AC geoskill-precipitation-nowcasting
基于光流法(交叉相关位移估计)的拉格朗日持久性降水临近预报,外推未来 0-6 小时降水场,输出预报序列 GeoTIFF 与位移场 JSON。Optical-flow (cross-correlation) Lagrangian persistence nowcasting that extrapolates precipitation fields 0-6 hours ahead, outputting a forecast GeoTIFF stack and a displacement-field JSON.
基于光流法(交叉相关位移估计)的拉格朗日持久性降水临近预报,外推未来 0-6 小时降水场,输出预报序列 GeoTIFF 与位移场 JSON。Optical-flow (cross-correlation) Lagrangian persistence nowcasting that extrapolates…
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: 22. 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. 14 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1434 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 259: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 14 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.