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.

All Blueprints

Research Agent — Web search, extraction, fact-checking, and citations
Code Review Agent — Lints, flags risky patterns, and suggests refactors
Content Writer Agent — Multi-step outline → draft → edit pipeline
Testing Agent — Finds coverage gaps and generates unit tests
Contract Review Agent — Extracts clauses, flags risks, summarizes contracts
File-Based ETL Agent — Infers schemas and builds documented pipelines from CSV/JSON
SQL Agent — Natural language to validated SQLite queries
Data Insights Agent — Stats, correlations, outliers, charts, and written insights
Incident Runbook Agent — Severity classification, timelines, and postmortem drafts
Multi-Agent Orchestrator — Manager-worker delegation across researcher/coder/writer
HF Spaces Multi-Agent Chain — Chain hosted Hugging Face Spaces via agents.md
Datasette Agent Tool Gating — Permission-gated write tools with user approval
Autonomous Researcher (Firecrawl MCP) — Recursive crawling and dossier storage via MCP

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Agent Blueprints