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SKILL verified MIT Self-run

Paper Claim Extractor

skill-maximussthegreat-ml-researcher-os-paper-claim-extractor · by maximussthegreat

Use when reading an ML paper, abstract, README, or result section and the task is to extract claims, assumptions, experiments, limitations, or implementation requirements.

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Install

$ agentstack add skill-maximussthegreat-ml-researcher-os-paper-claim-extractor

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Paper Claim Extractor

Use this skill before implementing, reproducing, or summarizing an ML paper.

Goal

Convert paper text into a structured research brief that makes the agent slow down before coding.

Required output

Produce these sections:

  1. Core claim
  2. Evidence table
  3. Assumptions
  4. Datasets and splits
  5. Metrics
  6. Baselines
  7. Ablations
  8. Implementation requirements
  9. Limitations
  10. Questions before reproduction

Evidence table format

| Claim | Evidence in text | Evidence type | Confidence | Reproduction note | | --- | --- | --- | --- | --- |

Evidence type must be one of:

  • reported_result
  • method_description
  • ablation
  • theory
  • author_claim
  • missing

Confidence must be one of:

  • high
  • medium
  • low

Rules

  • Do not treat the paper's conclusion as ground truth.
  • Do not invent datasets, hyperparameters, or baselines.
  • If a detail is missing, write not specified.
  • Separate what the paper reports from what you infer.
  • Flag any claim that depends on a single dataset, a weak baseline, or missing ablations.

Final check

End with:

Ready to plan experiments: yes/no
Blocking missing details:
- ...

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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