Run an instrumented walk of a specification universe and recover honest inference from it.

Custom licenceAuto-check passedData & Analytics

Install Specification Search

skills CLI
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill specification-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills specification-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/73-brycewang-p-hacking-skills/skills/03-specification-search .claude/skills/specification-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
specification-search
GitHub stars
4.5k
Token cost
~3.3k tokens
SKILL.md length
1,411 words
Files
1
Skills in repo
383
Repo updated
First seen
Licence
Custom licence

At a glance

Run an instrumented walk of a specification universe and recover honest inference from it.

  • Works in 6 steps: bonferroni_p_of_best — correct but badly… → effective_tests — Li & Ji's count of… → romano_wolf_p_of_best — stepdown FWER… → …
  • Run a multiverse
  • SKILL.md covers The contract, Designs, Running and Reading the audit, plus 4 more sections
  • Calls python

What it does

Specification Search is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Run an instrumented walk of a specification universe and recover honest inference from it. Estimates every specification in a design card (or walks it with a realistic search procedure), logs a complete ledger, flags pathological specifications, calibrates the search against an enforced null, runs the Simonsohn joint tests on the whole curve, measures how far the finding sits from the pre-registered analysis, attributes significance to the choices that produced it, and writes a publishable honest report. Use to…

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Statistics. The repository describes itself as: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI…

When your agent uses it

  • Run a multiverse
  • Specification-curve analysis
  • Audit a search someone else ran
  • Compute multiplicity-corrected

Example prompts

  • “/specification-search”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. bonferroni_p_of_best — correct but badly conservative, because
  2. effective_tests — Li & Ji's count of independent specifications. Three
  3. romano_wolf_p_of_best — stepdown FWER control that exploits the
  4. min_p_test.honest_p — the headline. The share of null datasets on which
  5. min_p_test_unflagged — the same, for the best specification that carries
  6. procedure_test — with --procedure: what the procedure reported,

What it can do on your machine

Read from SKILL.md and the folder at commit 9fa87d8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Specification Search loads about 3.3k tokens when it runs. Until then it costs about 199 tokens; SKILL.md has 1,411 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~199
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,411 words (~3,278 tokens).

“This engine will walk any grid you hand it, including a grid built to find significance, with any procedure a p-hacker would use. It will not let the walk go unrecorded. Every run directory contains:”

— opening of SKILL.md by brycewang-stanford, Custom licence
name
specification-search

Read the full SKILL.md on GitHub

Files

Just SKILL.md in skills/73-brycewang-p-hacking-skills/skills/03-specification-search of brycewang-stanford/Auto-Empirical-Research-Skills.

Open the folder on GitHubat commit 9fa87d8

Compare with similar skills

Specification Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Specification Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Specification Search this skillbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~3.3kAutomated safety check: PassCustom licence
Sandbox Benchvercel/next.js143k—~4.1kAutomated safety check: PassMIT
Statistical Analysisspacering-net/codeg3.9k3 repos~5kAutomated safety check: PassMIT
StatsmodelszLanqing/codex-claude-academic-skills4.7k15 repos~4.9kAutomated safety check: PassBSD-3-Clause
AI Daily DigestvigorX777/ai-daily-digest1.6k—~1.3kAutomated safety check: PassNone
Statistical Powerspacering-net/codeg3.9k1 repos~3.6kAutomated safety check: NotesMIT

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Questions about Specification Search

What does Specification Search do?

Run an instrumented walk of a specification universe and recover honest inference from it. Specification Search is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Run an instrumented walk of a specification universe and recover honest inference from it.

When should I use Specification Search?

Specification Search fits situations like: run a multiverse; specification-curve analysis; audit a search someone else ran; compute multiplicity-corrected.

How do I install Specification Search in Claude Code?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill specification-search -a claude-code`. Or copy the skill folder (skills/73-brycewang-p-hacking-skills/skills/03-specification-search in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/specification-search in your project. Claude Code loads it when a task matches its description.

How do I install Specification Search in Codex?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill specification-search -a codex`. Or copy the skill folder (skills/73-brycewang-p-hacking-skills/skills/03-specification-search in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/specification-search in your project. Codex loads it when a task matches its description.

Can I use Specification Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill specification-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/specification-search, .gemini/skills/specification-search, .github/skills/specification-search and .opencode/skills/specification-search in your project.

What does Specification Search need to run?

Going by SKILL.md and its folder, Specification Search needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Specification Search access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Specification Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Specification Search use?

Specification Search has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Specification Search use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Specification Search?

Skills that share tags, products or a category with Specification Search: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.9k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars) and AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Specification Search?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,542 GitHub stars. The repository holds 383 skills in this directory. The repository was last updated on October 5, 2026.

Source: brycewang-stanford/Auto-Empirical-Research-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.