BC xiaozhi-teach-lesson-log
把独立教师的课后记忆变成结构化教学档案，每节课 5 分钟记完。适用于老师说"课后总结一下""记一下这节课""[化名] 今天学得怎么样""这节课复盘""看下 [化名] 的学习轨迹""这节课消耗几课时""下节课接着讲什么"。流程：即时记 5 维度（学了什么/掌握度/课堂反应/进步/调整）→ 分知识点记掌握度 → 生成课时待确认条目 → 给下节课衔接点。触发需带学员化名与日期；记录与课时条目都先给老师预览，确认后才写入。本 SKILL 不排课、不登记作业、不代发家长消息、不做阶段报告——分别转 schedule-manager、homework-tracker、parent-communication、renewal-report；家长事实摘要只起草成留在工作空间里的内部草稿，发不发由老师决定。
把独立教师的课后记忆变成结构化教学档案，每节课 5 分钟记完。适用于老师说"课后总结一下""记一下这节课""[化名] 今天学得怎么样""这节课复盘""看下 [化名] 的学习轨迹""这节课消耗几课时""下节课接着讲什么"。流程：即时记 5 维度（学了什么/掌握度/课堂反应/进步/调整）→ 分知识点记掌握度 →…
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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 349 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 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 3478 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- low 15 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 6 example trigger phrases
- +3Description length 349: enough signal without eating the budget
- +4Structure: 40 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (21 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: 73.