open-agent-sdk-typescript

Q: How do I install open-agent-sdk-typescript?

Run npx skills add https://github.com/reason-machines/ai-agent-skills --skill open-agent-sdk-typescript in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/open-agent-sdk-typescript/ (personal) or .claude/skills/open-agent-sdk-typescript/ (project).

by reason-machinesAI & Agents

Build AI agents with in-process agent loops using Anthropic or OpenAI APIs, custom tools, MCP servers, and multi-turn conversations

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/ai-agent-skills --skill open-agent-sdk-typescript

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads open-agent-sdk-typescript automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Open Agent SDK (TypeScript)

Skill by ara.so — AI Agent Skills collection.

Open Agent SDK is a TypeScript library that runs full AI agent loops in-process without CLI dependencies or subprocesses. It supports both Anthropic and OpenAI-compatible APIs, provides 35+ built-in tools, MCP server integration, custom tool creation, skills system, subagents, and lifecycle hooks. Deploy anywhere: cloud, serverless, Docker, or CI/CD.

Installation

npm install @codeany/open-agent-sdk

Set your API key as an environment variable:

export CODEANY_API_KEY=your-api-key-here

For OpenAI-compatible models:

export CODEANY_API_TYPE=openai-completions
export CODEANY_API_KEY=sk-your-key
export CODEANY_BASE_URL=https://api.openai.com/v1
export CODEANY_MODEL=gpt-4o

For third-party Anthropic-compatible providers:

export CODEANY_BASE_URL=https://openrouter.ai/api
export CODEANY_API_KEY=sk-or-your-key
export CODEANY_MODEL=anthropic/claude-sonnet-4

Core Concepts

API Types

The SDK supports two API types:

anthropic-messages: Anthropic Claude models (default)
openai-completions: OpenAI, DeepSeek, Qwen, Mistral, or any OpenAI-compatible API

API type is auto-detected from model name. Models containing gpt-, o1, o3, deepseek, qwen, or mistral automatically use openai-completions.

Agent vs Query

query(): One-shot streaming query, no session persistence
createAgent(): Reusable agent with multi-turn conversation history

Quick Start Examples

One-Shot Streaming Query

import { query } from "@codeany/open-agent-sdk";

for await (const message of query({
  prompt: "Read package.json and tell me the project name.",
  options: {
    allowedTools: ["Read", "Glob"],
    permissionMode: "bypassPermissions",
  },
})) {
  if (message.type === "assistant") {
    for (const block of message.message.content) {
      if ("text" in block) {
        console.log(block.text);
      }
    }
  }
  
  if (message.type === "result") {
    console.log(`Cost: $${message.total_cost_usd?.toFixed(4)}`);
    console.log(`Turns: ${message.num_turns}`);
  }
}

Simple Blocking Prompt

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent({ model: "claude-sonnet-4-6" });
const result = await agent.prompt("What files are in this project?");

console.log(result.text);
console.log(`Turns: ${result.num_turns}`);
console.log(`Tokens: ${result.usage.input_tokens + result.usage.output_tokens}`);

OpenAI / GPT Models

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent({
  apiType: "openai-completions",
  model: "gpt-4o",
  apiKey: process.env.OPENAI_API_KEY,
  baseURL: "https://api.openai.com/v1",
});

const result = await agent.prompt("Analyze the code structure of this project");
console.log(result.text);

Multi-Turn Conversation

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent({ maxTurns: 5 });

const r1 = await agent.prompt(
  'Create a file /tmp/hello.txt with "Hello World"'
);
console.log("Response 1:", r1.text);

const r2 = await agent.prompt("Read back the file you just created");
console.log("Response 2:", r2.text);

const r3 = await agent.prompt("Delete the file");
console.log("Response 3:", r3.text);

console.log(`Total messages in session: ${agent.getMessages().length}`);

// Clean up
await agent.close();

