SKILLEMALL.ai

AB nutrition-advisor-en

Use only when the user explicitly asks for nutrition or diet-related help: calorie and macro estimation, TDEE/BMR and target intake calculations, meal planning for fat loss, muscle gain, or weight maintenance, daily food and hydration logging, restaurant meal estimation, cycle-aware nutrition, and diet guidance related to glucose management, digestion, sleep, anti-inflammatory eating, stress, intermittent fasting, carb cycling, or reverse dieting. Do not use for medical diagnosis, non-diet fitness programming, pure cooking recipes, shopping lists, file management, or general lifestyle advice.

ClawHub Agent Skills author: Megan v1.0.1 MIT-0 3 files body ≈ 4 217 tokens Open the sourceclawhub.ai analyzed 2 d ago

Use only when the user explicitly asks for nutrition or diet-related help: calorie and macro estimation, TDEE/BMR and target intake calculations, meal…

As a process B 75/100 · Nearly there — weak spots: inputs and preconditions, running it twice

AnalyzerWriting and documentsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
75/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
60
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: 3. 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 75/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 60Failures and branches. 2 branches
    • 70Execution cost. Instruction body is 4217 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 64 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 28 top-level sections: this looks like several domains in one skill

    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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 599: enough signal without eating the budget
    • +4Structure: 33 headings
    • +3Step-by-step instructions: 64 items
    • +3Output format is stated explicitly
    • +4Has examples (16 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This nutrition skill is a disclosed, user-directed advisor with local-only optional logging and clear medical safety boundaries.
    LLM: benign (high) · VirusTotal: · 13 Jul 2026