Borrowing it
Nothing to install: this file belongs to vstorm-co/pydantic-ai-backend. 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/vstorm-co/pydantic-ai-backend/main/CLAUDE.mdgit clone --depth 1 https://github.com/vstorm-co/pydantic-ai-backendWrote 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/vstorm-co/pydantic-ai-backend/claude-md)<a href="https://agentmods.dev/instructions/vstorm-co/pydantic-ai-backend/claude-md"><img src="https://agentmods.dev/badge/instructions/vstorm-co/pydantic-ai-backend/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/vstorm-co/pydantic-ai-backend/claude-md"><img src="https://agentmods.dev/badge/instructions/vstorm-co/pydantic-ai-backend/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00948 | $0.00948 |
| Opus 5 | $0.00474 | $0.00474 |
| Sonnet 5 | $0.00190 | $0.00190 |
| Haiku 4.5 | $0.00095 | $0.00095 |
Grade A, and why
pydantic-ai-backend 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Guidance for Claude Code when working on this repository.
What This Project Is
pydantic-ai-backend provides file storage and sandbox backends for AI agents. It's designed to work with pydantic-ai and pydantic-deep.
Key pattern: Protocol-based backends - all backends implement BackendProtocol for consistent file operations.
Commands
uv sync --all-extras --group dev # Install all dependencies
uv run pytest # Run tests
uv run coverage run -m pytest && uv run coverage report # Test with coverage
uv run ruff check . # Lint
uv run ruff format . # Format
uv run pyright # Type check
uv run mypy src/pydantic_ai_backends # MyPy check
Structure
src/pydantic_ai_backends/
├── __init__.py # Public API, lazily loaded
├── types.py # FileData, FileInfo, WriteResult, EditResult, RuntimeConfig
├── protocol.py # BackendProtocol, SandboxProtocol (+ async variants)
├── adapter.py # Sync -> async adapters, ensure_async()
├── capability.py # ConsoleCapability for pydantic-ai
├── hashline.py # Content-hash line editing
├── _editing.py # Shared `edit` replacement rules
├── _limits.py # Output and read ceilings
├── _optional.py # Optional-extra imports with install hints
├── _paths.py # Virtual path normalisation and validation
├── _text.py # Encoding detection, decoding, PDF extraction
├── backends/
│ ├── base.py # BaseSandbox (shell-based defaults)
│ ├── state.py # StateBackend (in-memory)
│ ├── local.py # LocalBackend (real filesystem + shell)
│ ├── composite.py # PrefixRouter, CompositeBackend, AsyncCompositeBackend
│ ├── daytona.py # DaytonaSandbox
│ ├── kubernetes.py # KubernetesPodSandbox
│ ├── _background.py # Long-lived process registry
│ ├── _guard.py # Synchronous permission enforcement
│ └── docker/ # sandbox.py, session.py, runtimes.py, _client/_image/_stats
├── permissions/ # types.py, checker.py, presets.py
├── toolsets/ # console.py, descriptions.py, _content/_tracking/_ruleset
└── remote/ # client.py (RemoteSandbox), server.py (sandboxd), wire.py
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.
- 10d ago First seen · 95 lines · 948 tokens per session scan A 8a8786fa4f6b
pydantic-ai-backend CLAUDE.md is an instructions file published in the GitHub repository vstorm-co/pydantic-ai-backend (127 stars, last pushed 6d ago), licensed MIT. It adds 948 tokens to every session, about $0.0047 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.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.