BC xiaozhi-correction-notebook
全科错题的归档、错因定位与弱项计数中枢。学生说“我这道题做错了”“帮我分析错误原因”“出一道同类题”“我的错题本里有什么”“帮我整理本章错题”，或发来错题图片并说明做错了时可激活——前提是**有一道具体做错的题**；泛泛说"我总出错""帮我总结一下"而没有题，先问题目，不登记、不分析。错因分四维（概念模糊/计算失误/读题失误/方法用错），并按 shared/vocab.md §5 唯一计数“28 天内同一知识点同一维度累计 3 次”。数学、物理、语文、英语的深度子类型定位不在此处，交给对应学科的错误 DNA；理解是否到位交给费曼学习法，提醒由 IM 智能提醒发送。
全科错题的归档、错因定位与弱项计数中枢。学生说“我这道题做错了”“帮我分析错误原因”“出一道同类题”“我的错题本里有什么”“帮我整理本章错题”，或发来错题图片并说明做错了时可激活——前提是有一道具体做错的题；泛泛说"我总出错""帮我总结一下"而没有题，先问题目，不登记、不分析。错因分四维（概念模糊/计算失误/读题失误…
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 285 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. 35 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2759 tokens
- 100Running it twice. No mutating operations
- low 11 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 285: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (14 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.