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完全自主的AI公司运营系统 - 7×24小时自动化发现需求、设计、开发、销售、运维，实现盈利的轻量级解决方案

ClawHub Agent Skills author: sendwealth v0.1.1 MIT-0 13 files body ≈ 2 220 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 33/100 · Will not run — References files that are not bundled: LICENSE

ProcedureGitHubCustomer supporttype 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
81/100
safety, quality, tests
Safety 60%
92
Quality 40%
65
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: LICENSE
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 · 8

✓ No critical or high findings

Medium and low: 8
  • low Exfiltration read-dotenv examples/init_ai_company.py:177
    Reads a .env file (test fixture / example file; quoted — discussed, not commanded)
    cp .env.example .env
    fixturequoted
  • low Exfiltration read-dotenv examples/init_ai_company.py:220
    Reads a .env file (test fixture / example file; quoted — discussed, not commanded)
    print(f"   2. cp .env.example .env")
    fixturequoted
  • low Exfiltration read-dotenv examples/QUICKSTART.md:32
    Reads a .env file (test fixture / example file)
    cp .env.example .env
    fixture
  • low Exfiltration read-dotenv examples/README.md:17
    Reads a .env file (test fixture / example file)
    cp .env.example .env
    fixture
  • low Exfiltration read-dotenv README.md:67
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv SKILL.md:201
    Reads a .env file
    cp .env.example .env
  • low Dangerous commands cmd-cron-mention SKILL.md:229
    Mentions editing / listing crontab
    crontab -e
  • low Exfiltration exfil-webhook-url SKILL.md:552
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    webhook_url: "https://hooks.slack.com/..."
    placeholder

Files scanned: 13. 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: LICENSE

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: LICENSE
  • 0Tools and files. 1 referenced file(s) missing: LICENSE
  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 100Steps. 65 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2220 tokens
  • low 16 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)
  • +3Description length 54: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Structure: 61 headings
  • +3Step-by-step instructions: 65 items
  • +4Has examples (29 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
This is a coherent automation scaffold, but it asks users to wire up credentials, scheduled jobs, deployment, email, and social posting without enough safety boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026