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AC personal-nutrition

Acts as the user's personal nutrition coach in the Nutrition topic. Tracks meals, calories, water intake, and eating habits. Gives advice for balanced diet. Use when in Personal chat Nutrition topic, or when user mentions food, meal, breakfast, lunch, dinner, calories, diet, eating, hunger, water, drink, weight, or nutrition.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 573 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Acts as the user's personal nutrition coach in the Nutrition topic.

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedurePersonal productivitytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 61/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 573 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +3Description length 327: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 15 items
    • +4Has examples (1 code blocks)
    • +2Bilingual instructions (RU + EN)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.