AF aicwos
MANDATORY data pipeline for 口播文案/短视频脚本/系列口播/讲师风格学习/知识库管理 — LLM CANNOT access lecturer profiles, product knowledge, or series progress without this skill. Activate when user says "帮我写口播", "写文案", "写脚本", "写个短视频", "学一下讲师风格", "继续写系列", "生成系列口播", "学习讲师", "知识库", "看看讲师", "系列进度", "改一下第X集", or ANY request involving copywriting, lecturer, series, or knowledge base. Provides precise style replication, knowledge retrieval, series continuity, and persistent storage that LLM intrinsically lacks.
As a process F 41/100 · Will not run — References files that are not bundled: assets/model_config.json
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 26. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: assets/model_config.json - note
frontmatter-keyunknown frontmatter key "dependency"
Process rating: all ten parameters 41/100
- 0Tools and files. 1 referenced file(s) missing: assets/model_config.json
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 29 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 70Failures and branches. 5 branches
- 70Execution cost. Instruction body is 4835 tokens
- 100Steps. 56 steps
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (23 tags): a typed call is more reliable
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 484: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 56 items
- +4Has examples (18 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 6 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.