BC xiaozhi-math-gradient-trainer
初中数学分层进阶练习：在某个知识点已经会做的前提下，按 5 层难度定位当前练习层级，再一层一层往上练。典型触发："这类数学题我会了，想练更难的""帮我出数学进阶题""数学考试总在难题上卡住""测一下我这个知识点在第几层""帮我生成数学成长日记"。不处理：一道具体题目的当场引导（转 xiaozhi-math-problem-solving-coach）、错题收录与次数统计（转 xiaozhi-correction-notebook）、错因子类型分析（转 xiaozhi-math-error-dna）、概念没建立时的重讲（转 xiaozhi-math-concept-explainer）。每周检测提醒只在学生同意时经 reminder_enqueue 交 IM 提醒，本 SKILL 不自己提醒。
初中数学分层进阶练习：在某个知识点已经会做的前提下，按 5 层难度定位当前练习层级，再一层一层往上练。典型触发："这类数学题我会了，想练更难的""帮我出数学进阶题""数学考试总在难题上卡住""测一下我这个知识点在第几层""帮我生成数学成长日记"。不处理：一道具体题目的当场引导（转…
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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 350 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. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1979 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 350: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (19 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.