AC geoskill-heatwave-impact-assessment
热浪影响评估：逐像元 P90 分位数阈值 + 连续≥3天连通域热浪检测，Stull/简化湿球温度健康风险分级，人口暴露与脆弱性制图。Heatwave impact assessment: per-pixel P90 threshold with connected-run detection, wet-bulb temperature health risk, population exposure and vulnerability mapping. 输出热浪日数/暴露人口/脆弱性/湿球风险 GeoTIFF + 事件清单 JSON。
热浪影响评估：逐像元 P90 分位数阈值 + 连续≥3天连通域热浪检测，Stull/简化湿球温度健康风险分级，人口暴露与脆弱性制图。Heatwave impact assessment: per-pixel P90 threshold with connected-run detection, wet-bulb…
As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 24. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 62/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1827 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 12 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)
- +2Single-language instructions
- +3Description length 270: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 22 items
- +3Output format is stated explicitly
- +4Has examples (14 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.