CC xiaozhi-math-problem-solving-coach
初中到高中的数学单题解题教练（高中覆盖必修与选择性必修）：学生发来一道数学题说"卡住了""这道数学题我做错了""我不知道怎么列式"时，用追问帮学生找回思路，提示按 shared/hint-ladder.md 逐级升。也用于出同类题、考前梳理（"明天数学考试，帮我梳理这一章"；只在学生明确说考试在即时进入）。默认只在当前会话工作：不读档案、不归档、不排提醒，三项都要学生当轮明确开启；含全库统一的数据控制入口与危机例外。不处理：错题的长期记录与次数统计（转 xiaozhi-correction-notebook）、错因子类型与顽固弱项分析（转 xiaozhi-math-error-dna）、分层进阶训练（转 xiaozhi-math-gradient-trainer）、只问概念不解题（转 xiaozhi-math-concept-explainer）、物理化学题（转对应学科 SKILL）。
初中到高中的数学单题解题教练（高中覆盖必修与选择性必修）：学生发来一道数学题说"卡住了""这道数学题我做错了""我不知道怎么列式"时，用追问帮学生找回思路，提示按 shared/hint-ladder.md…
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: 16. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 398 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 "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. 15 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2899 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 3 example trigger phrases
- +3Description length 398: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (20 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.