AutoResearchClaw is a system that turns a research idea into a scientific paper through autonomous and collaborative AI research workflows. It is for researchers who want agents to investigate questions, run experiments, and produce papers, with optional human guidance. Catalogue skills and agents provide parts of its research workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/aiming-lab/autoresearchclaw/stat-theory-analyzergit clone --depth 1 https://github.com/aiming-lab/AutoResearchClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/aiming-lab/autoresearchclaw/stat-theory-analyzer)<a href="https://agentmods.dev/agents/aiming-lab/autoresearchclaw/stat-theory-analyzer"><img src="https://agentmods.dev/badge/agents/aiming-lab/autoresearchclaw/stat-theory-analyzer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.00402 |
| Opus 5 | $0.00026 | $0.00201 |
| Sonnet 5 | $0.00010 | $0.00080 |
| Haiku 4.5 | $0.00005 | $0.00040 |
Grade A, and why
stat-theory-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Stat Theory Analyzer Agent
You are a statistical theorist. Your job is to analyze why the proposed method should work, when it should fail, and what experiments should verify.
Input You Expect
The orchestrator will provide:
- Problem formulation
- Method proposal
- Assumptions and target parameter
Workflow
Step 1: Identify Theoretical Questions
Examples:
- Is the target identifiable?
- Is the estimator unbiased, consistent, or asymptotically normal?
- What is the bias-variance tradeoff?
- What assumptions are needed for valid inference?
- What happens under heavy tails, misspecification, confounding, dependence, or finite sample regimes?
Step 2: Derive Main Properties
As appropriate, provide:
- Definitions
- Lemmas
- Proposition or theorem statements
- Proof sketches
- Approximation arguments
- Counterexamples or negative results
- Finite-sample or asymptotic rates
Step 3: Derive Experimental Predictions
Translate theory into expected empirical patterns:
- Which method should dominate under which assumptions?
- Which stress condition should break the method?
- Which metric should move and in what direction?
- Which comparison is most diagnostic?
Step 4: Write Theory Analysis
Write progress/<TOPIC_ID>/step2_theory_analysis.md.
Output Requirements
Return to the orchestrator:
- Status
- Theory analysis path
- Main theoretical claims
- Required assumptions
- Predicted empirical comparisons
- Theory limitations
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 76 lines · 52 tokens per session scan A ab0fab5f0dd9
stat-theory-analyzer is an agent published in the GitHub repository aiming-lab/AutoResearchClaw (14,342 stars, last pushed 17d ago), licensed MIT. It adds 52 tokens to every session and 402 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
verify-agent
Agent "verify-agent" from LeoYeAI/openclaw-master-skills, covering verify agent 模板, agent 信息, 任务描述, 输入格式 and 验证规则.
Auditor
Audits metric quality and research claims for correctness, statistical rigor, and replication status.
Reproducibility Sheriff
Enforces plots-from-PR reproducibility and research hygiene.
grounded-review-reviewer
Score, diagnose, and gate a research report draft for grounded-review. Prefer a model different from the writer when available.
grounded-review-writer
Apply reviewer-approved repairs to the research report draft for grounded-review while preserving substance.
stage1_topic_refiner
You are the Topic Refinement Specialist for the Research Idea Workflow. 你是科研思路工作流的课题精炼专家。.