BC xiaozhi-teach-student-analyzer
把班级成绩表变成可执行的教学调整。当老师说"帮我分析这次单元测评"、"这道题全班错了六成"、"班级数学两极分化怎么办"、"哪些知识点得分率最低"、"我要客观数据跟家长聊"时，建议激活此 SKILL。工作流：导入逐题分数 → 班级画像 → 知识点热力图 → 分层 → 教学调整建议。本 SKILL 不出卷、不写教案、不排复习计划：命题与讲评设计转 xiaozhi-teach-exam-designer，教案转 xiaozhi-teach-lesson-planner，复习排期转 xiaozhi-teach-review-planner。
把班级成绩表变成可执行的教学调整。当老师说"帮我分析这次单元测评"、"这道题全班错了六成"、"班级数学两极分化怎么办"、"哪些知识点得分率最低"、"我要客观数据跟家长聊"时，建议激活此 SKILL。工作流：导入逐题分数 → 班级画像 → 知识点热力图 → 分层 → 教学调整建议。本 SKILL…
As a process C 55/100 · 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 269 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 55/100
- 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
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3603 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- low 13 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
- -217 emoji in the instructions: noise for the model
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 269: enough signal without eating the budget
- +4Structure: 34 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (20 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.