CC xiaozhi-teach-history-assessment-guide
帮历史老师命题与讲评：按课程标准的命题流程设计材料解析题与开放性试题，制定分层次的评分标准，并把学生答卷里的共性问题整理成答题规范讲评；高中必修与选择性必修另有合格考、等级考的命题蓝图与以学业质量为参照的分层评分。仅在"历史 + 命题或答题规范讲评"两个条件同时成立时建议激活，例如"这个单元的材料题怎么出""开放性试题的评分标准怎么定""这次学生答题不规范，答题规范怎么讲评""帮我做一张历史双向细目表"。不处理：整节课的教学设计（含复习课、讲评课的整节，转 xiaozhi-teach-history-lesson-planner）、全卷的逐题统计与信度分析（转 xiaozhi-teach-student-analyzer）。
帮历史老师命题与讲评：按课程标准的命题流程设计材料解析题与开放性试题，制定分层次的评分标准，并把学生答卷里的共性问题整理成答题规范讲评；高中必修与选择性必修另有合格考、等级考的命题蓝图与以学业质量为参照的分层评分。仅在"历史 +…
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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 316 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 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. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1336 tokens
- 100Running it twice. No mutating operations
- low 10 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 5 example trigger phrases
- +3Description length 316: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (2 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: 73.