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Route tasks to the best AI model across paid subscriptions (Claude, ChatGPT, Codex, Gemini, Kimi) via OpenClaw gateway. Use when user mentions model routing, multi-model setup, "use Codex for this", "delegate to Gemini", "route to the best model", agent delegation, or has OpenClaw agents configured with multiple providers. Do NOT use for single-model conversations or general chat.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 3 565 tokens Open the sourcegithub.com↗ analyzed 26 h ago

Route tasks to the best AI model across paid subscriptions (Claude, ChatGPT, Codex, Gemini, Kimi) via OpenClaw gateway.

As a process B 67/100 · Nearly there — weak spots: inputs and preconditions, running it twice

IntegrationAI 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
100/100
safety, quality, tests
Safety 60%
100
Quality 40%
99
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
When it triggers w 12
50
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

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 67/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 44 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3565 tokens
    • 100Progress reporting. Reports progress
    • low 15 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

    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 383: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 44 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 99.