Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/atlanhq/agent-toolkit/pythongit clone --depth 1 https://github.com/atlanhq/agent-toolkitWhat 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 | $0.00213 | $0.00213 |
| Opus 5 | $0.00106 | $0.00106 |
| Sonnet 5 | $0.00043 | $0.00043 |
| Haiku 4.5 | $0.00021 | $0.00021 |
Grade A, and why
python 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 2d 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.
What it actually says
You are an AI assistant specialized in Python development. Your approach emphasizes:
Clear project structure with separate directories for source code, docs, and config.
Modular design with distinct files for models, services, controllers, and utilities.
Configuration management using environment variables.
Robust error handling and logging, including context capture.
Detailed documentation using docstrings and README files.
Dependency management via https://github.com/astral-sh/uv and virtual environments.
Code style consistency using Ruff.
CI/CD implementation with GitHub Actions or GitLab CI.
AI-friendly coding practices:
You provide code snippets and explanations tailored to these principles, optimizing for clarity and AI-assisted development.
Follow the following rules:
For any python file, be sure to ALWAYS add typing annotations to each function or class. Be sure to include return types when necessary. Add descriptive docstrings to all python functions and classes as well. Please use pep257 convention. Update existing docstrings if need be.
Make sure you keep any comments that exist in a file.
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.
- 2d ago First seen · 33 lines · 213 tokens per session scan A 12cb8487a53a
python is a cursor rule published in the GitHub repository atlanhq/agent-toolkit (32 stars, last pushed 4d ago), licensed MIT. It adds 213 tokens to every session, about $0.0011 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 cursor rules, from other repositories
api-property-optionality-hygiene
Fix ApiProperty/ApiPropertyOptional optionality mismatches in DTO files; use for scheduled batch fixes or DTO edits.
java-springboot-jpa-cursorrules-prompt-file
description: "Cursor rules for Java development with Springboot and JPA integration." globs: / alwaysApply: false.
conservative-file-creation
Check for existing files before creating. Be conservative about new files and code.
secure-dev-rust
These rules apply to all Rust code in the repository and aim to prevent common security risks through disciplined use of memory safety, input validation, error handling, and safe APIs.
design-patterns
Design patterns (GoF) and file size conventions for sweagent TypeScript codebase.
cursorrules
ALWAYS start your session by reading AGENTS.md and .memory/wiki/hot.md to get project context before suggesting code or answering questions.