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Agent skill

Performant Code

by vstorm-co in vstorm-co/pydantic-deepagents

Writing efficient code that handles large data and tight constraints

MITAuto-check passed

Install Performant Code

skills CLI
$ npx skills add vstorm-co/pydantic-deepagents --skill performant-code -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install vstorm-co/pydantic-deepagents performant-code --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/vstorm-co/pydantic-deepagents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/apps/cli/skills/performant-code .claude/skills/performant-code && rm -rf skills-src

Use ~/.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/

Facts

Skill name
performant-code
GitHub stars
1.1k
Token cost
~624 tokens
SKILL.md length
316 words
Files
1
Skills in repo
14
Repo updated
First seen
Licence
MIT

At a glance

Writing efficient code that handles large data and tight constraints

  • SKILL.md covers Think About Scale First, I/O Optimization, Algorithm Complexity and Language-Specific Tips, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Performant Code is an agent skill from vstorm-co/pydantic-deepagents. Writing efficient code that handles large data and tight constraints

Its SKILL.md is about 620 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with Python. The repository describes itself as: Open-source, self-hosted Claude Code - a terminal AI assistant and the Python framework behind it. Tool-calling, sandboxed execution, multi-agent teams, skills, checkpoints… The licence is MIT.

Example prompts

  • “/performant-code”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 650b592. 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

    No URLs in SKILL.md.

    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

Performant Code loads about 624 tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 316 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~21
When it runs · the whole SKILL.md, loaded when a task matches
~624

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 vstorm-co/pydantic-deepagents at commit 650b592, republished under its MIT licence (© vstorm-co). 316 words, ~624 tokens.

Download SKILL.mdSave it as .claude/skills/performant-code/SKILL.md (or your agent's skills folder).
name
performant-code
description
Writing efficient code that handles large data and tight constraints
tags
performance, optimization, benchmark
version
1.0.0

Performant Code

How to write code that won't timeout on large inputs.

Think About Scale First

Before writing code, ask: how big is the data?

Data sizeApproach
< 1 MBLoad into memory, any approach works
1-100 MBLoad into memory, but use efficient algorithms
100 MB - 1 GBStream/mmap, avoid loading entirely into memory
> 1 GBStreaming only, chunk-based processing

I/O Optimization

Large files
  • mmap (C: mmap(), Python: mmap.mmap()) — map file into memory, OS handles paging
  • Buffered binary reads — fread() in C, open(f, 'rb').read(chunk) in Python
  • NEVER read a 500MB file line-by-line with fgets() when you need random access
Writing output
  • Buffer writes — don't call write() for every byte
  • Use fwrite() or sys.stdout.buffer.write() for binary output
  • Flush only when needed

Algorithm Complexity

  • O(n) beats O(n log n) beats O(n²) — always
  • Nested loops on large data = timeout. Restructure to single pass + hash map
  • Sorting is O(n log n) — only sort if you need to
  • Use hash maps/sets for lookup instead of linear search
  • Pre-compute what you can outside loops

Language-Specific Tips

C
  • Use mmap() for large file access
  • -O2 or -O3 for compiler optimizations
  • Avoid malloc()/free() in tight loops — pre-allocate
  • Use memcpy() instead of byte-by-byte copying
  • Integer arithmetic > floating point when possible
Python
  • Use numpy for numerical work (100x faster than pure Python loops)
  • collections.Counter, defaultdict — avoid manual counting
  • List comprehensions > explicit loops
  • struct.unpack() for binary parsing
  • subprocess.run() > os.system()
  • For heavy computation: consider writing a small C program instead
General
  • Profile before optimizing — find the actual bottleneck
  • If a program hangs, it's likely: infinite loop, deadlock, or I/O bound on huge data
  • If a program is slow, check: algorithm complexity, I/O pattern, memory allocation

Constraints Awareness

  • If the task says "< 5000 bytes" — count your bytes, use wc -c
  • If there's a time limit — test with actual data, not toy inputs
  • If there's a memory limit — don't load everything into RAM
  • Always verify constraints BEFORE declaring done

© vstorm-co, 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 apps/cli/skills/performant-code of vstorm-co/pydantic-deepagents.

Open the folder on GitHubat commit 650b592

Compare with similar skills

Performant Code 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.

Performant Code compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Performant Code this skillvstorm-co/pydantic-deepagents1.1k—~624Automated safety check: PassMIT
MCP Server Builderanthropics/skills180k64 repos~2.3kAutomated safety check: PassApache-2.0
PDF Processinganthropics/skills180k48 repos~2kAutomated safety check: PassProprietary
NotebookLM Research AssistantPleasePrompto/notebooklm-skill7.8k14 repos~2.4kAutomated safety check: NotesMIT
Manim Video Productionbrowser-use/video-use28k6 repos~3kAutomated safety check: PassMIT
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT

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Works with

Questions about Performant Code

What does Performant Code do?

Writing efficient code that handles large data and tight constraints. Performant Code is an agent skill from vstorm-co/pydantic-deepagents.

How do I install Performant Code in Claude Code?

Run `npx skills add vstorm-co/pydantic-deepagents --skill performant-code -a claude-code`. Or copy the skill folder (apps/cli/skills/performant-code in vstorm-co/pydantic-deepagents) into .claude/skills/performant-code in your project. Claude Code loads it when a task matches its description.

How do I install Performant Code in Codex?

Run `npx skills add vstorm-co/pydantic-deepagents --skill performant-code -a codex`. Or copy the skill folder (apps/cli/skills/performant-code in vstorm-co/pydantic-deepagents) into .agents/skills/performant-code in your project. Codex loads it when a task matches its description.

Can I use Performant Code 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 vstorm-co/pydantic-deepagents --skill performant-code -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performant-code, .gemini/skills/performant-code, .github/skills/performant-code and .opencode/skills/performant-code in your project.

What does Performant Code need to run?

SKILL.md names no scripts, command-line tools or credentials: Performant Code is instructions for the agent only. Our summary lists: Python 3.

Does Performant Code access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Performant Code 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 Performant Code use?

Performant Code 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 Performant Code use?

About 624 tokens (SKILL.md is roughly 2.5k 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 Performant Code?

Skills that share tags, products or a category with Performant Code: MCP Server Builder (anthropics/skills, 180k stars), PDF Processing (anthropics/skills, 180k stars), NotebookLM Research Assistant (PleasePrompto/notebooklm-skill, 7.8k stars) and Manim Video Production (browser-use/video-use, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performant Code?

vstorm-co (a GitHub organization) maintains it in vstorm-co/pydantic-deepagents, which has 1,077 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 6, 2026.

Source: vstorm-co/pydantic-deepagents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.