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    Constraint Negotiator

    2

    Expose hidden trade-offs and architect feasible operating envelopes for systems under conflicting pressures.

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    Constraint Negotiator

    Constraint Negotiator

    Example session with this skill installed

    We need to build a RAG-based search tool. It must be 100% accurate, use the cheapest LLMs to save costs, and have sub-second latency, but management also wants it to cite every single source.

    • Read your context and instructions
    • Compiled the constraint negotiator

    OBJECTIVE-CONSTRAINT COLLISION MAP

    • Collision: Accuracy vs. Cost (CRITICAL)
    • Tension: Cheap models lack the reasoning for 100% accuracy in complex RAG tasks.
    • Truth: You are implicitly choosing cost over reliability.

    VERDICT

    Impossible brief disguised as ambition.

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

    About this skill

    What it does

    The Constraint Negotiator is a specialized framework for developers, architects, and product leads who are facing "impossible" briefs. It explicitly identifies the hidden tensions in complex systems—like the trade-off between latency and safety, or customization and maintainability—and forces a structured negotiation to find a feasible path forward.

    Problem it solves

    Most projects fail not due to a lack of talent, but because they are governed by incompatible demands (e.g., "fast, cheap, and secure"). This skill exposes the "negotiation debt" that teams accumulate when they pretend trade-offs don't exist, preventing the delivery of brittle, compromise-heavy solutions that satisfy no one.

    Output & Benefits

    The skill produces a detailed "Negotiation Status" report, including a Collision Map of conflicting objectives, a Dominant Constraint Diagnosis, and a Feasible Operating Envelope. Unlike simple preference matrices, it provides 2-4 viable paths with explicit sacrifices, ensuring you don't commit to something operationally unstable or mathematically impossible.

    Supported Environments

    Ideal for AI agent design, system architecture, product roadmapping, and multi-stakeholder governance. It bridges the gap between high-level ambition and operational reality.

    • Does not perform mathematical optimization (Linear Programming).
    • Requires clear initial context to identify hidden tensions.
    • Provides strategic paths rather than automated code fixes.

    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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    Listed4 months ago

    What's inside

    Frequently Asked Questions

    The Constraint Negotiator identifies 'impossible' briefs where objectives like security and speed conflict, providing a structured Collision Map to resolve these tensions before they become technical debt.

    It is designed as a platform-agnostic logic layer that integrates seamlessly with major LLM-based agents (GPT-4, Claude 3.5, etc.) via any marketplace-compatible orchestration framework.

    You receive the core logic framework, a library of negotiation templates for specific industries (e.g., FinTech vs. AI Safety), and documentation on how to output the Feasible Operating Envelope.

    Setup is instantaneous; once added to your agent's workspace, you simply input your project's conflicting variables to trigger the Dominant Constraint Diagnosis process.

    Yes, buyers receive lifetime access to version updates, including refined negotiation algorithms and new collision patterns as system architecture trends evolve.

    New in Business & Operations