SKILLEMALL.ai

AC multi-agent-comm

Multi-Agent Communication Protocol — 通用多智能体通信框架。用于在 OpenClaw 中编排多个 Agent 之间的结构化通信、任务委派和协同工作。适用场景:(1) 在主 Agent 与子 Agent 之间传递消息 (2) 多个独立 Agent(如 QClaw、学术助手、学生工作助理等)之间的双向通信 (3) 将大任务分解为并行子任务并收集结果 (4) 跨 Agent 共享上下文和记忆。关键词:agent communication, ACP, multi-agent, subagent, session spawn, agent 间通信, 多智能体协同, 任务委派。

ClawHub Agent Skills author: Zhenbin Huang v1.0.1 MIT-0 3 files body ≈ 745 tokens Open the sourceclawhub.ai analyzed 35 h ago

Multi-Agent Communication Protocol — 通用多智能体通信框架。用于在 OpenClaw 中编排多个 Agent 之间的结构化通信、任务委派和协同工作。适用场景:(1) 在主 Agent 与子 Agent 之间传递消息 (2) 多个独立 Agent(如…

As a process C 53/100 · Has gaps — 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
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

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: 3. 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 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. 13 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 745 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 305: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a documentation-only multi-agent communication skill whose session, agent, and setup guidance is aligned with its stated purpose, though users should handle resumed sessions and API keys carefully.
LLM: benign (high) · VirusTotal: · 23 Jun 2026