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 skills add NicoGenti/opencode-orchestrator-kit --skill python-conventionsgit clone --depth 1 https://github.com/NicoGenti/opencode-orchestrator-kitWrote 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/nicogenti/opencode-orchestrator-kit/python-conventions)<a href="https://agentmods.dev/skills/nicogenti/opencode-orchestrator-kit/python-conventions"><img src="https://agentmods.dev/badge/skills/nicogenti/opencode-orchestrator-kit/python-conventions/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nicogenti/opencode-orchestrator-kit/python-conventions"><img src="https://agentmods.dev/badge/skills/nicogenti/opencode-orchestrator-kit/python-conventions.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.00433 |
| Opus 5.5 | $0.00013 | $0.00173 |
| Sonnet 5.5 | $0.00006 | $0.00087 |
| Haiku 4.5 | $0.00003 | $0.00043 |
Grade A, and why
python-conventions 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 1mo 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.
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.
What it actually says
Python Conventions
Based on PEP 8, the official Python style guide [web:74].
Naming
lower_case_with_underscoresfor functions and variables [web:87].CapitalizedWords(PascalCase) for classes [web:87].UPPERCASE_WITH_UNDERSCORESfor constants [web:87].- Always use
selfas the first argument of instance methods [web:84].
Formatting
- 4 spaces per indentation level; never mix tabs and spaces [web:74][web:84].
- Limit lines to 79 characters for code, 72 for docstrings/comments — relax this ceiling only if the project's linter config already does (e.g., Black's 88-char default) [web:74].
- Two blank lines around top-level functions and classes; one blank line between methods inside a class [web:74].
- One space around operators; no space immediately inside parentheses/brackets [web:87].
- Pick one quote style (single or double) and use it consistently across the codebase [web:87].
Imports
- Order: standard library, then third-party, then local application imports, each group separated by a blank line [web:87][web:84].
- Prefer one import per line; use explicit
from module import nameonly when it improves clarity.
Structure
- Use type hints on public function signatures.
- Use docstrings for modules, classes, and public functions describing purpose, not implementation.
- Keep functions focused; if a function mixes multiple responsibilities, split it.
When Reviewing
Flag mixed tabs/spaces, inconsistent quote style, and missing type hints on public APIs ahead of line-length nits if the project has its own formatter (Black/Ruff) already configured — defer to that tool's config over strict PEP 8 line length.
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.
- 1mo ago First seen · 41 lines · 32 tokens per session scan A 42768a99ba81
python-conventions is a skill published in the GitHub repository NicoGenti/opencode-orchestrator-kit (7 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 433 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
demo-1-terminal-arcade
Demo skill that builds a colorful, playable terminal Snake game in a single pure-stdlib Python curses file — score HUD, speed ramp, eat/death animations, and a game-over screen.
backend-development
A general guide for building backend services, which are the server-side programs that handle data, business rules, and APIs. It switches between Python, Node.js, Go, and Java guidance based on the requested technology.
nodriver
Write Python browser automation scripts using nodriver (undetected Chrome DevTools Protocol). Use when: writing web scrapers, automating logins, filling forms, bypassing anti-bot systems (Cloudflare, Captcha), taking screenshots, managing cookies, or any browser automation that needs to avoid detection. Triggers on…
goga-cell-python
Python rules for implementing CODEMANIFEST contracts.
backend-development-python
A Python backend development guide covering FastAPI, Django, Flask, data validation, database access, migrations, and browser automation. Python is a programming language; a backend is the server-side code behind an application or API.
python-services
Python patterns for CLI tools, async concurrency, and backend services. Use when working with Python code, building CLI apps, FastAPI services, async with asyncio, background jobs, or configuring uv, ruff, ty, pytest, or pyproject.toml.