temporal-pydanticai-codeact: Instructions file for Claude Code

CLAUDE.md

temporal-pydanticai-codeact CLAUDE.md is an instructions file for Claude Code from scalabreseGD/temporal-pydanticai-codeact. It costs 4,985 tokens per session, scanned A, original, MIT.

Repository-specific instructions for a Python library that builds agents with code execution using PydanticAI, Temporal, and Docker. Temporal manages reliable long-running workflows, while PydanticAI helps build typed AI applications.

In plain words
What is it for?
Setting up the development environment and implementing or documenting workflows in the `temporal.pydanticai.codeact` package.
Why use it?
It records the project's structure, required Python setup, dependencies, and documentation expectations before code is written.

Instructions file for Claude Code

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

This is scalabreseGD/temporal-pydanticai-codeact's own configuration. It tells Claude Code how to work on temporal-pydanticai-codeact 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 temporal-pydanticai-codeact configures →

Reuse

Borrowing it

Nothing to install: this file belongs to scalabreseGD/temporal-pydanticai-codeact. 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/scalabreseGD/temporal-pydanticai-codeact/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/scalabreseGD/temporal-pydanticai-codeact

Made for: Claude Code.

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ModelPer sessionOnce invoked
Fable 5.1 $0.04985 $0.04985
Opus 5 $0.02492 $0.02492
Sonnet 5 $0.00997 $0.00997
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Measured 7d ago against content hash 8d4f904ff50e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

temporal-pydanticai-codeact CLAUDE.md scanned grade A with 1 finding 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 7d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

content = fetch(url="https://example.com")
CLAUDE.md · 719 lines

How it starts

The opening of the file, as written. The whole thing — 719 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.

Project Overview

This is a Python library named temporal.pydanticai.codeact, a reusable package for building agents with code execution capabilities using:

  • PydanticAI (v1.27.0) - Agent framework for building production-grade GenAI applications
  • Temporal (v1.19.0) - Workflow orchestration for reliable, long-running processes
  • Docker Python Client (v7.1.0) - Programmatic Docker container management

The library is structured as a proper Python package under the namespace temporal.pydanticai.codeact.

Environment Setup

  • Python Version: 3.13+
  • Virtual Environment: .venv/ (already configured)
  • Package Manager: uv (inferred from pyproject.toml structure)

Core Dependencies

  • pydantic-ai (>=1.27.0): Agent framework for building type-safe AI applications
  • temporalio (>=1.19.0): Workflow orchestration and durable execution
  • docker (>=7.1.0): Docker Engine API client for container management

Documentation Requirements

CRITICAL: Before writing any code that uses external libraries or frameworks, you MUST check Context7 MCP for the most up-to-date documentation. Use the mcp__context7__resolve-library-id and mcp__context7__get-library-docs tools to retrieve current API references and code examples.

This is especially important for:

  • PydanticAI API usage and patterns
  • Python standard library updates (since this uses Python 3.13+)
  • Any third-party dependencies added to the project

Common Commands

Environment Management

# Activate virtual environment
source .venv/bin/activate

# Install dependencies (when added to pyproject.toml)
uv sync

# Add new dependencies
uv add <package-name>

Development Workflow

# Run all tests
pytest

# Run tests from specific module
pytest tests/temporal/pydanticai/codeact/test_datamodels_codeact.py

# Run with verbose output
pytest -v

# Run only unit tests (no Docker/Temporal required)
pytest -m unit

# Type checking
mypy src/

# Linting
ruff check .

# Auto-fix linting issues
ruff check --fix .

Read the full file on GitHub · 719 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. 7d ago First seen · 719 lines · 4,985 tokens per session scan A 8d4f904ff50e

Subscribe to this mod's changes

temporal-pydanticai-codeact CLAUDE.md is an instructions file published in the GitHub repository scalabreseGD/temporal-pydanticai-codeact (2 stars, last pushed 8mo ago), licensed MIT. It adds 4,985 tokens to every session, about $0.0249 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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