BC xiaozhi-teach-exam-designer
帮老师把"拼凑试卷"变成"按双向细目表命题"。当老师**明确要求生成或修改命题产物**时建议激活：出一份单元测验/试卷、写双向细目表、调整试卷难度配比、改编某道题、写评分细则、按题目统计决定哪些题返修。**不激活**：只讨论考试结果与学情分析（转 `xiaozhi-teach-student-analyzer`）、只备讲评课的环节与提问（转 `xiaozhi-teach-lesson-planner` / `xiaozhi-teach-classroom-coach`）、布置作业（转 `xiaozhi-teach-assignment-designer`）、非命题的日常教学讨论。工作流：测评类型 → 双向细目表 → 选题改编 → 难度与认知层级配比 → 评分标准 → 讲评错题清单；考后 P/D/信度只读不算。
帮老师把"拼凑试卷"变成"按双向细目表命题"。当老师明确要求生成或修改命题产物时建议激活：出一份单元测验/试卷、写双向细目表、调整试卷难度配比、改编某道题、写评分细则、按题目统计决定哪些题返修。不激活：只讨论考试结果与学情分析（转…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 359 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "grade_bands" - note
frontmatter-keyunknown frontmatter key "id" - note
frontmatter-keyunknown frontmatter key "min_platform_version" - note
frontmatter-keyunknown frontmatter key "max_round_limit" - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
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. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3321 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
- +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
- +2Single-language instructions
- +3Description length 359: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (19 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.