SKILLEMALL.ai
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AA team-planner

This skill should be used when the user wants to plan a team of AI agents to work on a complex task. It analyzes task requirements, designs team structure, defines member roles, and plans collaboration workflows. Trigger phrases include "plan a team", "design agent roles", "how should agents collaborate", or any request for multi-agent coordination strategy.

ClawHub Agent Skills author: GhOvOst v1.0.0 MIT-0 5 files body ≈ 2 650 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process A 85/100 · Runs to the end — weak spots: running it twice, progress reporting

AnalyzerAI 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
A
85/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
Failures and branches w 10
60
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: 5. 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 85/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 60Failures and branches. 2 branches
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 126 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Result and completion. Output format and completion criterion are stated
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2650 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)
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 360: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 126 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)

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

    External checks

    ClawHub: clean
    This instruction-only skill plans multi-agent teamwork; its triggers are somewhat broad, but it does not execute code, access credentials, persist, or hide behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026