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.
Python 3.11+ performance optimization guidelines (formerly python-311).
Install Python
$ npx skills add pproenca/dot-skills --skill python -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install pproenca/dot-skills python --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/pproenca/dot-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/python .claude/skills/python && 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" agent skill from https://github.com/pproenca/dot-skills/tree/master/skills/.curated/python into .claude/skills/python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python", 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/pproenca/dot-skills/tree/master/skills/.curated/pythonType 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 pproenca/dot-skills --skill python -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install pproenca/dot-skills python --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pproenca/dot-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/.curated/python .agents/skills/python && 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" agent skill from https://github.com/pproenca/dot-skills/tree/master/skills/.curated/python into .agents/skills/python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python", 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 pproenca/dot-skills --skill python -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install pproenca/dot-skills python --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pproenca/dot-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/.curated/python .cursor/skills/python && 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" agent skill from https://github.com/pproenca/dot-skills/tree/master/skills/.curated/python into .cursor/skills/python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python", 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/pproenca/dot-skills.git --path skills/.curated/python--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 pproenca/dot-skills --skill python -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install pproenca/dot-skills python --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pproenca/dot-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/.curated/python .gemini/skills/python && 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" agent skill from https://github.com/pproenca/dot-skills/tree/master/skills/.curated/python into .gemini/skills/python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python", 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 pproenca/dot-skills pythonInstalls 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 pproenca/dot-skills --skill python -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/pproenca/dot-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/.curated/python .github/skills/python && 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" agent skill from https://github.com/pproenca/dot-skills/tree/master/skills/.curated/python into .github/skills/python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python", 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 pproenca/dot-skills --skill python -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install pproenca/dot-skills python --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pproenca/dot-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/.curated/python .opencode/skills/python && 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" agent skill from https://github.com/pproenca/dot-skills/tree/master/skills/.curated/python into .opencode/skills/python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python", 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- GitHub stars
- 214
- Token cost
- ~2.1k tokens
- SKILL.md length
- 705 words
- Files
- 47 (incl. references, assets)
- Skills in repo
- 182
- Repo updated
- First seen
- Licence
- MIT
At a glance
Python 3.11+ performance optimization guidelines (formerly python-311).
- Works in 8 steps: I/O & Async Patterns — CRITICAL → Data Structure Selection — CRITICAL → Memory Optimization — HIGH → …
- Tasks involving asyncio
- SKILL.md covers When to Apply, Rule Categories by Priority, Table of Contents and References
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Python is an agent skill from pproenca/dot-skills. Python 3.11+ performance optimization guidelines (formerly python-311). This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal performance patterns. Triggers on tasks involving asyncio, data structures, memory management, concurrency, loops, strings, or Python idioms.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 49 other files, including reference files and assets (for example `AGENTS.md`, `assets/templates/_template.md` and `metadata.json`).
It sits in Development, covering Performance optimization and Refactoring. It works with Python. The repository describes itself as: A collection of AI agent skills following the Agent Skills open format. The licence is MIT.
When your agent uses it
- Tasks involving asyncio
- Data structures
- Memory management
Example prompts
- “/python”
Requirements
- Python 3
Workflow steps
8 steps, taken from the first numbered list in SKILL.md.
- I/O & Async Patterns — CRITICAL
- Data Structure Selection — CRITICAL
- Memory Optimization — HIGH
- Concurrency & Parallelism — HIGH
- Loop & Iteration — MEDIUM
- String Operations — MEDIUM
- Function & Call Overhead — LOW-MEDIUM
- Python Idioms & Micro — LOW
What it can do on your machine
Read from SKILL.md and the folder at commit cf93c57. 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
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
realpython.comdocs.python.orgpeps.python.orgwiki.python.orggithub.comdatacamp.comblog.jetbrains.com
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 loads about 2.1k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 705 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 pproenca/dot-skills at commit cf93c57, republished under its MIT licence (© pproenca). 705 words, ~2,078 tokens.
Download SKILL.mdSave it as
.claude/skills/python/SKILL.md (or your agent's skills folder). This skill also uses 46 other files; get the full folder from GitHub.- name
- python
- description
- Python 3.11+ performance optimization guidelines (formerly python-311). This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal performance patterns. Triggers on tasks involving asyncio, data structures, memory management, concurrency, loops, strings, or Python idioms.
Python 3.11 Best Practices
Comprehensive performance optimization guide for Python 3.11+ applications. Contains 42 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.
