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 skills/laurigates/claude-plugins/python-containersnpx skills add laurigates/claude-plugins --skill python-containersgit clone --depth 1 https://github.com/laurigates/claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/laurigates/claude-plugins/python-containers)<a href="https://agentmods.dev/skills/laurigates/claude-plugins/python-containers"><img src="https://agentmods.dev/badge/skills/laurigates/claude-plugins/python-containers.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.02198 |
| Opus 5 | $0.00025 | $0.01099 |
| Sonnet 5 | $0.00010 | $0.00440 |
| Haiku 4.5 | $0.00005 | $0.00220 |
Grade C, and why
python-containers scanned grade C with 2 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
&& rm -rf /var/lib/apt/lists/* Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
HEALTHCHECK --interval=30s CMD python -c "import requests; requests.get('http://localhost:8000/health')" || exit 1 How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Container Optimization
Expert knowledge for building optimized Python container images using slim base images, virtual environments, modern package managers (uv, poetry), and multi-stage build patterns.
When to Use This Skill
| Use this skill when... | Use container-development instead when... |
|---|---|
| Building Python-specific Dockerfiles | General multi-stage build patterns |
| Optimizing Python image sizes | Language-agnostic container security |
| Handling pip/poetry/uv in containers | Docker Compose configuration |
| Dealing with musl/glibc issues | Non-Python container optimization |
Core Expertise
Python Container Challenges:
- Large base images with unnecessary packages (~1GB)
- Critical: Alpine causes issues with Python (musl vs glibc)
- Complex dependency management (pip, poetry, pipenv, uv)
- Compiled C extensions requiring build tools
- Virtual environment handling in containers
Key Capabilities:
- Slim-based images (NOT Alpine for Python)
- Multi-stage builds with modern tools (uv recommended)
- Virtual environment optimization
- Compiled extension handling
- Non-root user configuration
Why NOT Alpine for Python
Use slim instead of Alpine for Python containers. Alpine uses musl libc which causes:
- Many wheels don't work (numpy, pandas, scipy)
- Forces compilation from source (slow builds)
- Larger final images due to build tools
- Runtime errors with native extensions
Optimized Dockerfile Pattern (uv)
The recommended pattern achieves ~80-120MB images:
# Both stages MUST share this interpreter version — see below.
ARG PYTHON_VERSION=3.11
# Build stage
FROM python:${PYTHON_VERSION}-slim AS builder
WORKDIR /app
RUN pip install --no-cache-dir uv
# Copy dependency files
COPY pyproject.toml uv.lock ./
# Install dependencies with uv (much faster than pip)
RUN uv sync --frozen --no-dev
COPY . .
# Runtime stage
FROM python:${PYTHON_VERSION}-slim
WORKDIR /app
# Install only runtime dependencies (if needed)
RUN apt-get update && \
apt-get install -y --no-install-recommends \
libpq5 \
&& rm -rf /var/lib/apt/lists/*
# Create non-root user
RUN addgroup --gid 1001 appgroup && \
adduser --uid 1001 --gid 1001 --disabled-password appuser
# Copy only what's needed
COPY --from=builder --chown=appuser:appgroup /app/.venv /app/.venv
COPY --chown=appuser:appgroup app/ /app/app/
COPY --chown=appuser:appgroup pyproject.toml /app/
ENV PATH="/app/.venv/bin:$PATH" \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1
USER appuser
EXPOSE 8000
HEALTHCHECK --interval=30s CMD python -c "import requests; requests.get('http://localhost:8000/health')" || exit 1
CMD ["python", "-m", "app"]
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 227 lines · 50 tokens per session scan C 76d0476afd84
python-containers is a skill published in the GitHub repository laurigates/claude-plugins (58 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 2,198 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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