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AF clawflow

Protocol for multi-agent collaboration via OpenClaw's message-passing and recursive task DAGs. Use this skill whenever the user wants to coordinate work across multiple OpenClaw agents, decompose complex tasks into subtasks with dependencies, or build any kind of multi-agent pipeline. Also trigger when the user mentions "agent orchestration", "task DAG", "multi-agent", "dispatch", "agent pipeline", "delegate tasks", "agent collaboration", or wants to break a project into parallelisable steps handled by different agents. Use it even if the user just says "I need multiple agents to work together."

ClawHub Agent Skills author: Srikanth Srungarapu v1.0.0 7 files body ≈ 2 020 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process F 57/100 · Will not run — References files that are not bundled: references/schemas.md, references/agent-loop.md, references/coordinating.md

ProcedureAI 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
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
57/100
Will not run
References files that are not bundled: references/schemas.md, references/agent-loop.md, references/coordinating.md
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. 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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/schemas.md
  • warning missing-ref reference to a missing file: references/agent-loop.md
  • warning missing-ref reference to a missing file: references/coordinating.md
  • warning missing-ref reference to a missing file: scripts/message.py

Process rating: all ten parameters 57/100

Will not run. References files that are not bundled: references/schemas.md, references/agent-loop.md, references/coordinating.md
  • 0Tools and files. 4 referenced file(s) missing: references/schemas.md, references/agent-loop.md, references/coordinating.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 100Steps. 30 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2020 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 10 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

  • +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
  • +5Description quotes 8 example trigger phrases
  • +3Description length 602: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
Clawflow is a coherent multi-agent coordination skill, but it should be reviewed because it can recursively delegate work, persist task/message logs, and forward broad context between agents without strong built-in limits.
LLM: suspicious (high) · VirusTotal: suspicious · 27 May 2026