Quant Statistical Methods
HKUDS/Vibe-Trading
Guides your agent through unit-root, cointegration, GARCH, bootstrap and regression-diagnostic tests on financial time series, using a tested helper module.
Statistical methods for combining results across multiple studies.
MITAuto-check passed
Install Meta Analysis
$ npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/AutoResearchClaw meta-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/researchclaw/skills/builtin/experiment/meta-analysis .claude/skills/meta-analysis && rm -rf skills-srcUse ~/.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/
Install the "meta-analysis" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysis into .claude/skills/meta-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/AutoResearchClaw meta-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/researchclaw/skills/builtin/experiment/meta-analysis .agents/skills/meta-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "meta-analysis" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysis into .agents/skills/meta-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/AutoResearchClaw meta-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/researchclaw/skills/builtin/experiment/meta-analysis .cursor/skills/meta-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "meta-analysis" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysis into .cursor/skills/meta-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aiming-lab/AutoResearchClaw.git --path researchclaw/skills/builtin/experiment/meta-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/AutoResearchClaw meta-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/researchclaw/skills/builtin/experiment/meta-analysis .gemini/skills/meta-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "meta-analysis" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysis into .gemini/skills/meta-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aiming-lab/AutoResearchClaw meta-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/researchclaw/skills/builtin/experiment/meta-analysis .github/skills/meta-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "meta-analysis" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysis into .github/skills/meta-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aiming-lab/AutoResearchClaw meta-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/researchclaw/skills/builtin/experiment/meta-analysis .opencode/skills/meta-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "meta-analysis" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/meta-analysis into .opencode/skills/meta-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meta-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
meta-analysis- GitHub stars
- 15k
- Token cost
- ~230 tokens
- SKILL.md length
- 63 words
- Files
- 1
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
Statistical methods for combining results across multiple studies.
- Works in 7 steps: Report effect sizes, not just p-values → Use standardized metrics for cross-study… → Account for heterogeneity (different… → …
- Aggregating cross-study
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Cross-experiment results
What it does
Meta Analysis is an agent skill from aiming-lab/AutoResearchClaw. Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.
Its SKILL.md is about 230 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞. The licence is MIT.
When your agent uses it
- Aggregating cross-study
- Cross-experiment results
Example prompts
- “/meta-analysis”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Report effect sizes, not just p-values
- Use standardized metrics for cross-study comparison
- Account for heterogeneity (different setups, datasets, seeds)
- Report confidence intervals alongside point estimates
- Use forest plots to visualize cross-study comparisons
- Identify and discuss outliers or inconsistent results
- Consider publication bias when interpreting aggregate results
What it can do on your machine
Read from SKILL.md and the folder at commit be4ba47. 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
No scripts in the folder and no shell commands in SKILL.md.
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
Meta Analysis loads about 230 tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 63 words of instructions outside code blocks.
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
The full file from aiming-lab/AutoResearchClaw at commit be4ba47, republished under its MIT licence (© aiming-lab). 63 words, ~230 tokens.
Download SKILL.mdSave it as
.claude/skills/meta-analysis/SKILL.md (or your agent's skills folder).- name
- meta-analysis
- description
- Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.
- metadata.category
- experiment
- metadata.trigger-keywords
- meta-analysis,effect size,pooled,cross-study,aggregat
- metadata.applicable-stages
- 7,14
- metadata.priority
- 5
- metadata.version
- 1.0
- metadata.author
- researchclaw
- metadata.references
- Borenstein et al., Introduction to Meta-Analysis, 2009
Meta-Analysis Best Practice
When comparing results across studies or experiments:
- Report effect sizes, not just p-values
- Use standardized metrics for cross-study comparison
- Account for heterogeneity (different setups, datasets, seeds)
- Report confidence intervals alongside point estimates
- Use forest plots to visualize cross-study comparisons
- Identify and discuss outliers or inconsistent results
- Consider publication bias when interpreting aggregate results
© aiming-lab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in researchclaw/skills/builtin/experiment/meta-analysis of aiming-lab/AutoResearchClaw.
Open the folder on GitHubat commit be4ba47
Compare with similar skills
Meta Analysis 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Meta Analysis this skillaiming-lab/AutoResearchClaw | 15k | — | ~230 | Automated safety check: Pass | MIT | |
| Quant Statistical MethodsHKUDS/Vibe-Trading | 35k | — | ~4k | Automated safety check: Pass | MIT | |
| Statistical PowerK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~4.4k | Automated safety check: Notes | MIT | |
| Manuscript Statistics AuditYuan1z0825/nature-skills | 46k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Statistical Analystalirezarezvani/claude-skills | 28k | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Statistical Powerspacering-net/codeg | 3.8k | 1 repos | ~3.6k | Automated safety check: Notes | MIT |
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Manuscript Statistics Audit
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Audits or rewrites the statistical reporting in a manuscript: experimental units, replication, tests, uncertainty and figure legends, without inventing missing details.
Statistical Analyst
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Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes.
Statistical Power
spacering-net/codeg
Sample-size and statistical power calculations for planning studies.
- Official
Study Plan
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Build or update a long-term bar prep (or exam prep) study plan — phases, subjects weighted by weakness, daily session schedule, adaptive to session history in study-plan.yaml.
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Metabolic Study Planner
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Questions about Meta Analysis
What does Meta Analysis do?
Statistical methods for combining results across multiple studies. Meta Analysis is an agent skill from aiming-lab/AutoResearchClaw. Statistical methods for combining results across multiple studies.
When should I use Meta Analysis?
Meta Analysis fits situations like: aggregating cross-study; cross-experiment results.
How do I install Meta Analysis in Claude Code?
Run `npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a claude-code`. Or copy the skill folder (researchclaw/skills/builtin/experiment/meta-analysis in aiming-lab/AutoResearchClaw) into .claude/skills/meta-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Meta Analysis in Codex?
Run `npx skills add aiming-lab/AutoResearchClaw --skill meta-analysis -a codex`. Or copy the skill folder (researchclaw/skills/builtin/experiment/meta-analysis in aiming-lab/AutoResearchClaw) into .agents/skills/meta-analysis in your project. Codex loads it when a task matches its description.
Can I use Meta Analysis 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 aiming-lab/AutoResearchClaw --skill meta-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meta-analysis, .gemini/skills/meta-analysis, .github/skills/meta-analysis and .opencode/skills/meta-analysis in your project.
What does Meta Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Meta Analysis is instructions for the agent only.
Does Meta Analysis 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 Meta Analysis 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 Meta Analysis use?
Meta Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Meta Analysis use?
About 230 tokens (SKILL.md is roughly 920 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 Meta Analysis?
Skills that share tags, products or a category with Meta Analysis: Quant Statistical Methods (HKUDS/Vibe-Trading, 35k stars), Statistical Power (K-Dense-AI/scientific-agent-skills, 48k stars), Manuscript Statistics Audit (Yuan1z0825/nature-skills, 46k stars) and Statistical Analyst (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Meta Analysis?
aiming-lab (a GitHub organization) maintains it in aiming-lab/AutoResearchClaw, which has 14,587 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on August 19, 2026.
Source: aiming-lab/AutoResearchClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.