BC policy-to-action
政策翻译官 —— 官话 → 人话 → 行动。把复杂政策条文转化为「能不能用、能省多少、该怎么做」的标准化报告,企业/个人通用,双输出 HTML + 可转发文本总览。
政策翻译官 —— 官话 → 人话 → 行动。把复杂政策条文转化为「能不能用、能省多少、该怎么做」的标准化报告,企业/个人通用,双输出 HTML + 可转发文本总览。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "trigger"
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. 95 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1194 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)
- +3Description length 82: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +4Structure: 25 headings
- +3Step-by-step instructions: 95 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.
External checks
ClawHub: clean
This skill is a coherent policy-analysis report generator; it asks for relevant user-provided context and uses web research, with no hidden code execution or credential access found.
LLM: benign (high) · VirusTotal: · 7 Aug 2026