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Stat Result Validator

Audits statistical research outputs for formulation, theory, evidence and claim consistency

Source Download skill
Repository
aiming-lab/AutoResearchClaw
Stars
14,802
Licence
MIT
Files
1 file

What it does

This skill gives an AI agent a checklist for reviewing a statistical research project before its conclusions are trusted. The agent checks that the problem is clearly defined, the method fits the problem, theory is stated, experiments test the claims fairly, and the final claims are not stronger than the evidence. Each claim is then marked PASS, WARN, or FAIL, with missing pieces listed. It is designed for the output of the AutoResearchClaw research pipeline, which expects a specific folder layout.

Great for

  • Researchers or students who want a structured second opinion on a statistical analysis or paper draft
  • Teams using the AutoResearchClaw pipeline who need a quality gate before reporting results
  • Reviewers checking whether a paper's claims are supported by its experiments and theory

Skip it if

  • Projects that do not follow the expected progress/ and experiments/ folder layout, since many checks look for specific files (the agent would have to adapt the checklist)
  • Replacing a qualified statistician's review for high-stakes decisions, because the skill is a checklist applied by an AI and can miss subtle statistical errors
  • Non-statistical content, since the checks are written for statistical research chains

Try asking

  • “Validate the statistical research outputs for topic TOPIC_ID and tell me which final claims are PASS, WARN, or FAIL”
  • “Check whether my method proposal actually addresses the estimand stated in my problem formulation”
  • “Audit the comparison between my proposed method and baselines for fair-comparison problems”
  • “Review my paper draft and list any claims stronger than the theory supports”
Step-by-step guide: how to use Stat Result ValidatorInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    stat-result-validator.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip stat-result-validator.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip stat-result-validator.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Run it after all research stages are complete, since it checks the whole chain from formulation to final claims
  • Provide the actual files (metrics.json, claim_verdicts.json, paper.md) so the agent can cite specific evidence rather than guessing
  • Treat PASS as a checklist result, not proof of correctness, and have a domain expert review any FAIL or WARN items

What's inside

  • SKILL.md

Redistributed unmodified from aiming-lab/AutoResearchClaw under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.