Custom Tools

Using Zod Schema (Recommended)

import { z } from "zod";
import { query, tool, createSdkMcpServer } from "@codeany/open-agent-sdk";

const getWeather = tool(
  "get_weather",
  "Get the current weather for a city",
  {
    city: z.string().describe("City name"),
    unit: z.enum(["celsius", "fahrenheit"]).optional().describe("Temperature unit"),
  },
  async ({ city, unit = "celsius" }) => {
    // Simulate API call
    const temp = unit === "celsius" ? 22 : 72;
    return {
      content: [
        {
          type: "text",
          text: `Weather in ${city}: ${temp}°${unit === "celsius" ? "C" : "F"}, sunny`,
        },
      ],
    };
  }
);

const calculator = tool(
  "calculate",
  "Perform mathematical calculations",
  {
    expression: z.string().describe("Mathematical expression to evaluate"),
  },
  async ({ expression }) => {
    try {
      const result = Function(`'use strict'; return (${expression})`)();
      return {
        content: [{ type: "text", text: `${expression} = ${result}` }],
      };
    } catch (error) {
      return {
        content: [{ type: "text", text: `Error: ${error.message}` }],
        isError: true,
      };
    }
  }
);

const server = createSdkMcpServer({
  name: "custom-tools",
  tools: [getWeather, calculator],
});

for await (const msg of query({
  prompt: "What's the weather in Tokyo? Also calculate 2**16.",
  options: { mcpServers: { "custom-tools": server } },
})) {
  if (msg.type === "assistant") {
    for (const block of msg.message.content) {
      if ("text" in block) console.log(block.text);
    }
  }
}

Low-Level Tool Definition

import { createAgent, getAllBaseTools, defineTool } from "@codeany/open-agent-sdk";

const databaseQuery = defineTool({
  name: "DatabaseQuery",
  description: "Execute SQL queries against the database",
  inputSchema: {
    type: "object",
    properties: {
      query: {
        type: "string",
        description: "SQL query to execute",
      },
      readonly: {
        type: "boolean",
        description: "Whether this is a read-only query",
      },
    },
    required: ["query"],
  },
  isReadOnly: false,
  async call(input) {
    // Validate read-only
    if (!input.readonly && /^\s*(SELECT|SHOW|DESCRIBE)/i.test(input.query)) {
      return "Error: Use readonly=true for SELECT queries";
    }
    
    // Execute query (simulated)
    return JSON.stringify({
      rows: [{ id: 1, name: "Example" }],
      rowCount: 1,
    });
  },
});

const agent = createAgent({
  tools: [...getAllBaseTools(), databaseQuery],
});

const result = await agent.prompt(
  "Query the users table and show me all records"
);
console.log(result.text);

Built-in Tools

The SDK includes 35+ built-in tools. Common ones include:

File operations: Read, Write, Edit, Delete, Move, Rename
Search: Glob, Grep, Search
Git: GitStatus, GitDiff, GitLog, GitCommit, GitCheckout
Analysis: Lint, Symbols, CodeGraph, Dependencies
Shell: Bash, BashSession
Utility: Ask, Attempt, Skill, Agent (subagents)

Restricting Tools

import { createAgent } from "@codeany/open-agent-sdk";

// Read-only agent
const readOnlyAgent = createAgent({
  allowedTools: ["Read", "Glob", "Grep", "Search"],
  permissionMode: "dontAsk",
});

// Agent without shell access
const noShellAgent = createAgent({
  disallowedTools: ["Bash", "BashSession"],
});

// Minimal tool set
const minimalAgent = createAgent({
  tools: [], // No tools at all
});

Skills

Skills are reusable prompt templates. Five built-in skills: simplify, commit, review, debug, test.

