BF shimo-export
石墨文档导出 AI Skill — 通过 AI Agent 与石墨文档 (shimo.im) API 交互, 实现自动登录、文件列表浏览、团队空间扫描、批量导出(支持 Markdown、PDF、Word、Excel、PPT、XMind、图片等格式)。 当用户提到石墨文档、导出文件、下载文档、批量导出、团队空间、文件列表时,使用此 skill。 即使用户没有明确说"石墨",只要意图涉及从 shimo.im 导出或浏览文档,也应触发此 skill。 Shimo Document Export AI Skill — Enables AI agents to interact with shimo.im API for automated login, file browsing, team space scanning, and batch export in multiple formats (md, pdf, docx, xlsx, pptx, xmind, jpg).
As a process F 35/100 · Will not run — References files that are not bundled: references/api.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 2. 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
missing-refreference to a missing file: references/api.md - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 35/100
- 0Tools and files. 1 referenced file(s) missing: references/api.md
- 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
- 100Steps. 44 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1645 tokens
- 100Running it twice. No mutating operations
- low The response is described with custom markup (16 tags): a typed call is more reliable
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
- +1No license
- +2Single-language instructions
- +3Description length 441: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 44 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.