python-stack

A set of Python project patterns for AI tools, data apps, API servers, and automation. It covers frameworks such as FastAPI, Streamlit, Gradio, and LangChain, plus scraping tools and virtual environments.

In plain words
What is it for?
Use it to build Python APIs, AI or retrieval apps, data dashboards, chatbots, and browser or web-scraping automation.
Why use it?
It provides stack and setup guidance for Python projects and helps avoid applying web-only Node.js practices to them.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/ccivlcid/vibeharness/python-stack
Any agent
npx skills add ccivlcid/VibeHarness --skill python-stack
Clone the repo
git clone --depth 1 https://github.com/ccivlcid/VibeHarness

Made for: Claude Code, Codex.

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 607 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00064 $0.00607
Opus 5 $0.00032 $0.00303
Sonnet 5 $0.00013 $0.00121
Haiku 4.5 $0.00006 $0.00061

Measured yesterday against content hash 86e291fc51bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-stack 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 yesterday.

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.

.agent/skills/python-stack/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python — AI, Data, Automation

Do not apply to Node.js web-only projects. Verify stack matches PROJECT_RULES.md. Record architecture decisions in docs/ai-dev/.

Stack by Project Type

Type Stack Install
AI/RAG/Chatbot FastAPI + LangChain + ChromaDB pip install fastapi uvicorn langchain openai chromadb
Data analysis Streamlit + Pandas + Plotly pip install streamlit pandas plotly
API server FastAPI + SQLAlchemy pip install fastapi uvicorn sqlalchemy
Automation BeautifulSoup/Playwright pip install beautifulsoup4 requests playwright

Initial Setup

python -m venv venv

# Mac/Linux:
source venv/bin/activate
# Windows:
venv\Scripts\activate

pip install -r requirements.txt

Always provide the correct activation command for the user's OS.

FastAPI Pattern

from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles

app = FastAPI()
app.mount("/static", StaticFiles(directory="static"), name="static")

@app.get("/api/hello")
async def hello():
    return {"message": "Hello!"}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)

Streamlit Pattern

import streamlit as st
import pandas as pd

st.title("Dashboard")
uploaded = st.file_uploader("Upload CSV", type="csv")
if uploaded:
    df = pd.read_csv(uploaded)
    st.dataframe(df)
    st.bar_chart(df)

SQLite + SQLAlchemy

from sqlalchemy import create_engine, Column, String, DateTime
from sqlalchemy.orm import declarative_base, sessionmaker

engine = create_engine("sqlite:///dev.db")
Base = declarative_base()
SessionLocal = sessionmaker(bind=engine)

Environment Variables

from dotenv import load_dotenv
import os
load_dotenv()
api_key = os.getenv("OPENAI_API_KEY")

Code Conventions

  • snake_case (functions, variables), PascalCase (classes)
  • Type hints required: def get_user(user_id: str) -> User:
  • f-strings: f"Hello {name}"
  • Pin versions in requirements.txt

Read the full file on GitHub · 97 lines

Changes

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.

  1. yesterday First seen · 97 lines · 64 tokens per session scan A 86e291fc51bf

Subscribe to this mod's changes

python-stack is a skill published in the GitHub repository ccivlcid/VibeHarness (5 stars, last pushed 4mo ago), licensed MIT. It adds 64 tokens to every session and 607 once invoked, about $0.0003 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens