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 skills add aiming-lab/AutoResearchClaw --skill stat-result-validatorgit 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/skills/aiming-lab/autoresearchclaw/stat-result-validator)<a href="https://agentmods.dev/skills/aiming-lab/autoresearchclaw/stat-result-validator"><img src="https://agentmods.dev/badge/skills/aiming-lab/autoresearchclaw/stat-result-validator.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 | $0.00036 | $0.00820 |
| Opus 5 | $0.00018 | $0.00410 |
| Sonnet 5 | $0.00007 | $0.00164 |
| Haiku 4.5 | $0.00004 | $0.00082 |
Grade A, and why
stat-result-validator 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stat Result Validator
Overview
Use this skill after formulation, method proposal, theory, experimental evaluation, comparison, and result synthesis. It checks whether the final result is supported by a coherent statistical research chain.
Artifact Checks
Required for all topics:
progress/<TOPIC_ID>/step0_problem_formulation.md
progress/<TOPIC_ID>/step1_method_proposal.md
progress/<TOPIC_ID>/step2_theory_analysis.md
progress/<TOPIC_ID>/step3_experimental_evaluation.md
progress/<TOPIC_ID>/step4_comparison.md
progress/<TOPIC_ID>/step5_result_synthesis.md
progress/<TOPIC_ID>/step6_quality_audit.md
experiments/<TOPIC_ID>/config.yaml
experiments/<TOPIC_ID>/results/metrics.json
experiments/<TOPIC_ID>/results/run_manifest.json
experiments/<TOPIC_ID>/results/comparison_summary.md
experiments/<TOPIC_ID>/results/claim_verdicts.json
experiments/<TOPIC_ID>/report/paper.md
experiments/<TOPIC_ID>/README.md
Analysis-specific source files and raw outputs are determined by the experiment
plan and should live under experiments/<TOPIC_ID>/src/ and
experiments/<TOPIC_ID>/results/.
Formulation Checks
The formulation must define:
- Observed data and sampling regime
- Data model or data source
- Target parameter, decision, prediction, or risk
- Assumptions
- Claims or hypotheses
- Evaluation criteria
- Theory targets
Blocking failures:
- No target or estimand.
- Claims cannot be measured.
- Assumptions are absent or incompatible with the proposed method.
- Evaluation criteria do not answer the research question.
Method Checks
Verify that:
- The proposed method addresses the formulated target.
- Baselines are meaningful.
- Ablations isolate important design choices.
- Diagnostics are specified for likely failure modes.
- Method outputs match the metrics and theory targets.
Theory Checks
Theory may be rigorous or partial, but it must be explicit.
Check for:
- Definitions and assumptions.
- Proposition, theorem, derivation, counterexample, or clearly labeled heuristic analysis.
- Predicted empirical patterns.
- Limitations and regimes not covered.
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.
- 7d ago First seen · 130 lines · 36 tokens per session scan A 15742a69a3b2
stat-result-validator is a skill published in the GitHub repository aiming-lab/AutoResearchClaw (14,344 stars, last pushed 18d ago), licensed MIT. It adds 36 tokens to every session and 820 once invoked, about $0.0002 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.
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arxiv-summarizer-orchestrator
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baseline-comparison-audit
Audit whether a paper's baseline comparisons are COMPLETE, FAIR, and SIGNIFICANT: a required recent SOTA baseline is missing while 'best/SOTA' is claimed (HP-MISSING-BASELINE); a baseline is undertuned / given less compute-tuning-data, run at a mismatched config, or the equal-budget ablation-as-baseline is absent…
eval-design-forensics
Audit whether a paper's EVALUATION DESIGN actually measures what it claims and whether its reporting is complete — the validity layer family D (experiment-forensics) cannot reach. Three patterns: train/test leakage means the reported score may not measure generalization (HP-EVAL-LEAKAGE — adopts the Kapoor & Narayanan…
proof-derivation-forensics
Family-G proof & derivation integrity forensics: does a THIRD PARTY's written proof/derivation actually establish its theorem, or does it skip an obligation, assume its own conclusion, take an invalid step, drift a symbol's meaning, or smuggle an unstated assumption? Decides from the WRITTEN proof/derivation …