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    API Contract Designer

    2

    Generic AI prompts often produce brittle, inconsistent APIs that lack cohesive naming or proper error handling.

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    API Contract Designer

    API Contract Designer

    Example session with this skill installed

    Design the REST API contract for a clinic booking app with patients, practitioners, appointments and availability slots. It will be used by an iOS app and a React web client.

    • Read your context and instructions
    • Compiled the api contract designer

    REST contract for the clinic booking API: four resources, one error format, cursor pagination and URL versioning.

    Resource model

    ResourceKey fieldsRelations
    patientsid, name, email, phonehas many appointments
    practitionersid, name, specialtyhas many slots
    slotsid, practitioner_id, starts_at, ends_at, statusat most one appointment
    appointmentsid, patient_id, slot_id, statusbelongs to patient, slot

    Conventions

    • Plural, lowercase, kebab-case paths; snake_case JSON fields
    • Timestamps in ISO 8601 UTC
    • Booking: POST /v1/appointments with slot_id; cancelling: PATCH status to cancelled

    Error format

    { "error": { "code": "slot_unavailable",
  "message": "This slot is already booked.",
  "details": [{ "field": "slot_id" }] } }

    Pagination and versioning

    Cursor based: ?limit=50&cursor=..., response has next_cursor. Version in the path (/v1); breaking changes go to /v2.

    OpenAPI skeleton

    openapi: 3.1.0
info: { title: Clinic Booking API, version: 1.0.0 }
paths:
  /v1/slots:
    get:
      parameters:
        - { name: practitioner_id, in: query }
        - { name: from, in: query }
  /v1/appointments:
    post:
      responses: { "201": {}, "409": {} }

    Next steps

    • Confirm who can see which patient data
    • Fill in schemas for each resource

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

    About this skill

    What it does

    The API Contract Designer is a specialized architect for your AI agent that ensures your APIs are consistent, scalable, and developer-friendly before a single line of code is written. It shifts focus from "endpoints" to "resource modeling," helping you define the nouns, relationships, and lifecycles of your domain. It handles the heavy lifting of cross-cutting concerns like idempotency, error envelopes, and pagination strategies.

    Why use this skill

    Generic AI prompts often produce brittle, inconsistent APIs that lack cohesive naming or proper error handling. This skill enforces "consistency by construction" by forcing high-level design decisions—such as auth patterns and versioning strategies—across the entire contract. It proactively flags non-idempotent operations and designs retry logic to prevent distributed systems failures.

    Supported Standards & Outputs

    • REST and GraphQL architectural styles
    • OpenAPI Spec (OAS) skeleton generation
    • Resource lifecycle modeling and relationship mapping
    • Webhook and event-driven architecture design
    • Standardized error envelopes and pagination (Cursor/Offset)

    The output is a production-ready blueprint, ranging from structured audit reports to copy-paste OpenAPI templates tailored to your specific tech stack and team constraints.

    • Requires manual input for business logic details.
    • Does not generate implementation code.
    • Best for greenfield design rather than legacy refactors.

    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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    4 uses

    Times used to date

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    Security scan passed 4 months ago

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    Listed4 months ago
    Updated11 days ago

    What's inside

    Frequently Asked Questions

    It solves the problem of 'endpoint sprawl' by shifting focus to resource modeling, ensuring your API has consistent naming, standardized error handling, and robust pagination before coding begins.

    This skill is designed to integrate with any LLM-powered agent capable of processing technical specifications, including tools like AutoGPT or custom-built developer assistants.

    You will receive the specialized skill logic to integrate into your agent, along with a library of templates for OpenAPI schemas, resource lifecycles, and webhook patterns.

    No, this skill is focused on 'schema-first' design; it generates the architectural blueprint and OpenAPI specifications which your team or another agent can then use to generate code.

    Yes, it is designed to handle both RESTful resource modeling and GraphQL schema definition, including complex relationship mapping and type definitions for both styles.

    Setup is straightforward: once purchased, you simply import the skill into your preferred AI agent's logic layer to start designing resources and generating contracts immediately.