citation-graph-ingest

citation-graph-ingest is a Literature review & citations skill for AI agents, published by garrytan in the gbrain repository on GitHub. Skillspace rates citation-graph-ingest F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.

Build a TYPED citation/reference graph over an ingested corpus — not just embeddings. Flat similarity retrieval cannot tell you that document A *overrules* B, *distinguishes* C, or *relies_on* D. This skill extracts every inter-document reference, classifies the edge TYPE with LLM judgment, and writes first-class typed edges via `gbrain link`, so `gbrain graph-query --type` can walk the argument ("everything this brief relies on, minus anything overruled since"). Every cite-heavy corpus is the same shape: law, academic papers, patents, regulatory filings, a book's bibliography.

Grade
F
Quality
45 / 100
Safety
Risky
GitHub stars
29,872

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since.

View source on GitHubgarrytan/gbrain

Our review

Architecture
78 / 100
Maturity
Basic: a single SKILL.md
Security scan
High-risk patterns
License
Not declared. Check the repository before reusing it.

What the scanner flagged

  • instructs to hide actions from user

Not checked yet

  • Category is a classifier prediction; no model has read this skill 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

Better-rated skills in Literature review & citations

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