Agent Blueprints

Each blueprint is a self-contained agent — system prompt, tool definitions, initialization code, and a walkthrough of how it handles a real task. Designed to work with OpenAI and Anthropic APIs. Framework-agnostic.

Note:

Start with the Research Agent. It uses the simplest tool set and demonstrates the ReAct loop clearly. Then move to Code Review (file system tools) and Content Writer (multi-step pipeline).

Prerequisites

All blueprints expect Python 3.10+ and an API key (OpenAI or Anthropic). Install the client library:

pip install openai anthropic

Research Agent

Web search + summarize + cite sources + fact-check loop. Tools: web_search, extract_content, fact_check.

Code Review Agent

Reads file tree, runs linter, checks patterns, suggests refactors. Tools: read_file, run_linter, list_directory, git_diff.

Content Writer

Outline → research → draft → edit → final. Tools: web_search, grammar_check, tone_adjust, seo_analyze.

OpenClaw Setup Guide

Complete setup and configuration guide for OpenClaw — the agent with the fastest GitHub star growth in history. Skills & Tools model, NVIDIA NemoClaw, Pi SDK engine, security hardening.

Sandboxed Code Execution for AI Agents with MicroPython + WASM

Step-by-step tutorial on building a safe code-execution tool for AI agents using MicroPython compiled to WebAssembly. Covers installation, one-shot and persistent sessions, resource limits, host functions, and integration into agent tool loops — with working code you can copy and run.

Agent Concepts

Core concepts in AI agent development — memory architectures, multi-agent collaboration, evaluation, cost optimization, and skill management.

Agent Blueprints