Subagent Orchestration

    3

    Intelligently delegate tasks to Claude, Codex, or Gemini based on cost, model strengths, and rate limits.

    $15

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    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    subagent-orchestration

    Example session with this skill installed

    Run a cross-check on my refactor in main.js across all models to catch potential logic errors or optimization gaps.

    • Read your context and instructions
    • Compiled the subagent-orchestration

    [Claude]: Logic looks sound, but check the overflow on line 42.
    [Codex]: LGTM. I'd suggest a try-catch block here.
    [Gemini]: Optimization tip: use a map instead of a nested loop for O(n) complexity.
    Analysis: 2/3 models suggest error handling improvements.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Smart Multi-Model Routing & Delegation

    Subagent Orchestration is a high-level routing skill designed for developers who use multiple AI models (Claude, GPT/Codex, and Gemini) and want to optimize for cost, performance, and context window limitations. Instead of manually switching browser tabs or CLI tools, this skill allows your primary agent to intelligently delegate sub-tasks to the best-fitting model for the job.

    How it works

    The skill acts as an intelligent traffic controller. It analyzes your request and routes it to specific vendor CLIs based on task strengths: Claude for precise code refactoring, Gemini for massive context ingestion (up to 1M+ tokens), or Codex for web-integrated research. It handles the syntax differences between each model's CLI, enabling seamless cross-model execution.

    Why use this skill?

    • Cost Management: Automatically route lightweight formatting or summary tasks to cheaper models like Gemini Flash.
    • Rate Limit Resilience: If Claude is rate-limited, the skill can automatically failover to Gemini or Codex to keep your workflow moving.
    • Cross-Model Verification: Run the same security or logic check across all three models simultaneously to find "blind spots" through a side-by-side comparison table.
    • Context Optimization: Automatically detects when a prompt exceeds standard context limits and routes it to the large-window models.

    Supported Integration

    The skill leverages your existing local environment, supporting official CLIs for Claude, Codex/ChatGPT, and Gemini. It outputs clean, prefixed text for single runs or structured Markdown tables for cross-model comparisons.

    • Requires manual CLI auth for each vendor.
    • Blocking execution (no real-time streaming).
    • Heuristic-based routing rather than ML-optimized selection.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed6 months ago

    What's inside

    Frequently Asked Questions

    Subagent Orchestration solves the 'single-model bottleneck' by intelligently routing tasks to the model best suited for the specific job, whether that's Claude for coding, Gemini for huge datasets, or Codex for research—all while optimizing for cost and rate limits.

    The skill requires you to have the official CLIs for Anthropic (Claude), OpenAI (Codex/GPT), and Google (Gemini) already installed and authenticated on your local machine; it acts as the orchestration layer between them.

    No, this skill uses your local CLI credentials, so you are only charged by the AI providers based on your actual usage at their standard API/CLI rates.

    Yes, you can enable a cross-model verification mode that submits the same prompt to all three models simultaneously and generates a Markdown table comparing their outputs side-by-side.

    The skill includes a failover mechanism that detects rate-limit errors (like 429 status codes) and automatically re-routes the pending task to the next best available model to prevent workflow interruptions.

    Your purchase includes the core orchestration skill, a configuration guide for linking your CLIs, and lifetime access to any logic updates as model capabilities and CLI syntaxes evolve.

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