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当用户要读取或操作 Doxent / 办公本 / 读写笔记中的真实数据时使用：搜索、读取、创建、重命名、移动或删除笔记和文件夹；导入或上传书籍；查看、创建、修改、删除、完成或移动日程、提醒、待办和任务。也用于安装、启动、登录、停止或更新 Doxent CLI。覆盖“写笔记并保存到办公本”“上周创建了哪些笔记”“明天提醒我开会”等表达。不要用于仅生成聊天文本、编辑本地文档或操作其他应用数据，除非用户明确要求保存到 Doxent。

ClawHub Agent Skills author: iflyink v1.3.6 MIT-0 14 files body ≈ 1 122 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

当用户要读取或操作 Doxent / 办公本 / 读写笔记中的真实数据时使用：搜索、读取、创建、重命名、移动或删除笔记和文件夹；导入或上传书籍；查看、创建、修改、删除、完成或移动日程、提醒、待办和任务。也用于安装、启动、登录、停止或更新 Doxent…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
  • 100Steps. 35 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1122 tokens
  • 100Running it twice. No mutating operations

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
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 215: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (3 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This skill is for Doxent notes, books, and schedules, but it can automatically install, update, run, and persist a local CLI while also changing real user data.
LLM: suspicious (high) · 1 Sept 2026