SKILLEMALL.ai

AB knowair-forecast

Get hourly (up to 360 hours) and daily (up to 15 days) weather forecasts by latitude and longitude via the Caiyun Weather API. Returns temperature trends, weather conditions, precipitation probability, wind, humidity, and life indices. Supports configurable detail levels. Use when the user asks about weather forecast, tomorrow's weather, weekly forecast, hourly forecast, will it rain, temperature trend, or future weather.

ClawHub Agent Skills author: Shuo Wang v1.0.0 MIT-0 4 files body ≈ 418 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 70/100 · Nearly there — weak spots: result and completion, progress reporting

IntegrationData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
B
70/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Failures and branches w 10
50
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: knowair-forecast (ClawHub)

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: 4. 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 70/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 14 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 418 tokens
    • 100Running it twice. No mutating operations

    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 425: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This is a straightforward weather forecast skill that uses a disclosed Caiyun API token and user-provided coordinates to retrieve forecasts.
    LLM: benign (high) · VirusTotal: · 29 May 2026