peer-review

Files (24)

• SKILL.md
• citation_references_template.csv · assets/
• claim_evidence_matrix_template.csv · assets/
• reporting_checklist_template.csv · assets/
• reporting_guidelines.json · assets/
• review_intake_template.json · assets/
• review_scaffold_template.md · assets/
• source_ledger.csv · assets/
• statistical_reproducibility_template.json · assets/
• study_profile_template.json · assets/
• common_issues.md · references/
• ethical_review_practice.md · references/
• reporting_standards.md · references/
• security_validation.md · references/
• statistical_reproducibility.md · references/
• tool_reference.md · references/
• _common.py · scripts/
• audit_citations.py · scripts/
• audit_statistics_reproducibility.py · scripts/
• generate_review_scaffold.py · scripts/
• lint_review.py · scripts/
• select_reporting_guidelines.py · scripts/
• validate_claim_evidence.py · scripts/
• validate_review_intake.py · scripts/

SKILL.md (first lines)

# Peer Review

Support an accountable human reviewer with a rigorous, fair, actionable assessment. Treat every unpublished submission and review as confidential.

## Mandatory safety boundary

Before reading or analyzing unpublished content:

1. Confirm the user is authorized by the publisher, editor, author, or other material owner.
2. Check the target venue’s review, confidentiality, co-review, retention, and AI/tool policies.
3. Record conflicts, competence limits, requested scope, and specialist-review needs.
4. Default to local-only processing.

If authorization is unclear, do not inspect or quote the manuscript. Clarify only the unresolved authorization; existing documented authorization need not be requested again. Until resolved, use only the intake validator or synthetic/public fixtures. Local processing of the manuscript also requires authorization.

Running a bundled CLI locally does not make the surrounding assistant session local. Treat any manuscript content read into a hosted assistant as external processing when evaluating venue policy and authorization.

Never:

- Send unpublished manuscript, supplement, review, or editorial text to an external service without specific publisher/author authorization and venue permission
- Upload confidential content to a public model, search engine, citation service, grammar tool, plagiarism checker, or image service
- Reuse content for training, benchmarking, product improvement, or unrelated research
- Read broad environment state, `.env` files, API keys, or credentials
- Call a network, LLM, or image API from bundled tools
- Invoke another skill or a PDF/image pipeline automatically
- Impersonate an assigned reviewer, editor, journal, funder, or author
- Fabricate manuscript details, review findings, citations, analyses, experiments, reproduction, or an editorial outcome
- Announce a decision that belongs to an editor or panel

Delete local copies and derivatives when policy requires; otherwise retain only what the controlling policy authorizes. Record deletion or retention without copying confidential content into the record.

Read `references/ethical_review_practice.md` before handling confidential material.

## Human accountability

Label generated text as a working draft. The accountable human must:

- Read the complete authorized submission and relevant supplements
- Verify every factual statement, calculation, citation, and manuscript location
- Resolve conflicts and disclose assistance as required
- Rewrite comments in their own expert judgment
- Submit through the authorized channel

Automated coverage, consistency, or lint results are not peer review and do not establish manuscript merit.

## Intake gate

Copy and complete `assets/review_intake_template.json`, then run:

```bash
python3 scripts/validate_review_intake.py completed-intake.json
```

Proceed only when status is `READY_FOR_LOCAL_REVIEW`.

The validator blocks:

- Undocumented authorization
- Missing human accountability
- Unassessed or unresolved conflicts
- Unknown review model or unchecked venue policy
- Unauthorized AI assistance
- External service use
- Data reuse
- Missing deletion/retention planning

It validates declarations, not their truth.

A conflict marked `disclosed_to_editor` remains blocked. Use `editor_cleared` only after actual editor clearance, or `none_identified` when no conflict exists. Do not clear a conflict merely to pass the validator.

## Review workflow

### 1. Establish scope and available evidence

Record:

- Submission type and stage
- Review question and requested focus
- Target venue and review model
- Materials actually available: manuscript, supplements, protocol, registration, analysis plan, data/code statement, prior decision, or response letter
- Competence areas and limits
- Missing material that prevents assessment

Do not infer absent content. Use “not reported” or “not available for review.”

### 2. Orient without deciding

Create a short neutral map:

- Research question
- Population or system
- Design and unit
- Intervention, exposure, test, or model
- Comparator/reference
- Outcomes and timing
- Principal claims

Do not write an acceptance/rejection recommendation. Identify what evidence would be needed to evaluate each claim.

### 3. Select reporting guidance

Copy `assets/study_profile_template.json` and run:

```bash
python3 scripts/select_reporting_guidelines.py local-profile.json
```

For checklist coverage:

```bash
python3 scripts/select_reporting_guidelines.py \
  local-profile.json \
  --coverage local-coverage.csv
```

Use the current base guideline, explanation/elaboration, applicable extensions, and target venue policy. See `references/reporting_standards.md`.

**Critical distinction:** reporting completeness is not design quality, risk of bias, validity, or merit. Never convert missing items into an automatic score or publication judgment.

From K-Dense-AI/scientific-agent-skills, MIT.

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