When to Apply
Reference these guidelines when:
- Writing new Python async I/O code
- Choosing data structures for collections
- Optimizing memory usage in data-intensive applications
- Implementing concurrent or parallel processing
- Reviewing Python code for performance issues
Rule Categories by Priority
| Priority | Category | Impact | Prefix |
|---|---|---|---|
| 1 | I/O & Async Patterns | CRITICAL | io- |
| 2 | Data Structure Selection | CRITICAL | ds- |
| 3 | Memory Optimization | HIGH | mem- |
| 4 | Concurrency & Parallelism | HIGH | conc- |
| 5 | Loop & Iteration | MEDIUM | loop- |
| 6 | String Operations | MEDIUM | str- |
| 7 | Function & Call Overhead | LOW-MEDIUM | func- |
| 8 | Python Idioms & Micro | LOW | py- |
Table of Contents
I/O & Async Patterns — CRITICAL
- 1.1 Defer await Until Value Needed — CRITICAL (2-5× faster for dependent operations)
- 1.2 Use aiofiles for Async File Operations — CRITICAL (prevents event loop blocking)
- 1.3 Use asyncio.gather() for Concurrent I/O — CRITICAL (2-10× throughput improvement)
- 1.4 Use Connection Pooling for Database Access — CRITICAL (100-200ms saved per connection)
- 1.5 Use Semaphores to Limit Concurrent Operations — CRITICAL (prevents resource exhaustion)
- 1.6 Use uvloop for Faster Event Loop — CRITICAL (2-4× faster async I/O)
Data Structure Selection — CRITICAL
- 2.1 Use bisect for O(log n) Sorted List Operations — CRITICAL (O(n) to O(log n) search)
- 2.2 Use defaultdict to Avoid Key Existence Checks — CRITICAL (eliminates redundant lookups)
- 2.3 Use deque for O(1) Queue Operations — CRITICAL (O(n) to O(1) for popleft)
- 2.4 Use Dict for O(1) Key-Value Lookup — CRITICAL (O(n) to O(1) lookup)
- 2.5 Use frozenset for Hashable Set Keys — CRITICAL (enables set-of-sets patterns)
- 2.6 Use Set for O(1) Membership Testing — CRITICAL (O(n) to O(1) lookup)
Memory Optimization — HIGH
- 3.1 Intern Repeated Strings to Save Memory — HIGH (reduces duplicate string storage)
- 3.2 Use slots for Memory-Efficient Classes — HIGH (20-50% memory reduction per instance)
- 3.3 Use array.array for Homogeneous Numeric Data — HIGH (4-8× memory reduction for numbers)
- 3.4 Use Generators for Large Sequences — HIGH (100-1000× memory reduction)
- 3.5 Use weakref for Caches to Prevent Memory Leaks — HIGH (prevents unbounded cache growth)
Concurrency & Parallelism — HIGH
- 4.1 Use asyncio for I/O-Bound Concurrency — HIGH (300% throughput improvement for I/O)
- 4.2 Use multiprocessing for CPU-Bound Parallelism — HIGH (4-8× speedup on multi-core systems)
- 4.3 Use Queue for Thread-Safe Communication — HIGH (prevents race conditions)
- 4.4 Use TaskGroup for Structured Concurrency — HIGH (prevents resource leaks on failure)
- 4.5 Use ThreadPoolExecutor for Blocking Calls in Async — HIGH (prevents event loop blocking)
Loop & Iteration — MEDIUM
- 5.1 Hoist Loop-Invariant Computations — MEDIUM (avoids N× redundant work)
- 5.2 Use any() and all() for Boolean Aggregation — MEDIUM (O(n) to O(1) best case)
- 5.3 Use dict.items() for Key-Value Iteration — MEDIUM (single lookup vs double lookup)
- 5.4 Use enumerate() for Index-Value Iteration — MEDIUM (cleaner code, avoids index errors)
- 5.5 Use itertools for Efficient Iteration Patterns — MEDIUM (2-3× faster iteration patterns)
- 5.6 Use List Comprehensions Over Explicit Loops — MEDIUM (2-3× faster iteration)
String Operations — MEDIUM
- 6.1 Use f-strings for Simple String Formatting — MEDIUM (20-30% faster than .format())
- 6.2 Use join() for Multiple String Concatenation — MEDIUM (4× faster for 5+ strings)
- 6.3 Use str.startswith() with Tuple for Multiple Prefixes — MEDIUM (single call vs multiple comparisons)
- 6.4 Use str.translate() for Character-Level Replacements — MEDIUM (10× faster than chained replace())
Function & Call Overhead — LOW-MEDIUM
- 7.1 Reduce Function Calls in Tight Loops — LOW-MEDIUM (100ms savings per 1M iterations)
- 7.2 Use functools.partial for Pre-Filled Arguments — LOW-MEDIUM (50% faster debugging via introspection)
- 7.3 Use Keyword-Only Arguments for API Clarity — LOW-MEDIUM (prevents positional argument errors)
- 7.4 Use lru_cache for Expensive Function Memoization — LOW-MEDIUM (avoids repeated computation)
Python Idioms & Micro — LOW
- 8.1 Leverage Zero-Cost Exception Handling — LOW (zero overhead in happy path (Python 3.11+))
