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BF agent-office

Agent Office：创建本地 AI 员工、office worker、AI employee 与 multi-agent office team。每个员工以独立 HTTP Worker 运行，支持 openclaw / hermes / deerflow / cli / external / stub 六种引擎，适合 office automation、agent worker 管理与团队协作。

ClawHub Agent Skills author: jast-hub v1.5.1 MIT-0 35 files · 7 scripts body ≈ 2 073 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 35/100 · Will not run — References files that are not bundled: scripts/...

IntegrationAI and agentstype 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
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: scripts/...
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 30. 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")
  • warning missing-ref reference to a missing file: scripts/...
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "requirements"
  • note frontmatter-key unknown frontmatter key "ports"
  • note frontmatter-key unknown frontmatter key "directories"
  • note frontmatter-key unknown frontmatter key "daemon"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: scripts/...
  • 0Tools and files. 1 referenced file(s) missing: scripts/...
  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 100Steps. 76 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2073 tokens
  • 100Progress reporting. Reports progress
  • low 12 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

  • +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
  • +1No license
  • +2Single-language instructions
  • +3Description length 202: enough signal without eating the budget
  • +4Structure: 36 headings
  • +3Step-by-step instructions: 76 items
  • +4Has examples (14 code blocks)
  • +3All 12 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
The skill largely does what it advertises, but it can create persistent local AI workers that run commands, install remote runtime code, store task summaries, and forward task context to other services.
LLM: suspicious (high) · VirusTotal: · 29 May 2026