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/robhowley/py-pit-skills/dockerize-servicenpx skills add robhowley/py-pit-skills --skill dockerize-servicegit clone --depth 1 https://github.com/robhowley/py-pit-skillsWrote 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/robhowley/py-pit-skills/dockerize-service)<a href="https://agentmods.dev/skills/robhowley/py-pit-skills/dockerize-service"><img src="https://agentmods.dev/badge/skills/robhowley/py-pit-skills/dockerize-service.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 | $0.00040 | $0.02638 |
| Opus 5 | $0.00020 | $0.01319 |
| Sonnet 5 | $0.00008 | $0.00528 |
| Haiku 4.5 | $0.00004 | $0.00264 |
Grade A, and why
dockerize-service scanned grade A with 1 finding 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 6d ago.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000{detected_path}')" How it starts
The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: dockerize-service
Core position
This skill produces a local-development Docker Compose setup that reflects the project as-is. It does not introduce backing services the repo doesn't already use, and it does not create a second Docker pattern if one already exists.
Trigger
Use this skill when the user wants to:
- Containerize an existing Python project
- Add Docker Compose to a project
- Add a Dockerfile to a project
- "Dockerize" a service
Variables
{pkg_name}— snake_case package name (matches the project directory and Python package){PKG_NAME}_— env var prefix, only used if a pydantic-settingsenv_prefixis detected in the repo (e.g.,MY_SERVICE_); otherwise plain names are used
Step 1 — Inspect the repo
Inspect before asking. Work through each check in order and record findings.
1. Check for existing Docker artifacts
Look for Dockerfile, docker-compose.yml, docker-compose.yaml, .dockerignore. If any are present, extend them — do not create a competing setup. Note what was found.
2. Check for repo tooling
uv.lockpresent → uv-native project; use uv base image in Dockerfile- No
uv.lock→ pip-based project; usepython:3.12-slimwithpip install
3. Check for service signals
Inspect pyproject.toml dependencies and any settings/config files for:
sqlalchemy+ a non-sqlite database URL pattern, orpsycopg,psycopg2,asyncpgin deps → Postgresredisin deps → Redis- No signals → app-only (do not add Postgres as a default)
If Postgres is signaled, also note which driver is already present (psycopg2-binary, psycopg[binary], asyncpg, etc.) — this determines what to add in Step 6.
4. Check for an existing health endpoint
Grep routes for /health, /healthz, /ping, /api/v1/health, or similar. Record the exact path if found.
5. Detect app entrypoint
Look for the ASGI app object in {pkg_name}/main.py, {pkg_name}/app.py, or {pkg_name}/application.py. Record the module path (e.g., {pkg_name}.main:app). Also check [project.scripts] in pyproject.toml for any uvicorn/gunicorn invocations. This becomes the CMD in the Dockerfile — default to {pkg_name}.main:app only if no entrypoint is found elsewhere.
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.
- 6d ago First seen · 282 lines · 40 tokens per session scan A f9d109ce401e
dockerize-service is a skill published in the GitHub repository robhowley/py-pit-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 2,638 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
python-backend
Production Python async patterns including asyncio TaskGroup, FastAPI dependency injection and middleware, SQLAlchemy 2.0 async sessions, and database connection pool tuning. Python 3.11+ runtime concerns such as ExceptionGroup, cancellation semantics, and session rollback. Use when building async services, wiring…
python
Use when building FastAPI applications, implementing async endpoints, setting up Pydantic schemas, working with SQLAlchemy, or writing pytest tests for Python backend services.
database
Relational database authority — PostgreSQL, async ORM (SQLAlchemy 2 / asyncpg), Alembic schema migrations, Supabase Python and JS clients, query optimisation, index strategy, connection pooling, transaction patterns, and bulk operations across Python and Node stacks.
pytest
Advanced Python unit testing framework for customer support tech enablement, covering FastAPI, SQLAlchemy, PostgreSQL, async operations, mocking, fixtures, parametrization, coverage, and comprehensive testing strategies for backend support systems.
FastAPI Customer Support Tech Enablement
Comprehensive FastAPI skill for building modern Python web APIs with focus on customer support systems, ticket management, real-time chat, and backend operations.
SQLAlchemy ORM Expert
Comprehensive SQLAlchemy skill for customer support tech enablement, covering ORM patterns, session management, query optimization, async operations, and PostgreSQL integration.