Using Built-in Skills

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent();

// The agent can invoke skills via the Skill tool
const result = await agent.prompt(
  'Use the "review" skill to review src/index.ts'
);
console.log(result.text);

Creating Custom Skills

import { registerSkill, getAllSkills, createAgent } from "@codeany/open-agent-sdk";

registerSkill({
  name: "explain",
  description: "Explain a concept in simple terms",
  userInvocable: true,
  async getPrompt(args) {
    return [
      {
        type: "text",
        text: `Explain in simple terms: ${args || "Ask what to explain."}`,
      },
    ];
  },
});

registerSkill({
  name: "optimize",
  description: "Optimize code for performance",
  userInvocable: true,
  async getPrompt(args) {
    return [
      {
        type: "text",
        text: `Analyze and optimize the following for performance:\n${args}\n\nProvide specific improvements and benchmarks.`,
      },
    ];
  },
});

console.log(`${getAllSkills().length} skills registered`);

const agent = createAgent();
const result = await agent.prompt(
  'Use the "optimize" skill on src/heavy-computation.ts'
);
console.log(result.text);

MCP Server Integration

External MCP Servers

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent({
  mcpServers: {
    filesystem: {
      command: "npx",
      args: ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"],
    },
    postgres: {
      command: "npx",
      args: ["-y", "@modelcontextprotocol/server-postgres"],
      env: {
        DATABASE_URL: process.env.DATABASE_URL,
      },
    },
  },
});

const result = await agent.prompt("List files in /tmp and query the database");
console.log(result.text);

await agent.close(); // Important: closes MCP connections

In-Process MCP Servers

import { z } from "zod";
import { createAgent, tool, createSdkMcpServer } from "@codeany/open-agent-sdk";

const httpGet = tool(
  "http_get",
  "Make HTTP GET requests",
  {
    url: z.string().url().describe("URL to fetch"),
    headers: z.record(z.string()).optional().describe("HTTP headers"),
  },
  async ({ url, headers }) => {
    const response = await fetch(url, { headers });
    const text = await response.text();
    return {
      content: [
        {
          type: "text",
          text: `Status: ${response.status}\n\n${text}`,
        },
      ],
    };
  }
);

const mcpServer = createSdkMcpServer({
  name: "http-tools",
  tools: [httpGet],
});

const agent = createAgent({
  mcpServers: {
    http: mcpServer,
  },
});

const result = await agent.prompt("Fetch https://api.github.com/repos/codeany-ai/open-agent-sdk-typescript");
console.log(result.text);

Subagents

Subagents are specialized agents with restricted tools and custom prompts.

import { query } from "@codeany/open-agent-sdk";

for await (const msg of query({
  prompt: "Use the security-reviewer to audit src/auth.ts for vulnerabilities",
  options: {
    agents: {
      "security-reviewer": {
        description: "Expert security code reviewer",
        prompt: "You are a security expert. Analyze code for vulnerabilities, focusing on authentication, authorization, input validation, and data exposure.",
        tools: ["Read", "Glob", "Grep", "Symbols"],
      },
      "performance-optimizer": {
        description: "Performance optimization specialist",
        prompt: "You optimize code for speed and efficiency. Identify bottlenecks, suggest algorithmic improvements, and recommend caching strategies.",
        tools: ["Read", "Symbols", "Dependencies"],
      },
    },
  },
})) {
  if (msg.type === "assistant") {
    for (const block of msg.message.content) {
      if ("text" in block) console.log(block.text);
    }
  }
}

Lifecycle Hooks

20 available hook events for observability and control.

import { createAgent, createHookRegistry } from "@codeany/open-agent-sdk";

const hooks = createHookRegistry({
  PreToolUse: [
    {
      handler: async (input) => {
        console.log(`[HOOK] About to use tool: ${input.toolName}`);
        console.log(`[HOOK] Arguments:`, input.toolInput);
        
        // Block dangerous operations
        if (input.toolName === "Bash" && input.toolInput.command?.includes("rm -rf")) {
          console.warn("[HOOK] Blocking dangerous command");
          return { block: true };
        }
      },
    },
  ],
  PostToolUse: [
    {
      handler: async (input) => {
        console.log(`[HOOK] Tool ${input.toolName} completed`);
        console.log(`[HOOK] Result length:`, input.toolResult.length);
      },
    },
  ],
  PostToolUseFailure: [
    {
      handler: async (input) => {
        console.error(`[HOOK] Tool ${input.toolName} failed:`, input.error);
      },
    },
  ],
  SessionStart: [
    {
      handler: async () => {
        console.log("[HOOK] Session started");
      },
    },
  ],
  SessionEnd: [
    {
      handler: async () => {
        console.log("[HOOK] Session ended");
      },
    },
  ],
  FileChanged: [
    {
      handler: async (input) => {
        console.log(`[HOOK] File changed: ${input.path}`);
      },
    },
  ],
});

const agent = createAgent({
  hooks,
  model: "claude-sonnet-4-6",
});

const result = await agent.prompt("List files and create a new test file");
console.log(result.text);

