AC xhs-track-analysis
Use when 需要对小红书某个品类/赛道做深度分析，在看用户问什么、平台内容怎么回答、谁在讲且谁更可信、用户到底信不信，形成带证据边界的品牌建议与 GO/NO-GO 投决。Triggers on: 小红书赛道分析, 做赛道分析, 分析XX品类在小红书, 赛道研究, 小红书品类研究, 小红书内容生态分析, 小红书竞品内容分析, 小红书达人分析, 小红书种草分析. 产出决策简报（GO/NO-GO），不做市场规模建模、平台算法逆向或自动生成投放策略。
Use when 需要对小红书某个品类/赛道做深度分析，在看用户问什么、平台内容怎么回答、谁在讲且谁更可信、用户到底信不信，形成带证据边界的品牌建议与 GO/NO-GO 投决。Triggers on: 小红书赛道分析, 做赛道分析, 分析XX品类在小红书, 赛道研究, 小红书品类研究, 小红书内容生态分析…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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: 25. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Use when 需要对小红书某个品类/赛道做深度分析，在看用户问什么、平台内容怎么回答、谁在讲且谁更可信、用户到底信不信，形成带证… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 52/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 56 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1062 tokens
- 100Running it twice. No mutating operations
- low 10 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
- +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 226: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 56 items
- +4Reference files are cited in the instructions (5 of 5)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.