Code Review Checklist
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
Run and test Python code in a dedicated playground directory.
Install Python Playground
$ npx skills add pydantic/monty --skill python-playground -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install pydantic/monty python-playground --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/pydantic/monty.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/python-playground .claude/skills/python-playground && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "python-playground" agent skill from https://github.com/pydantic/monty/tree/main/.agents/skills/python-playground into .claude/skills/python-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-playground", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/pydantic/monty/tree/main/.agents/skills/python-playgroundType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add pydantic/monty --skill python-playground -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install pydantic/monty python-playground --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pydantic/monty.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/python-playground .agents/skills/python-playground && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "python-playground" agent skill from https://github.com/pydantic/monty/tree/main/.agents/skills/python-playground into .agents/skills/python-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-playground", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pydantic/monty --skill python-playground -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install pydantic/monty python-playground --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pydantic/monty.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/python-playground .cursor/skills/python-playground && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "python-playground" agent skill from https://github.com/pydantic/monty/tree/main/.agents/skills/python-playground into .cursor/skills/python-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-playground", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/pydantic/monty.git --path .agents/skills/python-playground--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add pydantic/monty --skill python-playground -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install pydantic/monty python-playground --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pydantic/monty.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/python-playground .gemini/skills/python-playground && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "python-playground" agent skill from https://github.com/pydantic/monty/tree/main/.agents/skills/python-playground into .gemini/skills/python-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-playground", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install pydantic/monty python-playgroundInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add pydantic/monty --skill python-playground -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/pydantic/monty.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/python-playground .github/skills/python-playground && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "python-playground" agent skill from https://github.com/pydantic/monty/tree/main/.agents/skills/python-playground into .github/skills/python-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-playground", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pydantic/monty --skill python-playground -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install pydantic/monty python-playground --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pydantic/monty.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/python-playground .opencode/skills/python-playground && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "python-playground" agent skill from https://github.com/pydantic/monty/tree/main/.agents/skills/python-playground into .opencode/skills/python-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-playground", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
python-playground- GitHub stars
- 8.6k
- Token cost
- ~424 tokens
- SKILL.md length
- 187 words
- Files
- 1
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- MIT
At a glance
Run and test Python code in a dedicated playground directory.
- Works in 3 steps: First, ensure the playground directory… → Use the Write tool to create the Python… → Run with: uv run playground/test.py to…
- You need to execute Python scripts
- SKILL.md covers Instructions, Example workflow and Guidelines
- Calls uv and cargo
What it does
Python Playground is an agent skill from pydantic/monty, published by the product's own GitHub organization. Run and test Python code in a dedicated playground directory. Use when you need to execute Python scripts, test code snippets, investigate CPython behavior, or experiment with Python without affecting the main codebase.
Its SKILL.md is about 420 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development. It works with Python. The repository describes itself as: A minimal, secure Python interpreter written in Rust for use by AI. The licence is MIT.
When your agent uses it
- You need to execute Python scripts
- Test code snippets
- Investigate CPython behavior
- Experiment with Python without affecting the main codebase
Example prompts
- “/python-playground”
Requirements
- Python 3
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- First, ensure the playground directory exists. If the playground directory doesn't already exist, run mkdir playground.
- Use the Write tool to create the Python file at playground/test.py
- Run with: uv run playground/test.py to test cpython behavior or cargo run -- playground/test.py to test monty behavior
What it can do on your machine
Read from SKILL.md and the folder at commit 5915273. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
uvcargo
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Python Playground loads about 424 tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 187 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from pydantic/monty at commit 5915273, republished under its MIT licence (© pydantic). 187 words, ~424 tokens.
Download SKILL.mdSave it as
.claude/skills/python-playground/SKILL.md (or your agent's skills folder).- name
- python-playground
- description
- Run and test Python code in a dedicated playground directory. Use when you need to execute Python scripts, test code snippets, investigate CPython behavior, or experiment with Python without affecting the main codebase.
Python Playground
Run Python code in an isolated playground directory for testing and experimentation.
Instructions
- First, ensure the playground directory exists. If the
playgrounddirectory doesn't already exist, runmkdir playground. - Use the Write tool to create the Python file at
playground/test.py - Run with:
uv run playground/test.pyto test cpython behavior orcargo run -- playground/test.pyto test monty behavior
IMPORTANT: Use separate tool calls for each step - do NOT chain commands with &&. This allows the pre-approved commands to work without prompting.
Example workflow
Step 1 - Create directory if it doesn't already exist (Bash, already allowed):
mkdir playgroundStep 2 - Write code (use Write tool, not cat):
Write to playground/test.py:
def foo():
raise ValueError('test')
foo()Step 3 - Run script (Bash, already allowed):
uv run playground/test.pyGuidelines
- The
playground/directory is gitignored - Use a different file name for each test you want to run, give the files recognizable names like
test_value_error.py - Use
uv run ...to run scripts (uses project Python) - Or,
cargo run -- ...to run scripts using Monty - Use Write tool for creating files (avoids permission prompts)
- Run mkdir and uv as separate commands (not chained)
- do NOT delete files from playground after you've finished testing
© pydantic, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .agents/skills/python-playground of pydantic/monty.