Available Hook Events

Tool lifecycle: PreToolUse, PostToolUse, PostToolUseFailure
Session: SessionStart, SessionEnd, Stop
Subagents: SubagentStart, SubagentStop
User interaction: UserPromptSubmit, PermissionRequest, PermissionDenied
Tasks: TaskCreated, TaskCompleted
Config: ConfigChange, CwdChanged
File system: FileChanged
System: Notification, PreCompact, PostCompact, TeammateIdle

Permission Modes

Control how the agent handles permission requests:

import { createAgent } from "@codeany/open-agent-sdk";

// Bypass all permissions (default)
const autoAgent = createAgent({
  permissionMode: "bypassPermissions",
});

// Never ask, deny if permission needed
const denyAgent = createAgent({
  permissionMode: "dontAsk",
});

// Ask for permission (requires custom handler)
const askAgent = createAgent({
  permissionMode: "ask",
  // Implement permission handler via hooks
});

// Change mode mid-session
autoAgent.setPermissionMode("dontAsk");

Configuration Options

Agent Options

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent({
  // API configuration
  apiType: "anthropic-messages", // or "openai-completions"
  model: "claude-sonnet-4-6",
  apiKey: process.env.CODEANY_API_KEY,
  baseURL: "https://api.anthropic.com",
  
  // Session
  sessionId: "my-session-id",
  maxTurns: 10,
  
  // Working directory
  cwd: process.cwd(),
  
  // System prompt
  systemPrompt: "You are a helpful coding assistant",
  appendSystemPrompt: "\n\nAlways explain your reasoning.",
  
  // Tools
  tools: [], // Custom tool list
  allowedTools: ["Read", "Write", "Glob"],
  disallowedTools: ["Bash"],
  
  // Permissions
  permissionMode: "bypassPermissions",
  
  // MCP servers
  mcpServers: {},
  
  // Subagents
  agents: {},
  
  // Hooks
  hooks: createHookRegistry({}),
  
  // Model parameters
  temperature: 0.7,
  maxTokens: 4096,
});

Query Options

import { query } from "@codeany/open-agent-sdk";

for await (const msg of query({
  prompt: "Your prompt here",
  options: {
    model: "gpt-4o",
    apiType: "openai-completions",
    apiKey: process.env.OPENAI_API_KEY,
    cwd: "/path/to/project",
    allowedTools: ["Read", "Glob"],
    permissionMode: "bypassPermissions",
    maxTurns: 5,
    temperature: 0.5,
  },
})) {
  // Handle messages
}

Advanced Patterns

Session Management

import { createAgent, listSessions, forkSession } from "@codeany/open-agent-sdk";

// Create agent with persistent session
const agent = createAgent({
  sessionId: "my-project-session",
});

await agent.prompt("Analyze the codebase structure");
await agent.prompt("Now suggest improvements");

// List all sessions
const sessions = await listSessions();
console.log("Saved sessions:", sessions);

// Fork a session for experimentation
const forkedId = await forkSession("my-project-session");
const forkedAgent = createAgent({ sessionId: forkedId });

await forkedAgent.prompt("Try refactoring with a different approach");

Interrupting Long-Running Queries

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent();

// Start a long-running query
const queryPromise = agent.prompt("Analyze all files in the project");

// Interrupt after 5 seconds
setTimeout(() => {
  agent.interrupt();
  console.log("Query interrupted");
}, 5000);

try {
  const result = await queryPromise;
  console.log(result.text);
} catch (error) {
  console.log("Query was interrupted");
}

