Statistical Research Orchestrator
Guides an agent through a formal statistical research pipeline from problem setup to audited report
- Repository
- aiming-lab/AutoResearchClaw
- Stars
- 14,802
- Licence
- MIT
- Files
- 1 file
What it does
This skill tells an AI agent to run statistical research in a fixed order: first define the problem formally (target, assumptions, evaluation criteria), then propose a method, analyse its theory, design and run experiments, compare results against baselines, write a final report, and finally audit the whole chain. Each stage is handled by a named sub-skill and leaves a markdown progress file that the next stage reads, and the agent is told to stop if the target or assumptions are undefined. The skill is a coordinator and process guide; it does not itself contain statistical methods or code beyond what the referenced sub-skills provide.
Great for
- Researchers who want an AI-assisted, theory-first workflow for a statistics question
- Students learning how to structure a statistical study with explicit assumptions and baselines
- Developers building an automated research pipeline who want audit checkpoints between stages
Skip it if
- Quick one-off data cleaning or charting, since the full pipeline is heavy and slow (the workflow is designed for multi-stage research projects)
- Making high-stakes decisions from the output without expert review, because the agent's theory and proof sketches may be wrong or only heuristic
Try asking
- “Set up a formal problem and target estimand for comparing two estimators on my dataset description, and stop if assumptions are missing”
- “Run the full statistical research pipeline on this topic file and write the progress files for each step”
- “Audit the existing progress folder for topic X and tell me whether the conclusions are supported by the experiments”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
stat-research-orchestrator.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip stat-research-orchestrator.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip stat-research-orchestrator.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 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
- Provide a clear topic statement and dataset description up front, since the pipeline halts if the target or assumptions are undefined
- Review the step0 formulation and step6 audit files yourself, because the agent's own audit is not an independent check
- Treat theory outputs as labelled heuristics unless a proof has been checked by a statistician
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.