Pydantic Deep Agents — Python Deep Agent Harness

Main

• Start with the CLI to validate your environment, then switch to the framework API once you’ve chosen your tool set and provider config.

• Use lifecycle hooks (PRE/POST_TOOL_USE) to add safety gates, logging, and policy checks around shell/file tools.

• Keep memory explicit: treat MEMORY.md (and similar context files) as audited inputs, not a dumping ground for secrets.

• Prefer “capabilities” over ad-hoc glue code: README frames tools/memory/sandbox as composable capabilities you can enable per agent.

Source-backed notes

• README describes a batteries-included agent harness (tools, memory, sandboxing, unlimited context) plus a terminal assistant CLI.
• README documents a one-line installer (install.sh) and pip-based install for Python environments.
• README mentions Claude Code-style lifecycle hooks (PRE/POST_TOOL_USE) as a first-class feature.

FAQ

• Is it just a library?: No — README includes both a CLI terminal assistant and a framework API for building production agents.
• How do I install?: Use pip install "pydantic-deep[cli]" or the one-line install.sh method described in README.
• What’s the safest way to extend it?: Add policy checks in lifecycle hooks and keep tool permissions scoped per agent.