SKILLEMALL.ai

AA pybricks-debug-coach

Coach Pybricks and LEGO robot debugging through evidence, one-variable tests, and observable pass/fail checks.

ClawHub Agent Skills author: Hao Ying v0.1.1 MIT-0 9 files body ≈ 1 695 tokens Open the sourceclawhub.ai analyzed 3 d ago

Coach Pybricks and LEGO robot debugging through evidence, one-variable tests, and observable pass/fail checks.

As a process A 82/100 · Runs to the end — weak spots: failures and branches, progress reporting

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
A
82/100
Runs to the end
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
50
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: 9. 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 82/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 48 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1695 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 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)
    • +3Description length 110: 120–800 characters recommended
    • +2Single-language instructions
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 48 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a text-only coaching skill for Pybricks robot debugging and does not request device control, credentials, persistence, or broad local access.
    LLM: benign (high) · VirusTotal: · 27 Jul 2026