self-review

Solid

Review the user's own manuscript, paper, thesis chapter, rebuttal, or release packet with clean-room anti-contamination controls. Use when asked for self-review, internal review, pre-submission review, readiness check, reviewer simulation on own work, or claim-evidence self-audit where prior chat memory, unstated assumptions, model background knowledge, or unlisted local notes must not be treated as evidence.

AI & Automation 28 stars 3 forks Updated 4 days ago MIT

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Quality Score: 84/100

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100
Frontmatter 20%
70
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100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# /self-review - Clean-Room Manuscript Self-Review ## Purpose Audit the user's own work without letting memory, prior chats, unstated project knowledge, or the model's background knowledge become evidence. The governing rule is: ```text self-review truth = explicit review packet + source anchor ``` Use `/argument-governance` first when the manuscript needs a formal intent, contribution, claim, and evidence map. ## Codex-Only Baseline Complete self-review with Codex, the review manifest, allowed sources, and the bundled packet checker. Do not require Gemini, gemini-agent, a second model, or a subagent. If an external review is available, keep it in `Reviewer-risk inference` or advisory notes and never use it as source support. If `/argument-governance` is unavailable, manually extract the same clean-room argument spine from manifest-listed sources only. ## Enhanced Advisory Mode If the manifest and the user explicitly allow an API-key-backed advisory review, Codex may run or incorporate a second-model pass after the clean-room self-review packet is valid. Rules: - the base clean-room review must be possible without the external call - API keys must be read from environment variables only - the manifest may name `api_key_env_var`, but must never store the key value - only manifest-approved source subsets may be sent externally - external findings must be placed under `Reviewer-risk inference` or advisory notes - external findings must be re-grounded against allowed ...

Details

Author
yha9806
Repository
yha9806/academic-writing-toolkit
Created
4 months ago
Last Updated
4 days ago
Language
Python
License
MIT

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