BC mybooks
MyBooks是个人书库管理系统，提供电子书及实体书管理，包括存储、分类、搜索和元数据管理功能。你可以帮助用户：查询书库统计信息和阅读统计,搜索/浏览书籍,获取书籍详情,更新书籍元数据（书名、作者、标签、分类、简介等）,自动联网填充书籍信息,发送书籍到邮箱或阅读器设备,上传电子书或通过ISBN添加实体书,管理阅读状态（想读/在读/已读/收藏）,查询/手动更新某本书分格式的阅读时长与进度,查看作者信息和分类信息,导入第三方阅读App的划线与想法（如微信读书，需配合微信读书 skill 读取原始数据）,以及MiMo TTS有声书功能（配置TTS API、EPUB转有声书、查询转换进度、克隆音色与语音提示词管理，需管理员权限）等
MyBooks是个人书库管理系统，提供电子书及实体书管理，包括存储、分类、搜索和元数据管理功能。你可以帮助用户：查询书库统计信息和阅读统计…
As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 8151 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 55/100
- 0Result and completion. Does not say what the result is
- 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
- 30Running it twice. 16 mutating operations with no state check
- 40Execution cost. Instruction body is 8151 tokens: crowds the task out of the window
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 35 steps
- 100Consistency. Name and required fields are in place
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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- -292 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 315: enough signal without eating the budget
- +4Structure: 52 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (77 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.