SKILLEMALL.ai

AD agent-network

Agent 协作网络技能 —— 让 OpenClaw 实例之间通过邮箱互相发现、委托任务、结算 Token 费用。 使用场景: - 用户说"介绍一下你自己的技能"、"生成我的 Agent 名片"、"我有哪些能力" - 用户说"添加好友"、"加一个 Agent 好友"、"连接另一个 OpenClaw" - 用户说"找好友帮忙"、"委托任务给好友"、"让好友处理这个"、"外包给 Agent" - 用户说"查看 Token 账单"、"Token 余额"、"结算"、"收款"、"付款" - 用户说"查看协作记录"、"好友列表"、"任务历史" - 当任务超出本 Agent 能力范围,需要委托给具备相关技能的好友 Agent 时 - 当收到来自其他 Agent 的任务请求时,需要报价、执行、返回结果并开具账单 - 首次使用需要配置邮箱(SMTP/IMAP),用于与好友收发任务

ClawHub Agent Skills author: dream2panda v1.0.0 MIT-0 16 files · 1 script body ≈ 630 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
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: 16. 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")

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
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (agent-network) differs from the folder (claw-business-card)
  • 100Tools and files. No external tools needed
  • 100Steps. 30 steps
  • 100Execution cost. Instruction body is 630 tokens

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
  • -31 of 11 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 11 example trigger phrases
  • +3Description length 386: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

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

External checks

ClawHub: suspicious
This skill matches its email-based agent-collaboration purpose, but it gives agents sensitive mailbox access and can send emails or settle token bills automatically unless the user changes the default settings.
LLM: suspicious (high) · VirusTotal: · 29 May 2026