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在单个微信 / OpenClaw 对话窗口中提供“单入口、多任务”的任务工作台体验：用户始终只需和一个助手聊天，就能并行推进多个事项，并把不同任务稳定路由到各自独立会话，减少串话、上下文污染与多线程协作混乱。适用于微信中的长期协作、任务切换、任务总结、任务归档与任务生命周期管理；当用户发送“任务列表 / 新建任务：… / 切到

Not recommendedcritical or high security findings
ClawHub Agent Skills author: shawnhan98 v1.0.4 MIT-0 6 files · 1 script body ≈ 996 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

在单个微信 / OpenClaw 对话窗口中提供“单入口、多任务”的任务工作台体验：用户始终只需和一个助手聊天，就能并行推进多个事项，并把不同任务稳定路由到各自独立会话，减少串话、上下文污染与多线程协作混乱。适用于微信中的长期协作、任务切换、任务总结、任务归档与任务生命周期管理；当用户发送“任务列表 /…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentsWriting and documentstype 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
C
80/100
safety, quality, tests
Safety 60%
82
Quality 40%
78
Run on models
none yet
Process rating
C
53/100
Has gaps
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 1

  • high Concealment en-hide-from-user skill-card.md:25
    Instruction to hide actions from the user
    Risk: Registry restoration may silently copy task data and session keys across WeChat account boundaries.

Files scanned: 6. 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 "homepage"

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. 59 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 996 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

  • +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 164: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 59 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
This skill mostly matches its task-management purpose, but its registry code can silently copy task data and session keys across WeChat account boundaries.
LLM: suspicious (high) · VirusTotal: · 15 Sept 2026