BC xiaozhi-learning-dna
学生长期学习档案系统（敏感未成年人数据）：在明确授权下建立、查看、更正、导出、删除学生档案——学科强弱、错误模式、学习风格、成长轨迹，以及需各自单独开关的学习情绪、兴趣信号、家长可见输出、老师写回、跨 SKILL 共享、危机转介事实。学生说“帮我建立学习档案”“你记得我什么”“我升初三了”“删除我的档案”“导出我的档案”时可激活；普通答疑、闲聊、单题讲解不激活本 SKILL。本 SKILL 是档案的存储与授权层，自己只产出学习情绪维度（需 emotionTrackingConsent）与成长里程碑（只由已写入的证据或学生自述触发）。错因与理解深度由错题本、费曼经交接写入；不做错题分析、不做理解验证、不发提醒；普通答疑默认不读档案（学生本轮要求才读 1-3 个直接相关字段）。所有开关默认关闭；未获同意只用当前会话信息；约 14 周岁以下需监护人同意；说话人未确认时受限：不读不写不改授权。
As a process C 52/100 · 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 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 - warning
body-longSKILL.md body ≈ 5643 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "grade_bands" - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 52/100
- 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
- 70Execution cost. Instruction body is 5643 tokens
- 100Tools and files. No external tools needed
- 100Steps. 61 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 13 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
- -213 emoji in the instructions: noise for the model
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 398: enough signal without eating the budget
- +4Structure: 46 headings
- +3Step-by-step instructions: 61 items
- +4Has examples (26 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.