AC ljh-maidian
卖点体检器。丢一句或一组卖点文案进来，跑六道检验，判断这是独一份卖点还是随时会被抄的公共卖点，给出通过/打回结论和改法。 触发方式：/ljh-maidian、「帮我看看这个卖点行不行」「这句卖点站得住吗」「体检一下我的卖点」「这个卖点会不会被主播怼回来」 Selling-point health check. Feed in one or a batch of selling-point copy, run six checks, and get a pass/reject verdict with concrete fixes. Trigger: /ljh-maidian, "check my selling point", "is this selling point solid", "will this get challenged by a live host" 论文摘要评审、产品说明书合规审查等非带货卖点语境，不要自动触发。
卖点体检器。丢一句或一组卖点文案进来，跑六道检验，判断这是独一份卖点还是随时会被抄的公共卖点，给出通过/打回结论和改法。 触发方式：/ljh-maidian、「帮我看看这个卖点行不行」「这句卖点站得住吗」「体检一下我的卖点」「这个卖点会不会被主播怼回来」 Selling-point health check.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "slug"
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. 51 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1387 tokens
- 100Running it twice. No mutating operations
- low 14 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 423: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 51 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.