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Connect to the WHOOP Developer Platform via official OAuth (authorization code flow), store and refresh tokens, and fetch WHOOP v2 data (recovery, sleep, cycle/strain, workout, profile, body measurements). Use when a user asks to connect/authorize WHOOP, pull WHOOP metrics, summarize today/yesterday, generate daily/weekly WHOOP reports, or send WHOOP updates to any OpenClaw chat channel (TUI/webchat/Slack/Discord/WhatsApp/Telegram/etc.).

ClawHub Agent Skills author: Gavin C. v0.1.0 MIT-0 11 files body ≈ 690 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSlackDiscordTelegramWhatsAppData and analyticsInfrastructuretype 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%
85
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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: 11. 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 47/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 40Consistency. Frontmatter name (whoop) differs from the folder (openclaw-slug)
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 100Steps. 18 steps
    • 100Execution cost. Instruction body is 690 tokens
    • 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
    • -31 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 441: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

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

    External checks

    ClawHub: suspicious
    The WHOOP metric scripts are mostly coherent, but the package also includes unrelated trusted-partner healthcare API operations that should be reviewed before installation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026