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Manuscript Review · brycewang-stanford | DecimalAI

researchby brycewang-stanford

Manuscript Review

brycewang-stanford/review-paper

Source brycewang-stanford/Auto-Empirical-Research-Skills ↗License NOASSERTION

Comprehensive manuscript review covering argument structure, econometric specification, citation completeness, and potential referee objections. Make sure to use this skill whenever the user wants substantive academic feedback on a paper — not just surface edits. Triggers include: "review my paper", "give me feedback on this draft", "what would a referee say", "anticipate referee objections", "act as a referee", "check my identification strategy", "is my argument convincing", "review this manusc

NewMaintained

On-demandOn-demand: invoked explicitly — never occupies your agent's context until called.

Research pack

Last verified 8/8/2026

What it changes

2 of 22 test cases passed with the skill.

Pass-rate lift: —
Tokens: +31%
Agent turns: 0%
Response time: -14%

Model gemini-3.6-flashMeasured 8/8/2026v62 of 22 cases passed with skill · 4 comparable

Tokens, turns and time describe resource use, not a dollar price.

Lift withheld: 4 comparable cases; this report requires 8.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/brycewang-stanford-review-paper/SKILL.md https://app.decimal.ai/s/brycewang-stanford-review-paper/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add brycewang-stanford-review-paper, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/brycewang-stanford-review-paper/ and pins it in .decimal/skills.lock

decimalai skills add brycewang-stanford-review-paper

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/brycewang-stanford-review-paper/SKILL.md https://app.decimal.ai/s/brycewang-stanford-review-paper/SKILL.md

Raw file: /s/brycewang-stanford-review-paper/SKILL.md ↗ · machine-readable summary at /s/brycewang-stanford-review-paper.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

A test case the skill fixed. Same model, same prompt, with and without the skill.

Prompt

I need a full journal review of a 40-page pdf manuscript located at drafts/long_macro_model.pdf. What chunking strategy should be used when reading through this document, and where should the final review be stored?

What was checked, without and with the skill
Checked	Without skill	With skill
Specifies reading long PDFs in 5-page chunks.	Missed	Passed
Saves the report to quality_reports/paper_review_long_macro_model.md.	Missed	Passed

case-08 · gemini-3.6-flash · 8/8/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md147 linessingle file

Manuscript Review

Produce a thorough, constructive review of an academic manuscript — the kind of report a top-journal referee would write.

Input: $ARGUMENTS — path to a paper (.tex, .pdf, or .qmd), or a filename in master_supporting_docs/.

Steps

Locate and read the manuscript. Check:
- Direct path from $ARGUMENTS
- master_supporting_docs/supporting_papers/$ARGUMENTS
- Glob for partial matches
Read the full paper end-to-end. For long PDFs, read in chunks (5 pages at a time).
Evaluate across 6 dimensions (see below).
Generate 3-5 "referee objections" — the tough questions a top referee would ask.
Produce the review report.
Save to quality_reports/paper_review_[sanitized_name].md

Review Dimensions

1. Argument Structure

Is the research question clearly stated?
Does the introduction motivate the question effectively?
Is the logical flow sound (question → method → results → conclusion)?
Are the conclusions supported by the evidence?
Are limitations acknowledged?

2. Identification Strategy

Is the causal claim credible?
What are the key identifying assumptions? Are they stated explicitly?
Are there threats to identification (omitted variables, reverse causality, measurement error)?

Track record

Benchmark

2 / 22

test cases passed with the skill

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/2/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

brycewang-stanford / Auto-Empirical-Research-Skills

skills/15-Felpix-Studios-social-science-research/skills/review-paper/SKILL.md

View on GitHub ↗

License NOASSERTIONImported 8/2/2026Version v6

More skills from the same source and nearby in the registry, with their headline benchmark lift.

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See it in action

What's inside

Manuscript Review

Steps

Review Dimensions

1. Argument Structure

2. Identification Strategy

Track record

Benchmark

Adoption

SkillSafety

Source

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