AC ljh-yinzi
内容因子工具。三种模式：拆解（把一条爆款素材拆到因子级）、排序（给候选专攻课题按 EV 打分排优先级并跑完整 SOP）、建库（指导搭建因子库三张表）。 触发方式：/ljh-yinzi、「帮我拆一条爆款」「这几个方向该先做哪个」「怎么搭因子库」 Content-factor toolkit for short-video e-commerce. Three modes: decompose a viral video into factors, rank candidate focus topics by expected value, or build a reusable factor library. Trigger: /ljh-yinzi, "break down this viral video", "which topic should I focus on first", "help me build a factor library" 学术论文结构拆解、金融因子模型这类非内容电商场景，不要自动触发。
内容因子工具。三种模式：拆解（把一条爆款素材拆到因子级）、排序（给候选专攻课题按 EV 打分排优先级并跑完整 SOP）、建库（指导搭建因子库三张表）。 触发方式：/ljh-yinzi、「帮我拆一条爆款」「这几个方向该先做哪个」「怎么搭因子库」 Content-factor toolkit for…
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. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2019 tokens
- 100Running it twice. No mutating operations
- low 24 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 463: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.