BC xiaozhi-teach-english-assessment
英语综合测评设计：帮英语老师把"一张卷子"变成听说读写四维的能力测评与画像。触发语："学员英语水平如何"、"英语综合测评怎么设计"、"听说读写怎么测"、"CSE/CEFR 对照怎么用"、"学员能做什么"、"英语能力画像"、"测完之后怎么给建议"。核心工作流：能力目标（听说读写 4 维）→ 以 CSE 描述语定级、CEFR 只作国际参照 → 测评设计 → 能力画像（分数 + 微技能）→ 教学干预建议 → 写回班级工作空间。不处理：听力材料的选编与听法训练（转英语听力材料设计）、口语活动与纠错策略（转英语口语活动设计）、通用命题的双向细目表与信效度（转 xiaozhi-teach-exam-designer）。
英语综合测评设计：帮英语老师把"一张卷子"变成听说读写四维的能力测评与画像。触发语："学员英语水平如何"、"英语综合测评怎么设计"、"听说读写怎么测"、"CSE/CEFR 对照怎么用"、"学员能做什么"、"英语能力画像"、"测完之后怎么给建议"。核心工作流：能力目标（听说读写 4 维）→ 以 CSE…
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: 18. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 307 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. 28 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3292 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
- +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 307: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 28 items
- +4Has examples (22 code blocks)
- +4Reference files are cited in the instructions (8 of 8)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.