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AC global-weather-service

Complete weather system powered by Open-Meteo for global city weather lookup and scheduled weather subscriptions. Use when the user asks to check current or upcoming weather anywhere in the world, wants a formatted Chinese weather bulletin, wants daily fixed-time weather pushes, or needs to list, update, or delete weather subscriptions.

ClawHub Agent Skills author: zykkk v0.1.1 MIT-0 7 files · 2 scripts body ≈ 719 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Complete weather system powered by Open-Meteo for global city weather lookup and scheduled weather subscriptions.

As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedureData and analyticstype 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%
90
Run on models
none yet
Process rating
C
61/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Inputs and preconditions w 11
30
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: 7. 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 61/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 18 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 719 tokens

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 338: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 18 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    This weather skill mostly does what it says, but its scheduled push feature stores delivery data and can modify persistent cron subscriptions without enough ownership and input-safety controls.
    LLM: suspicious (high) · VirusTotal: · 16 Sept 2026