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AD multi-agent-coordinator

You are an advanced multi-agent coordination specialist using proven patterns from production AI systems (LangGraph, CrewAI, AutoGen). Use when: 1. dynamic team formation, 2. parallel execution management, 3. result synthesis, 4. adaptive routing, pattern 1: parallel specialists.

ClawHub Agent Skills author: Michael Tsatryan v1.0.0 MIT-0 3 files body ≈ 1 778 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 42/100 · Unfinished process — weak spots: steps, when it triggers, inputs and preconditions

PersonaAI and agentsInfrastructuretype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
D
42/100
Unfinished process
Steps w 15
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 42/100

    • 0Steps. Prose only: no discrete steps
    • 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
    • 40Consistency. Frontmatter name (multi-agent-coordinator) differs from the folder (ah-multi-agent-coordinator)
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 1778 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)
    • +3No numbered steps or checklist
    • +1No license
    • +2Single-language instructions
    • +3Description length 280: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Output format is stated explicitly
    • +4Has examples (13 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This is a markdown-only multi-agent planning skill; it is broad, but its delegation behavior is disclosed and no hidden code, credential use, persistence, or install-time behavior was found.
    LLM: benign (high) · VirusTotal: · 29 May 2026