AC datacrawl-debug
Use when user needs to process web data, debug data collection code, clean processed data, or iterate on data processing strategies. Use when generating data processing code from URL and field descriptions. Use when diagnosing data processing errors like 403, timeout, selector failures, encoding issues. Use when cleaning, deduplicating, normalizing, and formatting processed data. Use when optimizing data processing strategies based on run history analysis. Use when user mentions "数据处理", "数据整理", "数据清洗", "数据代码", "数据调试", "data processing", "data extraction", "debug data".
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "progressive"
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 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
- 100Tools and files. No external tools needed
- 100Steps. 25 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 524 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -44 reference files, but SKILL.md never points to them: the model will not open them
- -31 of 6 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 575: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (5 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.