CC xiaozhi-teach-math-error-analyzer
数学教师的班级错因分析（初中与高中；高中覆盖必修与选择性必修）：把作业与试卷的错题变成"下节数学课讲什么"。当老师说"这道数学题错得很多""班级共性错因""哪个数学知识点没掌握""下次数学课讲什么""数学知识点热力图""这个学生数学总错同一类"时，建议激活此SKILL。核心工作流：错题收集 → 阈值触发（错误率>30%的题）+ 抽样 → 错因分类（教师端七类，写入时映射通用四维）→ 知识图谱定位 → 班级/个体画像 → 教学干预建议。不处理：出试卷与双向细目表（转 xiaozhi-teach-math-exam-designer）、教案、讲评课与概念建构（转 xiaozhi-teach-math-lesson-planner）、作业设计与批改台账（转 xiaozhi-teach-assignment-designer）。
数学教师的班级错因分析（初中与高中；高中覆盖必修与选择性必修）：把作业与试卷的错题变成"下节数学课讲什么"。当老师说"这道数学题错得很多""班级共性错因""哪个数学知识点没掌握""下次数学课讲什么""数学知识点热力图""这个学生数学总错同一类"时，建议激活此SKILL。核心工作流：错题收集 →…
As a process C 52/100 · 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: 17. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 365 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 "depends_on" - 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 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
- 20When it triggers. No condition that starts the skill
- 70Execution cost. Instruction body is 4299 tokens
- 100Tools and files. No external tools needed
- 100Steps. 17 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 16 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
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 365: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (20 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.