BC xiaozhi-teach-resource-library
把独立教师散在文件夹、微信收藏和笔记本里的讲义、题目、讲评话术、错因案例收进一个可检索的库。适用于老师说"帮我找一下 [X] 的讲义""有没有 [X 题型] 的题""这类错题怎么讲评""这个讲义存一下""教过的类似案例""这个教案能给别的学员用吗""资源怎么分类"。流程：入库时打标签与版权状态 → 按知识点/难度检索 → 改编适配后复用 → 记录用过几次、效果如何。本 SKILL 不出题、不备课、不批改、不联系家长——只管资源的存、找、改；AI 生成的题必须老师验算后才算入库。
把独立教师散在文件夹、微信收藏和笔记本里的讲义、题目、讲评话术、错因案例收进一个可检索的库。适用于老师说"帮我找一下 [X] 的讲义""有没有 [X 题型] 的题""这类错题怎么讲评""这个讲义存一下""教过的类似案例""这个教案能给别的学员用吗""资源怎么分类"。流程：入库时打标签与版权状态 →…
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 241 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. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2775 tokens
- 100Running it twice. No mutating operations
- low 16 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 241: enough signal without eating the budget
- +4Structure: 37 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (21 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.