
4. Whether the contribution is sufficient for a top venue
Please be brutally honest.
Use send_input with the returned agent id to continue the conversation:
send_input:
target: [saved reviewer id from Step 2]
message: |
Please continue the review using the revised materials below.
Revised files:
- /absolute/path/to/file1
- /absolute/path/to/file2
Focus on unresolved weaknesses and whether the revision actually fixed them.
For each round:
Key follow-up patterns:
Stop iterating when:
Save the full interaction and conclusions to a review document in the project root:
Update project memory/notes with key review conclusions.
If — composed: <canonical-report-path> is explicitly present, fold consensus,
claims matrix, TODOs, and trace links into that report instead of writing a
standalone review document. Without the directive, write the standalone review
as documented; never infer composed mode from an existing file. — standalone
always wins. See
output-composition.md.
Save a trace for every spawn_agent, send_input, or oracle-pro review call following ../shared-references/review-tracing.md. Record the reviewer route, saved agent id, prompt summary, raw response path, decisions, and action items. This preserves the Claude mainline Review Tracing semantics while using Codex-native reviewer calls.
model: gpt-5.6-sol + reasoning_effort: ultra for reviews (deep-audit tier; capability fallback per reviewer-routing.md, never below xhigh)"I'm going to present a complete ML research project for your critical review. Please act as a senior ML reviewer (NeurIPS/ICML level)..."
"Please design the minimal additional experiment package that gives the highest acceptance lift per GPU week. Our compute: [describe]. Be very specific about configurations."
"Please turn this into a concrete paper outline with section-by-section claims and figure plan."
"Please give me a results-to-claims matrix: what claim is allowed under each possible outcome of experiments X and Y?"
"Please write a mock NeurIPS review with: Summary, Strengths, Weaknesses, Questions for Authors, Score, Confidence, and What Would Move Toward Accept."
Alternatives
wanshuiyin/Auto-claude-code-research-in-sleep
Get a deep critical review of research from an external reviewer backend (Codex or manual). Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.
wanshuiyin/Auto-claude-code-research-in-sleep
Use it for design and operations tasks; the detail page covers purpose, installation, and practical steps.
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