Show HN: Reticle – Postman for AI Agents
TL;DR
Reticle is a local desktop tool (Tauri + React + SQLite) that consolidates the full LLM agent testing loop into one interface. You define scenarios with prompts, variables, and tools, run them against multiple models, and see prompts, responses, tool calls, and results in one view. An eval mode checks whether a prompt or model change silently breaks existing behavior – essentially regression testing for AI agents. All data stays local: prompts, API keys, and run history are stored in SQLite on your own machine.
Nauti's Take
The Postman analogy is well-chosen and hits a real nerve – tooling for agent development is still lagging far behind the pace at which people are actually building agents. The fact that everything runs locally is not a limitation but a hard requirement for many companies.
The interesting question is whether Reticle can evolve from a useful solo tool into something teams share – collaborative eval sets and shared scenarios would be the logical next step. For now: a solid approach worth watching.
Briefingshow
Anyone building agents today mostly debugs in the dark: add logs, run code, manually compare prompts. Reticle targets this pain point directly, positioning itself as 'Postman for AI agents' – an analogy that highlights how badly a standardized testing tool is needed in this space. The eval mode is especially relevant: prompt changes have side effects that often only surface in production.
A local, privacy-friendly tool also lowers the barrier for teams unwilling to send sensitive data to cloud services.
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