Model Switching

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent({ model: "claude-sonnet-4-6" });

await agent.prompt("Quick analysis");

// Switch to more powerful model for complex task
agent.setModel("claude-opus-4");
await agent.prompt("Perform deep architectural analysis");

// Switch back to cheaper model
agent.setModel("claude-sonnet-4-6");
await agent.prompt("Summarize findings");

Streaming with Full Control

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent();

for await (const message of agent.query("Analyze this codebase")) {
  switch (message.type) {
    case "assistant":
      for (const block of message.message.content) {
        if ("text" in block) {
          process.stdout.write(block.text);
        } else if ("tool_use" in block) {
          console.log(`\n[Tool: ${block.tool_use.name}]`);
        }
      }
      break;
      
    case "tool_use":
      console.log(`\nExecuting: ${message.toolName}`);
      break;
      
    case "tool_result":
      console.log(`Tool result length: ${message.result.length} chars`);
      break;
      
    case "result":
      console.log(`\n\nCompleted in ${message.num_turns} turns`);
      console.log(`Cost: $${message.total_cost_usd?.toFixed(4)}`);
      console.log(`Tokens: ${message.usage.input_tokens + message.usage.output_tokens}`);
      break;
      
    case "error":
      console.error(`Error: ${message.error}`);
      break;
  }
}

Error Handling

import { createAgent } from "@codeany/open-agent-sdk";

const agent = createAgent();

try {
  const result = await agent.prompt("Your prompt here");
  console.log(result.text);
} catch (error) {
  if (error.message.includes("rate limit")) {
    console.error("Rate limit exceeded, retry later");
  } else if (error.message.includes("context length")) {
    console.error("Prompt too long, try simplifying");
  } else {
    console.error("Agent error:", error.message);
  }
} finally {
  await agent.close();
}

Troubleshooting

API Key Not Found

Error: API key not found

Solution: Set the CODEANY_API_KEY environment variable or pass apiKey in options:

const agent = createAgent({
  apiKey: process.env.CODEANY_API_KEY,
});

Model Not Found / Invalid API Type

Error: Model not found: gpt-4o

Solution: Explicitly set apiType for OpenAI models:

const agent = createAgent({
  apiType: "openai-completions",
  model: "gpt-4o",
  baseURL: "https://api.openai.com/v1",
});

MCP Server Connection Failed

Error: Failed to start MCP server

Solution: Ensure MCP server package is available and command is correct:

npm install -g @modelcontextprotocol/server-filesystem

const agent = createAgent({
  mcpServers: {
    filesystem: {
      command: "npx",
      args: ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"],
    },
  },
});

Permission Denied Errors

Permission denied: Cannot execute Bash

Solution: Adjust permission mode or allow specific tools:

const agent = createAgent({
  permissionMode: "bypassPermissions",
  allowedTools: ["Bash", "Read", "Write"],
});

Session Persistence Issues

Sessions are stored in .codeany/sessions/ by default. Ensure write permissions exist.

Rate Limiting

Implement retry logic with exponential backoff:

async function queryWithRetry(agent, prompt, maxRetries = 3) {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await agent.prompt(prompt);
    } catch (error) {
      if (error.message.includes("rate limit") && i < maxRetries - 1) {
        const delay = Math.pow(2, i) * 1000;
        console.log(`Rate limited, retrying in ${delay}ms...`);
        await new Promise(resolve => setTimeout(resolve, delay));
      } else {
        throw error;
      }
    }
  }
}

Web UI

The SDK includes a built-in web chat interface for testing:

npx tsx examples/web/server.ts

Then open http://localhost:8081 in your browser.

