SKILLEMALL.ai

AB steps-to-calories-calculator

Calculates calories burned walking from body weight and step count, using a peer-reviewed biomechanics formula (Weyand, Smith, Puyau & Butte, 2010, Journal of Experimental Biology) rather than a generic guess. Asks the user for body weight and step count first, converts units if needed, then computes an evidence-based estimate with its margin of error clearly stated. Use when a user asks how many calories they burned walking, wants a steps-to-calories converter, a walking calorie burn calculator, daily step count energy expenditure, or "how many calories do I burn per 1000/10000 steps".

ClawHub Agent Skills author: Arbaz Asif v0.1.0 MIT-0 3 files body ≈ 1 849 tokens Open the sourceclawhub.ai analyzed 3 d ago

Calculates calories burned walking from body weight and step count, using a peer-reviewed biomechanics formula (Weyand, Smith, Puyau & Butte, 2010, Journal of…

As a process B 67/100 · Nearly there — weak spots: result and completion, when it triggers

AnalyzerInfrastructurePersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
When it triggers w 12
20
Failures and branches w 10
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 67/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 21 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1849 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 14 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 593: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (3 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This skill is a self-contained walking calorie calculator that asks for weight and steps and does not request system access, credentials, networking, or persistence.
    LLM: benign (high) · VirusTotal: · 5 Sept 2026