SKILLEMALL.ai

AB multi-agent-builder

Build a reusable multi-agent team in OpenClaw from a user goal (e.g., "create a product-engineering team", "build a marketing ops team"). Use when the user wants role analysis, role confirmation, agent-by-agent creation plan, collaboration protocol, handoff flow, and channel-binding checklist. Mirror the user's language (English/Chinese/other) throughout the interaction and outputs.

ClawHub Agent Skills author: gzgogo v1.0.0 MIT-0 28 files body ≈ 1 828 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
B
69/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 28. 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 69/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 87 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1828 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +4No input/output examples
    • -33 of 4 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 385: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 87 items
    • +4Reference files are cited in the instructions (21 of 21)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This skill has a legitimate team-building purpose, but it can make persistent OpenClaw configuration changes and install optional dependencies with too little per-change user control.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026