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.
curl -O https://raw.githubusercontent.com/scalabreseGD/temporal-pydanticai-codeact/main/CLAUDE.mdgit clone --depth 1 https://github.com/scalabreseGD/temporal-pydanticai-codeactWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/scalabresegd/temporal-pydanticai-codeact/claude-md)<a href="https://agentmods.dev/instructions/scalabresegd/temporal-pydanticai-codeact/claude-md"><img src="https://agentmods.dev/badge/instructions/scalabresegd/temporal-pydanticai-codeact/claude-md.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.04985 | $0.04985 |
| Opus 5 | $0.02492 | $0.02492 |
| Sonnet 5 | $0.00997 | $0.00997 |
| Haiku 4.5 | $0.00498 | $0.00498 |
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") 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 .
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.
- 7d ago First seen · 719 lines · 4,985 tokens per session scan A 8d4f904ff50e
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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