9 docs tagged with "agents"

Choose what an AI assistant should remember and retrieve, without confusing stored notes, search results, and authority.

A practical map of the control, context, tool, evidence, and evaluation layers around AI agents.

Store, connect, and retrieve Markdown notes across conversations while keeping recorded decisions separate from permissions.

How step limits, tool validation, verification, cancellation, and durable state keep agent loops useful and recoverable.

How to assemble a small, current working set while preserving provenance and durable state outside the model window.

Let AI find gaps, explain one step, and provide practice while keeping recall and problem solving with the learner.

Find Markdown notes with keyword, semantic, or hybrid search, then read the source behind each result.

Design tools whose inputs, authority, side effects, failures, and evidence remain legible to models and operators.

Combine semantic discovery and keyword search to locate relevant workspace files, then verify the current source.