Conciseness

The body is dense and gbrain-specific throughout — no explanations of concepts Claude already knows, and every section carries non-obvious operational detail (provenance tag rules, exact-match `--type` semantics, edge-uniqueness keys). Minor over-explanation remains: the Contract and Anti-Patterns sections repeat several points (relational-recall limitation, test-before-bulk, source scoping), which fits the 4 anchor (efficient, minor instances that could be trimmed) rather than the lean 5.

Actionability

Copy-paste-ready commands throughout: `gbrain link doc-b-example doc-a-example --link-type extends --link-source citation-graph --context ... --source <corpus-source>`, `gbrain graph-query ... --type overrules --direction in`, plus `link-sources` and `check-backlinks` hygiene, a worked synthetic fixture, and a concrete output-format template. Fully executable guidance covering the common cases, matching the 5 anchor; the judgment steps (detect/classify) are instruction-only but name the exact tools (`gbrain search`, `get_page`, `resolve_slugs`) and are actionable.

Workflow Clarity

A clearly sequenced 5-step pipeline (preflight → detect → classify → write → verify → hygiene) with an explicit hard validation gate ("The run is not complete until a `graph-query` walk... No verified walk = the run reports failure"), failure-recovery guidance for specific errors (`page_not_found`, `sync_in_progress`/`lock_busy`), and a test-before-bulk checkpoint. This matches the 5 anchor (explicit validation, feedback loops, checklist-style process) — the batch-operation cap does not apply because validation is present.

Progressive Disclosure

Well-organized single-file skill with clear sections (What it is / Contract / Pipeline / Run it / Output Format / When it fails / Anti-Patterns / Dedup) and clearly signaled one-level-deep references to shared convention files at the top. It fits the 4 anchor (good structure, references mostly clear, minor gaps) rather than 5 because the conventions live outside the skill directory and a couple of sections (Dedup, Anti-Patterns) could arguably be externalized if the skill grows.

Specificity

Quotes multiple concrete actions — "extracts every inter-document reference, classifies the edge TYPE with LLM judgment, and writes first-class typed edges via `gbrain link`" plus the `graph-query --type` retrieval surface — comprehensively covering the pipeline. This matches the 5 anchor (multiple specific concrete actions, comprehensive coverage); it is not 4 because no meaningful capability is left out.

Completeness

The description field has a clear, explicit "what" but the "when" is only weakly implied by "Every cite-heavy corpus is the same shape: law, academic papers, patents..." — there is no "Use when..." clause in the description itself, which per the rubric caps completeness at 3. It is not 4 because the trigger guidance lives in a separate frontmatter `when_to_use` field outside the evaluated target, not in the description.

Trigger Term Quality

Natural terms present: "citation/reference graph", "overrules", "distinguishes", "relies_on", plus domain keywords ("law, academic papers, patents, regulatory filings, a book's bibliography"). Good coverage but a few natural user phrases are missing (e.g. "map citations", "who cites whom", "citation analysis"), so it fits the 4 anchor rather than the comprehensive 5.

Distinctiveness Conflict Risk

The description carves a clear niche — typed citation edges ("overrules / distinguishes / relies_on") written via `gbrain link` over an ingested corpus — with triggers no other generic skill would claim. Minimal conflict risk, matching the 5 anchor; it is not 4 because even closely related skills (citation formatting, claim verification) would not naturally fire on these phrases.