AC depth-of-field-control
用户想控制照片的清晰范围（背景虚化程度）、问"怎么拍出背景模糊/全景清晰"、 或纠结景深设置时调用。不适用于曝光量计算（应调用 exposure-dual-control）或 聚焦技术问题。 Invoke when the user wants to control the sharpness range (background blur level), asks "how to get blurred background / sharp everywhere," or is unsure about depth-of-field settings. Not for exposure calculation (use exposure-dual-control) or focus technique issues. 关键 trigger / Key triggers: "背景虚化"、"景深"、"bokeh"、"depth of field"、 "怎么让背景模糊"、"风光摄影全景清晰"、"hyperfocal distance"、 "how to blur background"、"sharp from foreground to infinity"。
用户想控制照片的清晰范围（背景虚化程度）、问"怎么拍出背景模糊/全景清晰"、 或纠结景深设置时调用。不适用于曝光量计算（应调用 exposure-dual-control）或 聚焦技术问题。 Invoke when the user wants to control the sharpness range…
As a process C 63/100 · 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "source_book" - note
frontmatter-keyunknown frontmatter key "source_chapter" - note
frontmatter-keyunknown frontmatter key "related_skills"
Process rating: all ten parameters 63/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 44 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 580 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
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +4Description says when NOT to use the skill
- +3Description length 534: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 44 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.