Agent skills for OpenAI Agents SDK

Claude Agent SDK build harness with a Planner/Builder/Evaluator loop.

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.

Design spec with 98 rules for building CLI tools that AI agents can safely use.

Generate AGENT.md files with proper YAML frontmatter, role definitions, expertise areas, and prompt templates following Babysitter SDK…

Installs and manages standardized design collaboration rules in AGENTS.md to enforce disciplined AI coding practices.

Analyzes and improves AI agent collaboration environments based on the 12 principles of Agent Harness maturity.

Analyze Agent Host debug log exports. Use when given an ah-logs or ahp-logs zip/folder, an Export Agent Host Debug Logs bundle…

Optimizes and generates AI coding agent instruction files like AGENTS.md and CLAUDE.md to improve project context and model performance.

Use when creating, editing, or deploying custom agent instructions or skills shared by Codex and Claude.

Use when writing or editing instructions for agents, including AGENTS.md, CLAUDE.md, SKILL.md, project rules, or reusable agent prompts.

Run all three agent integration phases sequentially: research, write-tests, and implement using E2E-first TDD (unit tests written last).

Builds self-verifying experiment laboratories and measurement feedback loops for optimization, debugging, visual fidelity, quality, cost…

Automate Agent Mail tasks via Rube MCP (Composio).

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

AI UGC video production from the terminal using the `agent-media` CLI.

Default media tools every AgentFlow agent has out of the box — generate real AI text-to-video (generate_ai_video → ai_video_status) and AI…

Send meme reaction images in chat. One command to pick & send. Multi-platform (Discord, Feishu, Telegram, etc). Use when the conversation…

Use when deciding when and how to commit items to a project memory system.

Memory is the cornerstone of intelligent agents.

End-to-end Agent Observability pipeline for an instrumented ml_app — classify production traces, root-cause failures, bootstrap…

Root cause analysis on production LLM traces.