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pydantic-deepagents: Instructions file for Claude Code

CLAUDE.md

pydantic-deepagents CLAUDE.md is an instructions file for Claude Code from vstorm-co/pydantic-deepagents. It costs 4,259 tokens per session, scanned A, original, MIT.

Repository guidance for working on pydantic-deepagents, a Python project for building AI agents. It lists its commands, tests, documentation workflow, and feature-based code layout.

In plain words
What is it for?
Installing dependencies, running all checks or one pytest test, building documentation, and locating code for a particular feature.
Why use it?
It gives a coding agent the project rules and commands it needs, reducing guesswork about how to change and check the code.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions subagents; mentions Claude Code.

This is vstorm-co/pydantic-deepagents's own configuration. It tells Claude Code how to work on pydantic-deepagents itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything pydantic-deepagents configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /home/user/project.

not rated 1.1krepo +5 16d ago A scan 4,259 tokens original MIT
View source ↗ vstorm-co/pydantic-deepagents vstorm-co.github.io
About the project

Pydantic Deep Agents is a self-hosted terminal AI assistant and Python framework for building coding, research, and other AI agents. It gives agents tools such as file access, shell commands, planning, memory, sub-agents, sandboxed execution, and MCP connections, and supports different models.

vstorm-co/pydantic-deepagents · 1,057 stars · on GitHub · vstorm-co.github.io

Reuse

Borrowing it

Nothing to install: this file belongs to vstorm-co/pydantic-deepagents. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/vstorm-co/pydantic-deepagents/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/vstorm-co/pydantic-deepagents

Made for: Claude Code.

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README.md
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<a href="https://agentmods.dev/instructions/vstorm-co/pydantic-deepagents/claude-md"><img src="https://agentmods.dev/badge/instructions/vstorm-co/pydantic-deepagents/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 4,259 This file is loaded in full into every session.
When invoked 4,259 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.04259 $0.04259
Opus 5 $0.02129 $0.02129
Sonnet 5 $0.00852 $0.00852
Haiku 4.5 $0.00426 $0.00426

Measured 8d ago against content hash e4d570b63e27, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pydantic-deepagents CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 376 lines

How it starts

The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Development Commands

Core Development Tasks

  • Install dependencies: make install (requires uv and pre-commit)
  • Run all checks: make all or pre-commit run --all-files
  • Run tests: make test
  • Build docs: make docs or make docs-serve (local development)

Single Test Commands

  • Run specific test: uv run pytest tests/test_agent.py::test_function_name -v
  • Run test file: uv run pytest tests/test_agent.py -v
  • Run with debug: uv run pytest tests/test_agent.py -v -s

Project Architecture

Repository Layout

  • pydantic_deep/ — Core library (agent, deps, models, instructions, types)
  • pydantic_deep/features/<name>/ — One vertical-slice package per feature (capability.py + toolset.py + service.py/types.py). Organize by feature, not by kind — features/ is the only import location; the old toolsets/, capabilities/, processors/ and improve/ shims were removed in 0.3.39.
  • apps/cli/ — CLI + TUI application (Textual-based terminal AI assistant)
  • apps/deepresearch/ — Full-featured research reference app
  • tests/ — Unit tests
  • docs/ — Documentation source (MkDocs)

Core Components

Agent Factory (pydantic_deep/agent.py)

  • create_deep_agent(): Main factory function for creating configured agents
  • create_default_deps(): Helper for creating DeepAgentDeps with sensible defaults
  • Built on top of pydantic-ai's Agent class
  • Requires pydantic-ai>=1.77.0

Dependencies (pydantic_deep/deps.py)

  • DeepAgentDeps: Dataclass holding agent dependencies (backend, working_dir, skills_dirs, subagents)
  • Passed to agent.run() for runtime configuration

Backends (from pydantic-ai-backend)

  • BackendProtocol: Interface for file storage backends
  • StateBackend: In-memory file storage (for testing, ephemeral use)
  • LocalBackend: Real filesystem operations
  • DockerSandbox: Isolated Docker container execution
  • CompositeBackend: Combines multiple backends with routing
  • BaseSandbox / AsyncBaseSandbox: Bases for a custom sandbox — implement execute and edit and every file operation is derived from shell commands. Use the async one for a natively async transport (asyncssh, an async SDK) rather than a sync facade, which ensure_async cannot see through and which deadlocks against its own thread pool under load.

Read the full file on GitHub · 376 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 376 lines · 4,259 tokens per session scan A e4d570b63e27

Subscribe to this mod's changes

pydantic-deepagents CLAUDE.md is an instructions file published in the GitHub repository vstorm-co/pydantic-deepagents (1,057 stars, last pushed 16d ago), licensed MIT. It adds 4,259 tokens to every session, about $0.0213 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Building agentsagent-frameworkanthropicllmspydanticpydantic-ai
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