lyndonkl/claude/claim-extractor

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Extracts atomic technical claims from a substacker essay draft, converting flowing intuition-first prose into a numbered list where each item is a statement that could in principle be verified or falsified. Skips non-technical sections (personal anecdote, motivation, call-to-action). Use when the Technical Reviewer starts a per-draft review. Trigger keywords — extract claims, atomic claims, technical claim list, fact-check prep.

Install

npx vskill@latest install lyndonkl/claude/claim-extractor

SKILL.md

Claim Extractor

Workflow

Per draft:
- [ ] Step 1: Segment draft by heading / section
- [ ] Step 2: Within each section, split by sentence
- [ ] Step 3: Flag sentences containing technical claims:
- Math symbols / formulas
- Named systems, components, algorithms
- Quantitative assertions
- Universal quantifiers ("always", "never", "all models")
- Named papers / results
- [ ] Step 4: Coalesce adjacent claim sentences that argue the same thing into one claim
- [ ] Step 5: Output numbered list: {id, excerpt (≤200 chars), location}

Non-claim content (skip)

  • Personal anecdotes without technical assertion
  • Motivation / framing
  • Calls to action
  • Closing maxims (unless they assert a technical fact)

Worked example

Draft paragraph:

Attention is O(n²). This is why context windows are expensive. Each token looks at every other token, and the matrix is n-by-n.

Extraction:

  1. "Attention is O(n²) in compute and memory in a naive implementation." [§2 ¶1]
  2. "Context windows are expensive because of attention's complexity." [§2 ¶1]
  3. "Each token attends to every other token via an n-by-n matrix." [§2 ¶1]

Guardrails

  1. Never paraphrase aggressively. Preserve the writer's hedges.
  2. Excerpts ≤200 chars verbatim.
  3. Coalesce adjacent claims only if they argue the same thing.
  4. Respect [contrarian] annotations — still extract the claim, but flag it for classify-claim to treat specially.
  5. Don't extract claims from code blocks or quoted text.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
147
Repository forks
22
7-day trend score
25

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