skills/codex/composio-sdk/SKILL.md
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: composio-sdk description: Build AI agents and apps with Composio - access 200+ external tools with Tool Router or direct execution --- # Composio Comprehensive guide to building AI agents and applications with Composio. Choose between: - **Tool Router** - Create isolated, secure MCP sessions for AI agents with automatic authentication - **Direct Execution** - Build traditional apps with manual tool execution and CRUD operation
npx skillsauth add frank-luongt/faos-skills-marketplace skills/codex/composio-sdkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Comprehensive guide to building AI agents and applications with Composio. Choose between:
Use this skill when:
Building AI Agents:
Building Traditional Applications:
Use Tool Router to build interactive chat-based agents or autonomous long-running task agents. Tool Router creates isolated MCP sessions for users with scoped access to toolkits and tools.
Key Features:
Essential patterns for creating agent sessions and configuring tools:
Authentication patterns for seamless user experiences:
Build connection UIs and check toolkit states:
Real-time event handling and webhook integration patterns:
Use Composio for traditional applications where tools are executed manually without agent frameworks. This approach gives you full control over tool execution, authentication, and resource management.
Key Capabilities:
Fundamental patterns for fetching and executing tools:
Manage authentication and connections programmatically:
Extend Composio with custom tools and behavior:
Build reactive applications with triggers (shared with agents):
Manage user context and multi-tenant isolation:
import { Composio } from '@composio/core';
const composio = new Composio();
// Create a session with Gmail tools
const session = await composio.create('user_123', {
toolkits: ['gmail'],
manageConnections: true
});
// Use MCP URL with any AI framework
console.log('MCP URL:', session.mcp.url);
import { Composio } from '@composio/core';
const composio = new Composio({
apiKey: 'your-api-key',
toolkitVersions: { github: '12082025_00' }
});
// Fetch tools
const tools = await composio.tools.get('user_123', {
toolkits: ['github']
});
// Execute a tool
const result = await composio.tools.execute('GITHUB_GET_REPO', {
userId: 'user_123',
arguments: { owner: 'composio', repo: 'sdk' },
});
console.log(result.data);
Tool Router (Agents):
Direct Execution (Apps):
Shared:
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-mlflow-evaluation --- # MLflow 3 GenAI Evaluation ## Before Writing Any Code 1. **Read GOTCHAS.md** - 15+ common mistakes that cause failures 2. **Read CRITICAL-interfaces.md** - Exact API signatures and data schemas ## End-to-End Workflows Follow these workflows based on your goal. Each step indicates which reference files to read. ### Workflow 1: First-Time Evaluation Setup For users new to MLflow GenAI evalu
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-lakebase-provisioned --- # Lakebase Provisioned Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads. ## When to Use Use this skill when: - Building applications that need a PostgreSQL database for transactional workloads - Adding persistent state to Databricks Apps - Implementing reverse ETL from Delta Lake to an operational database - Storing chat/agent m
tools
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-jobs --- # Databricks Lakeflow Jobs ## Overview Databricks Jobs orchestrate data workflows with multi-task DAGs, flexible triggers, and comprehensive monitoring. Jobs support diverse task types and can be managed via Python SDK, CLI, or Asset Bundles. ## Reference Files | Use Case | Reference File | | ----------------------
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-genie --- # Databricks Genie Create and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration. ## Overview Genie Spaces allow users to ask natural language questions about structured data in Unity Catalog. The system translates questions into SQL queries, executes them on a SQL warehouse, and presents results conversationally. ## When to Use This Skill Use this skill when: -