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Each listing spells out exactly what's inside — the steps, the ready-to-run code, and which AI tools it works with — so you know what you're getting before you buy.

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Invoke when a downstream system must consume LLM output as JSON matching a fixed schema and malformed or missing fields would break the pipeline.

  • 10-step procedure
  • Runnable Python included
  • 9-point quality checklist
agent-infrastructureWorks with any modern AI assistant·8 min read·Updated today

Invoke when an autonomous task may outlast one context window—persist resumable checkpoints to a state file so work survives resets and interruptions.

  • 9-step procedure
  • Runnable Python / JSON included
  • 8-point quality checklist
agent-infrastructureWorks with any modern AI assistant·7 min read·Updated today

Deploy and run a SearXNG meta-search instance for AI agents to query the live web: Docker setup, engine configuration, API integration, and result parsing.

  • Runnable YAML / Shell / JSON included
  • 7 pitfalls to avoid
  • Installs into 6 tools
agent-infrastructureWorks with any modern AI assistant·7 min read·Updated today