paper-audit-claims
Evaluates the scientific rigor of claims, arguments, and causal chains in project docs.
Install
mkdir -p .claude/skills/paper-audit-claims && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13268" && unzip -o skill.zip -d .claude/skills/paper-audit-claims && rm skill.zipInstalls to .claude/skills/paper-audit-claims
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Audit claims, causal chains, and conclusions in the manuscript or project design docs for scientific rigor. Use when the user asks to check claims, verify arguments, test causal chains, check for overclaiming, or before finalizing any section that makes empirical or causal assertions.Key capabilities
- →Audit claims for scientific rigor
- →Verify arguments in manuscripts
- →Test causal chains in design documents
- →Check for overclaiming
- →Evaluate support for assertions
- →Flag writing-quality signals
How it works
The skill audits claims, causal chains, and conclusions in documents for scientific rigor, identifying overclaiming and evaluating whether arguments are supported by available evidence and mechanisms.
Inputs & outputs
When to use paper-audit-claims
- →Auditing scientific claims
- →Verifying causal chains
- →Checking for overclaiming
About this skill
paper-audit-claims: claim audit for the decentralized-curation manuscript
When to use
Trigger when the user asks to audit claims, check for overclaims, verify causal chains, test assertions, or evaluate whether an argument is supported by the evidence and mechanisms actually available. Also trigger as a pre-merge check on any prose change that adds or strengthens a causal claim.
Delegate methodology to
claude-scientific-writer:scientific-critical-thinking for the claim-extraction and evidence-sufficiency workflow.
Project-specific targets
- Causal claims about incentive alignment and mechanism-as-proof reasoning in
paper.qmd. - Uniqueness / sufficiency claims in
projects/*/design.mdandprojects/*/blueprint.md. - Red-team robustness claims: cross-check against
context/attack-and-defense-log.md, which tracks integrated attacks and defenses.
Project Design Principles to uphold
- NoNeedForGovernance > Good Governance > Bad Governance > No Governance. Flag designs that justify added governance without ruling out the simpler "no governance needed" case.
- Do not decompose quality further than your mechanisms can distinguish. Two mechanisms (challenge-based accuracy, coherence-based relevance) mean two dimensions. A third dimension without a third mechanism is noise. (Corollary of Wang and Strong's "decompose quality before you mechanize it.")
Writing-quality signals to flag
- "Proves" when "suggests" is warranted.
- Universal claims from limited examples.
- Unfalsifiable assertions.
- Mechanism-as-proof claims: describing design as if design proves correct behavior.
- Appeals to absence of evidence.
Output shape
For each claim: (1) the claim verbatim with location; (2) what would need to hold for it to be true; (3) whether support is strong / mixed / weak / absent; (4) suggested revision or evidence needed.
Limitations
- →The skill focuses on claims about incentive alignment and mechanism-as-proof reasoning in `paper.qmd`.
- →The skill focuses on uniqueness / sufficiency claims in `projects/*/design.md` and `projects/*/blueprint.md`.
- →The skill cross-checks reliable claims against `context/attack-and-defense-log.md`.
How it compares
This skill provides a structured audit for scientific rigor, unlike a general review of document content.
Compared to similar skills
paper-audit-claims side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| paper-audit-claims (this skill) | 0 | 3mo | No flags | Advanced |
| citation-management | 23 | 7mo | Review | Beginner |
| microsoft-docs | 10 | 4mo | Review | Beginner |
| peer-review | 11 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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