Complete Example: Code Review Agent

import { z } from "zod";
import { createAgent, tool, createSdkMcpServer, createHookRegistry } from "@codeany/open-agent-sdk";

// Custom tool for static analysis
const analyzeComplexity = tool(
  "analyze_complexity",
  "Analyze code complexity metrics",
  {
    filePath: z.string().describe("Path to file to analyze"),
  },
  async ({ filePath }) => {
    // Simplified complexity analysis
    return {
      content: [
        {
          type: "text",
          text: JSON.stringify({
            cyclomaticComplexity: 12,
            cognitiveComplexity: 8,
            linesOfCode: 245,
          }),
        },
      ],
    };
  }
);

const mcpServer = createSdkMcpServer({
  name: "code-analysis",
  tools: [analyzeComplexity],
});

// Hook to log all tool usage
const hooks = createHookRegistry({
  PreToolUse: [
    {
      handler: async (input) => {
        console.log(`[Review] Using tool: ${input.toolName}`);
      },
    },
  ],
  PostToolUse: [
    {
      handler: async (input) => {
        console.log(`[Review] Tool ${input.toolName} completed`);
      },
    },
  ],
});

const agent = createAgent({
  model: "claude-sonnet-4-6",
  systemPrompt: "You are an expert code reviewer. Focus on code quality, security, performance, and maintainability.",
  allowedTools: ["Read", "Glob", "Grep", "Symbols", "analyze_complexity"],
  mcpServers: { analysis: mcpServer },
  hooks,
  permissionMode: "bypassPermissions",
});

async function reviewCode(pattern) {
  console.log(`\n=== Starting code review for: ${pattern} ===\n`);
  
  const result = await agent.prompt(`
Review all files matching ${pattern}. For each file:
1. Analyze code quality and structure
2. Check for security vulnerabilities
3. Assess performance implications
4. Suggest improvements

Use analyze_complexity to get metrics.
Provide a summary with prioritized recommendations.
  `);
  
  console.log("\n=== Review Results ===\n");
  console.log(result.text);
  console.log(`\n=== Stats: ${result.num_turns} turns, ${result.usage.input_tokens + result.usage.output_tokens} tokens ===`);
}

reviewCode("src/**/*.ts").then(() => agent.close());

FAQ

What does the open-agent-sdk-typescript skill do?

Build AI agents with in-process agent loops using Anthropic or OpenAI APIs, custom tools, MCP servers, and multi-turn conversations

How do I install open-agent-sdk-typescript?

Run npx skills add https://github.com/reason-machines/ai-agent-skills --skill open-agent-sdk-typescript in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/open-agent-sdk-typescript/ (personal) or .claude/skills/open-agent-sdk-typescript/ (project).

Which AI agents can use open-agent-sdk-typescript?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is open-agent-sdk-typescript safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains open-agent-sdk-typescript?

It is published by reason-machines in reason-machines/ai-agent-skills. It has 172 recorded installs.

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google-agents-cli-eval

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This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

AI & Agents513.5K installs

skill-creator

anthropics/skills

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

OfficialAI & Agents416.4K installs

codex-pet

prime-skills/runcomfy-agent-skills

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

AI & Agents402.1K installs

full-output-enforcement

leonxlnx/taste-skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

AI & Agents401K installs

executing-plans

obra/superpowers

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

AI & Agents245.7K installs

open-agent-sdk-typescript

Install

Install

Describe the task

Review the result

SKILL.md

Open Agent SDK (TypeScript)

Installation

Core Concepts

API Types

Agent vs Query

Quick Start Examples

One-Shot Streaming Query

Simple Blocking Prompt

OpenAI / GPT Models

Multi-Turn Conversation

Custom Tools

Using Zod Schema (Recommended)

Low-Level Tool Definition

Built-in Tools

Restricting Tools

Skills

Using Built-in Skills

Creating Custom Skills

MCP Server Integration

External MCP Servers

In-Process MCP Servers

Subagents

Lifecycle Hooks

Available Hook Events

Permission Modes

Configuration Options

Agent Options

Query Options

Advanced Patterns

Session Management

Interrupting Long-Running Queries

Model Switching

Streaming with Full Control

Error Handling

Troubleshooting

API Key Not Found

Model Not Found / Invalid API Type

MCP Server Connection Failed

Permission Denied Errors

Session Persistence Issues

Rate Limiting

Web UI

Complete Example: Code Review Agent

FAQ

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