Conciseness

The body is largely lean — no explanations of concepts Claude already knows, dense ID lookup tables explicitly justified as saving API calls ("so you don't need extra API calls"), and tight Pitfalls/Verification sections. It misses anchor 5 because of redundancy: the Quick Reference table repeats endpoints already shown in Procedure, and some Pitfall lines restate parameters already given inline.

Actionability

Every workflow ships copy-paste-ready curl + Python snippets with exact query parameters, the offline calculators have exact CLI invocations (e.g. `python scripts/body_calc.py tdee <weight_kg> <height_cm> <age> <M|F> <activity 1-5>`), and pitfalls give concrete mitigations (add `language=2`, `status=2`, `sleep 2`). This matches anchor 5: fully executable, specific examples covering the common cases.

Workflow Clarity

The exercise lookup is a clear numbered sequence (Step 1 identify → Step 2 reference IDs → Step 3 fetch and present), and a dedicated Verification section provides checkpoints with a sanity range ("TDEE should be 1500-3500"), plus rate-limit handling for batch requests — satisfying the batch-operations validation requirement. It falls short of anchor 5 because there are no error-recovery feedback loops (what to do when a query returns nothing or an API call fails).

Progressive Disclosure

The body points to real, one-level-deep bundle files — `references/FORMULAS.md` ("See references/FORMULAS.md for the science behind each formula") and `scripts/body_calc.py`, both verified to exist — and sections are clearly organized. Minor gaps keep it from anchor 5: the large ID/equipment tables and Quick Reference are bulk reference data inlined in SKILL.md that could live in `references/`, and `scripts/nutrition_search.py` exists in the bundle but is never referenced from SKILL.md, hurting discoverability.

Specificity

"Workout planning, macros, and body metrics via wger/USDA" names the domain and three capability areas plus the concrete data sources, but uses noun phrases rather than action verbs — matching anchor 3 (names domain and some concrete actions, not comprehensive) and below anchor 4, whose example lists several specific action verbs like 'Extracts... fills... converts'. It exceeds anchor 2 because it names three distinct capability areas and the specific systems used, not merely a generic domain.

Completeness

The 'what' is clearly stated (workout planning, macros, body metrics via wger/USDA) but there is no 'Use when...' clause or equivalent trigger guidance, so per the rubric guideline completeness is capped at 3 — a clear 'what' with 'when' missing or only weakly implied.

Trigger Term Quality

"Workout planning", "macros", and "body metrics" are natural terms users would say, but common synonyms and specific phrases are missing — calories, diet, meal planning, gym, exercise, BMI, TDEE, body fat, 1RM. This fits anchor 3 (some relevant keywords but missing common variations) rather than anchor 4 (good coverage with only a few terms missing), since several high-frequency user phrasings are absent.

Distinctiveness Conflict Risk

The fitness/nutrition niche with named data sources (wger, USDA) is fairly distinct, but a broader health/diet or general nutrition skill could overlap on terms like 'macros' or 'body metrics' — matching anchor 4 (mostly distinct, minor overlap risk with closely related skills) rather than anchor 5's clear niche with distinct triggers, since the description lacks the distinctive trigger phrases that would fully separate it.