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Show HN: Dari-docs – Optimize your docs using parallel coding agents

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Why This Matters

Dari-docs introduces a novel approach to improving technical documentation by simulating developer agents to identify ambiguities and gaps. This tool enables creators to refine their docs iteratively, ensuring that even AI agents can reliably understand and execute tasks based on the documentation. Its adoption could significantly enhance the clarity and usability of technical content in the industry.

Key Takeaways

Make your docs so good even the dumbest agent can ship.

dari-docs is a CLI for testing whether your documentation is clear enough for agents to use. It sends your docs to simulated developer agents, asks them to complete real tasks, reports where they get stuck, and can generate proposed docs edits from that feedback.

Use it to turn documentation quality from “seems understandable” into “an agent can actually complete the task.”

Why dari-docs?

Good docs used to mean “a developer can eventually figure this out.” That is no longer enough.

When the reader is an agent, ambiguity becomes measurable. Inconsistent terminology, hidden assumptions, scattered context, and missing setup steps all increase the chance that the agent fails the task or wastes context trying to infer what the docs meant.

dari-docs gives you a repeatable feedback loop for agent-readable documentation: define the task, run simulated users, inspect failures, and optionally pull back edited docs.

What it does

Tests docs with simulated developers — agents attempt concrete tasks using only the docs you provide.

— agents attempt concrete tasks using only the docs you provide. Finds task-blocking ambiguity — reports missing context, unclear setup, inconsistent terms, and places where the agent had to guess.

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