- 8.2 Prefer Local Variables Over Global Lookups — LOW (faster name resolution)
- 8.3 Use dataclass for Data-Holding Classes — LOW (reduces boilerplate by 80%)
- 8.4 Use Lazy Imports for Faster Startup — LOW (10-15% faster startup)
- 8.5 Use match Statement for Structural Pattern Matching — LOW (reduces branch complexity)
- 8.6 Use Walrus Operator for Assignment in Expressions — LOW (eliminates redundant computations)
Show full SKILL.md (48 more words)Show less
© pproenca, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 46 other files (references, assets) in skills/.curated/python of pproenca/dot-skills.
- SKILL.md
- AGENTS.md
- assets/templates/_template.md
- metadata.json
- references/_sections.md
- references/conc-asyncio-for-io.md
- references/conc-multiprocessing-cpu.md
- references/conc-queue-communication.md
- references/conc-taskgroup.md
- references/conc-threadpool-blocking.md
- references/ds-bisect-sorted.md
- references/ds-defaultdict.md
- references/ds-deque-for-queue.md
- references/ds-dict-for-lookup.md
- references/ds-frozenset-for-hashable.md
- references/ds-set-for-membership.md
- references/func-keyword-only.md
- references/func-lru-cache.md
- … and 29 more
Open the folder on GitHubat commit cf93c57
Compare with similar skills
Python 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.
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|---|---|---|---|---|---|---|
| Python this skillpproenca/dot-skills | 214 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Pycrazyguitar/pysheeet | 8.2k | — | ~886 | Automated safety check: Pass | MIT | |
| Dignified Python Standardsdocling-project/docling | 68k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Readable Pycrazyguitar/pysheeet | 8.2k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Svelte5 Best PracticesSikandarJODD/cnblocks | 430 | 1 repos | ~810 | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Python
What does Python do?
Python 3.11+ performance optimization guidelines (formerly python-311). Python is an agent skill from pproenca/dot-skills.11+ performance optimization guidelines (formerly python-311).
When should I use Python?
Python fits situations like: tasks involving asyncio; data structures; memory management.
How do I install Python in Claude Code?
Run `npx skills add pproenca/dot-skills --skill python -a claude-code`. Or copy the skill folder (skills/.curated/python in pproenca/dot-skills) into .claude/skills/python in your project. Claude Code loads it when a task matches its description.
How do I install Python in Codex?
Run `npx skills add pproenca/dot-skills --skill python -a codex`. Or copy the skill folder (skills/.curated/python in pproenca/dot-skills) into .agents/skills/python in your project. Codex loads it when a task matches its description.
Can I use Python 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 pproenca/dot-skills --skill python -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, .gemini/skills/python, .github/skills/python and .opencode/skills/python in your project.
What does Python need to run?
SKILL.md names no scripts, command-line tools or credentials: Python is instructions for the agent only. Our summary lists: Python 3.
Does Python access the network?
SKILL.md names 7 domains. As links in the text: realpython.com, docs.python.org, peps.python.org, wiki.python.org, github.com, datacamp.com and blog.jetbrains.com. This is read from the text; nothing was executed.
Is Python 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 use?
Python 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 use?
About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16k tokens, read only when the agent opens those files.
What are the alternatives to Python?
Skills that share tags, products or a category with Python: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Py (crazyguitar/pysheeet, 8.2k stars), Dignified Python Standards (docling-project/docling, 68k stars) and Readable Py (crazyguitar/pysheeet, 8.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Python?
pproenca (a GitHub user) maintains it in pproenca/dot-skills, which has 214 GitHub stars. The repository holds 182 skills in this directory. The repository was last updated on August 15, 2026.
Source: pproenca/dot-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.