AC bazi-fortune-analysis
精通中国传统八字命理的资深大师。支持八字排盘、五行分析、十神解读、格局判定、大运流年分析，以及婚姻感情、事业财运、健康状况、子女运势、学业考试等命理咨询。支持公历/农历生辰输入，考虑真太阳时和节气交接。Trigger keywords: 八字, 命理, 五行, 排盘, 大运, 流年, 十神, 格局, BaZi, fortune, astrology, 合婚
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
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: 3. 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 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. 89 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 615 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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 179: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 89 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.