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AC coach

Create personalized triathlon, marathon, and ultra-endurance training plans. Use when athletes ask for training plans, workout schedules, race preparation, or coaching advice. Can sync with Strava to analyze training history, or work from manually provided fitness data. Generates periodized plans with sport-specific workouts, zones, and race-day strategies.

ClawHub Agent Skills author: shiv19 v1.0.0 9 files body ≈ 4 518 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency

GeneratorInfrastructuretype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Consistency w 8
40
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 55/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (coach) differs from the folder (clawd-coach)
    • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 7 branches
    • 70Execution cost. Instruction body is 4518 tokens
    • 85Steps. 76 steps, 2 vague phrases
    • 100Running it twice. Mutating operations check current state
    • 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)
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 359: enough signal without eating the budget
    • +4Structure: 29 headings
    • +3Step-by-step instructions: 76 items
    • +3Output format is stated explicitly
    • +4Has examples (13 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)

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

    External checks

    ClawHub: suspicious
    This endurance-coaching skill is purpose-aligned, but its Strava setup asks for sensitive OAuth material and runs an unpinned npm tool that handles private activity data.
    LLM: suspicious (high) · VirusTotal: benign · 10 Sept 2026