Conciseness

The ontology-specific patterns (bdi: vocabulary, T2B2T, notation table) earn their tokens, but the Core Concepts section re-explains basic BDI theory Claude already knows ('Belief: What the agent believes to be true about the world', DOLCE endurant/perdurant distinctions), and the intro paragraph pads with buzzphrases like 'supporting deliberative reasoning, explainability, and semantic interoperability'. This matches anchor 3 (mostly efficient but includes some unnecessary explanation or could be tightened) rather than 4, since multiple sections could be trimmed.

Actionability

Most guidance is concrete and copy-adaptable: complete Turtle patterns for the cognitive chain, world-state grounding, temporal validity, and executable SPARQL competency questions. The Python LAG example calls undefined helpers (serialize_ontology, extract_rdf_triples, retry_with_feedback) and the SEMAS Prolog uses illustrative custom syntax, which are minor gaps — fitting anchor 4 (mostly executable guidance with minor gaps) rather than 5's fully copy-paste-ready coverage.

Workflow Clarity

A three-phase sequence exists (T2B2T: translate RDF to beliefs, execute BDI reasoning, project back to RDF) and the competency questions act as a validation checkpoint, but the sequence is scattered between the T2B2T section and guideline #8 rather than presented as an operational workflow, and there are no explicit error-recovery or checkpoint steps in the main flow. This fits anchor 3 (steps listed but validation gaps; sequence present but checkpoints implicit) better than 4's clear sequence with most checkpoints present.

Progressive Disclosure

The References section points to four files ('bdi-ontology-core.md', 'rdf-examples.md', 'sparql-competency.md', 'framework-integration.md') but no references/ directory or bundle files exist — every referenced path is dangling. Meanwhile the complete RDF examples and full competency queries are inlined in the body anyway, fitting anchor 2 (content that clearly belongs in separate files is inlined) combined with references that mislead rather than aid navigation; this keeps it below anchor 3's 'references present' with genuine structure behind them.

Specificity

The description names several action phrases ("model agent mental states", "transform RDF to beliefs", "implement BDI architecture") but these all describe the same single modeling activity, and there is no standalone statement of concrete capabilities or outputs (e.g., generating BDI ontology triples, SPARQL competency queries). It sits between anchor 3 (domain plus 1-2 concrete actions, not comprehensive) and anchor 4; the action coverage is too narrow and trigger-phrased to reach 4.

Completeness

The "when" is fully explicit ("This skill should be used when the user asks to...") with concrete trigger phrases, but the "what" is only implied through those trigger phrases rather than stated as a capability description. Anchor 4 ("both 'what' and 'when'; 'when' could be more explicit or specific") is inverted here — the 'when' is stronger than the 'what' — which keeps it below anchor 5's clear and explicit answer to both.

Trigger Term Quality

Quoted natural phrases ("model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent") plus mention triggers (BDI ontology, mental state modeling, rational agency, neuro-symbolic AI integration) comprehensively cover the niche domain with synonyms and both abbreviated and expanded forms. This matches anchor 5's comprehensive synonym coverage; no natural user phrasing for this domain is obviously missing.

Distinctiveness Conflict Risk

BDI, belief-desire-intention, mental state modeling, and rational agency form a clear niche with distinct triggers; no other common skill category would match these phrases. This matches anchor 5 (clear niche, distinct triggers, minimal conflict risk).