paper-three-pass-extraction
paper-three-pass-extraction is a Literature review & citations skill for AI agents, published by lyndonkl in the claude repository on GitHub. Skillspace rates paper-three-pass-extraction D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Domain-neutral methodology for autonomously extracting structured notes from a single academic paper via three escalating passes. Pass 1 (inspectional, ~10-15 min) reads title, abstract, intro, section headings, conclusion, references at a glance, then applies the Five Cs framework (Category, Context, Correctness, Contributions, Clarity). Pass 2 (content grasp, ~30-60 min) reads the full paper skipping proofs, answers main-argument / Big-Question / hypotheses / figure-by-figure / references / confusions. Pass 3 (deep understanding, ~1-4 hours, reserved for important papers) virtually re-implements, challenges every assumption, identifies what is NOT said, asks the falsifiability question. The methodology is internal to the agent applying it - questions are answered against the paper's content, never asked of the operator. Inspired by Keshav 2007 ("How to Read a Paper") and Adler-style inspectional reading. Use when an extraction agent needs to convert dense academic prose into…
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 133
Unproven: rated by static analysis only, not yet compared head-to-head.
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Our review
- Architecture
- 89 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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