fitness-nutrition

Gym workout planner and nutrition tracker. Search 690+ exercises by muscle, equipment, or category via wger. Look up macros and calories for 380,000+ foods via USDA FoodData Central. Compute BMI, TDEE, one-rep max, macro splits, and body fat — pure Python, no pip installs. Built for anyone chasing gains, cutting weight, or just trying to eat better.

Quality

83%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

85%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, well-structured skill body with clear workflows and properly signaled one-level-deep references; its only weakness is minor token redundancy between the Procedure and Quick Reference sections.

Suggestions

Drop or trim the 'Quick Reference' endpoint table since the same endpoints appear verbatim in the Procedure section, or replace the Procedure tables with it to avoid duplication.

Reference scripts/nutrition_search.py in the body (e.g. under Nutrition Lookup) so the existing bundle file is discoverable rather than orphaned.

Remove the 'Expert fitness coach and sports nutritionist skill' opener, which restates the description without adding operational value.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with justified reference tables, but the closing 'Quick Reference' table repeats endpoints already detailed in the Procedure section and the 'Expert fitness coach…' intro is mild fluff, so it could be tightened.	2 / 3
Actionability	Fully executable curl+python3 snippets with exact endpoints and parameters, plus concrete calculator invocations — copy-paste ready with no pseudocode.	3 / 3
Workflow Clarity	Three explicitly sequenced steps (Identify → Reference IDs → Fetch and present) and a dedicated Verification section with concrete sanity checks (e.g. 'TDEE should be 1500-3500').	3 / 3
Progressive Disclosure	Clear sectioned overview with one-level-deep, well-signaled references to real bundle files (scripts/body_calc.py, references/FORMULAS.md); content is appropriately split rather than nested.	3 / 3
	Total	11 / 12 Passed

Description

82%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A specific, well-targeted description with strong trigger terms and a distinct niche, weakened only by the absence of an explicit 'Use when…' invocation clause.

Suggestions

Append an explicit trigger clause, e.g. 'Use when the user asks about workouts, exercises, muscle groups, food macros, calories, BMI/TDEE, or one-rep max estimates.'

Move the audience framing ('Built for anyone chasing gains…') into the trigger clause so it doubles as invocation guidance.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Search 690+ exercises by muscle, equipment, or category', 'Look up macros and calories', 'Compute BMI, TDEE, one-rep max, macro splits, and body fat' — rather than vague language.	3 / 3
Completeness	Clearly states what the skill does, but offers no 'Use when…' trigger clause — the closing 'Built for anyone chasing gains…' describes an audience, not when to invoke it, so completeness is capped at 2 per the missing-trigger guideline.	2 / 3
Trigger Term Quality	Natural user vocabulary is well covered: 'gym workout planner', 'nutrition tracker', 'macros', 'calories', 'cutting weight', 'chasing gains', 'eat better'.	3 / 3
Distinctiveness Conflict Risk	A clear fitness/nutrition niche anchored to specific named APIs (wger, USDA FoodData Central) makes it unlikely to trigger for the wrong skill.	3 / 3
	Total	11 / 12 Passed

Validation

81%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: NousResearch/hermes-agent
Path: optional-skills/health/fitness-nutrition/SKILL.md
Commit: 4c9628e

Reviewed: about 15 hours ago

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