Open the folder on GitHubat commit 5915273
Compare with similar skills
Python Playground next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Python Playground this skillpydantic/monty | 8.6k | — | ~424 | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Merge Dependabot PRsonyx-dot-app/onyx | 32k | 1 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Kedro Babysitkedro-org/kedro | 11k | — | ~4k | Automated safety check: Pass | Custom licence | |
| LangBot Plugin Developmentlangbot-app/LangBot | 18k | — | ~3.9k | Automated safety check: Pass | Apache-2.0 | |
| Senior Architect Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 259 | 7 repos | ~1.2k | Automated safety check: Notes | Custom licence |
Similar skills
Merge Dependabot PRs
onyx-dot-app/onyx
Triages and lands a batch of open Dependabot PRs in the Onyx repo, where main is gated exclusively by GitHub's merge queue: approves and enqueues green PRs, closes superseded duplicates, fixes…
Kedro Babysit
kedro-org/kedro
Run Kedro's local lint / format / type-check / tests on changed files (uses the project's pre-commit hooks, ruff, mypy, pytest, lint-imports, detect-secrets, Make targets — in the right venv), or…
LangBot Plugin Development
langbot-app/LangBot
Guides building, debugging and testing LangBot plugins: components, SDK calls, README and locale rules, SDK pitfalls and WebSocket-based testing.
Senior Architect Toolkit
maslennikov-ig/claude-code-orchestrator-kit
Comprehensive software architecture skill for designing scalable, maintainable systems using ReactJS, NextJS, NodeJS, Express, React Native, Swift, Kotlin…
Flowsint Enricher Builder
reconurge/flowsint
Guides building Flowsint enrichers and types: where definitions live, how the base class and vault work, and when a new type is warranted.
More from pydantic/monty
All 9 skills in this repo- Official
Fix PR Comments
pydantic/monty
Read the review comments left by the known agent reviewers on the current PR, resolve and reply.
- Official
Review General
pydantic/monty
Review the current branch against its merge base for bugs, CPython divergence, sandbox escapes, resource-limit escapes, performance regressions, verbose comments and missing ./limitations/ or docs/…
- Official
Review Security
pydantic/monty
Security review of the current branch against its merge base — sandbox escapes, memory errors, panics and resource-limit bypasses.
- Official
Writing Style
pydantic/monty
How to write prose that reads like human technical documentation rather than LLM output.
- Official
Review Usability
pydantic/monty
Check whether the common Python code an LLM would plausibly write still works on this branch, testing real cases in ./playground against CPython.
- Official
Coverage
pydantic/monty
Fetch coverage diff from Codecov for the current branch or a specific PR.
Related
Works with
Categories
Questions about Python Playground
What does Python Playground do?
Run and test Python code in a dedicated playground directory. Python Playground is an agent skill from pydantic/monty, published by the product's own GitHub organization. Run and test Python code in a dedicated playground directory.
When should I use Python Playground?
Python Playground fits situations like: you need to execute Python scripts; test code snippets; investigate CPython behavior; experiment with Python without affecting the main codebase.
How do I install Python Playground in Claude Code?
Run `npx skills add pydantic/monty --skill python-playground -a claude-code`. Or copy the skill folder (.agents/skills/python-playground in pydantic/monty) into .claude/skills/python-playground in your project. Claude Code loads it when a task matches its description.
How do I install Python Playground in Codex?
Run `npx skills add pydantic/monty --skill python-playground -a codex`. Or copy the skill folder (.agents/skills/python-playground in pydantic/monty) into .agents/skills/python-playground in your project. Codex loads it when a task matches its description.
Can I use Python Playground in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pydantic/monty --skill python-playground -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/python-playground, .gemini/skills/python-playground, .github/skills/python-playground and .opencode/skills/python-playground in your project.
What does Python Playground need to run?
Going by SKILL.md and its folder, Python Playground needs the command-line tools its instructions call (uv and cargo). Our summary lists: Python 3.
Does Python Playground access the network?
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Python Playground safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Python Playground use?
Python Playground is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Python Playground use?
About 424 tokens (SKILL.md is roughly 1.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Python Playground?
Skills that share tags, products or a category with Python Playground: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Merge Dependabot PRs (onyx-dot-app/onyx, 32k stars), Kedro Babysit (kedro-org/kedro, 11k stars) and LangBot Plugin Development (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Python Playground?
pydantic (a GitHub organization, an official publisher) maintains it in pydantic/monty, which has 8,581 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 6, 2026.
Source: pydantic/monty on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.