speedpy AGENTS.md

A project guide for AI coding agents working on SpeedPy, a Django-based web application starter. It records the project structure, setup choices, development commands, and links to extra instructions for special tasks.

In plain words
What is it for?
Understanding the SpeedPy architecture, choosing Docker or local development steps, finding the right commands, and locating instructions for tasks such as video processing.
Why use it?
It gives an agent the repository's agreed instructions in one source of truth, reducing incorrect commands and inconsistent changes. It keeps occasional guidance out of the main file until it is needed.

Instructions file for CodexOpenCode

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 instructions/speedpy/speedpy/agents-md
Clone the repo
git clone --depth 1 https://github.com/speedpy/speedpy

Made for: Codex, OpenCode.

Per session 20,341 This file is loaded in full into every session.
When invoked 20,341 The same file — it is already loaded in full.
Security scan A 1 finding. 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 $0.20341 $0.20341
Opus 5 $0.10171 $0.10171
Sonnet 5 $0.04068 $0.04068
Haiku 4.5 $0.02034 $0.02034

Measured 2d ago against content hash eeb46ed1129e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

speedpy AGENTS.md 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 2d 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.

curl -sS -o speedpycom/data/disposable_email_blocklist.conf \
AGENTS.md · 1,747 lines

How it starts

The opening of the file, as written. The whole thing — 1,747 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file is the source of truth for AI Coding Agents working in this repository. CLAUDE.md and .cursorrules exist only as pointers to this file — keep guidance here.

Additional case-specific instructions

Read the matching file before you start, if your task is one of these. They live outside this file so that a capability most projects never touch does not cost every reader the tokens to scroll past it.

  • video manipulation, transcoding, compression, video upload, ffmpeg: agents_docs/working_with_video_files.md

Adding one: keep the file in agents_docs/, name it for the task rather than the technology (working_with_<thing>.md), and add exactly one bullet here — searchable words first, path last. Anything a project would only sometimes need belongs there, not in this file.

Project Overview

SpeedPy Standard is a Django-based web application starter template featuring a single-app architecture with custom user authentication, Celery for background tasks, and Tailwind CSS for styling. The project supports two development modes — Docker Compose or local uv + npm — picked at init time.

Development Commands

For mode-specific run commands (Django management, Tailwind, migrations, tests, shell access, etc.) read AGENTS-local.md in this directory. It is populated by init-docker.sh or init-local.sh and reflects the active setup. Do not assume a particular wrapper (docker compose run vs uv run) — the cheat sheet is the source of truth for invocation.

Initialization scripts:

  • bash init-docker.sh — boots the project with Docker Compose (Postgres, Redis, Celery, nginx media).
  • bash init-local.sh — runs the project on the host with uv + npm, SQLite, no Redis, Celery in always-eager mode.

Architecture

Apps Structure (single-app architecture)

This is a single-app Django project. All business logic ships from mainapp. Do not create a new Django app for a new feature, page, or model — extend mainapp. The only existing apps and their narrow purposes:

Read the full file on GitHub · 1,747 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. 2d ago First seen · 1,747 lines · 20,341 tokens per session scan A eeb46ed1129e

Subscribe to this mod's changes

speedpy AGENTS.md is an instructions file published in the GitHub repository speedpy/speedpy (79 stars, last pushed 2d ago), licensed MIT. It adds 20,341 tokens to every session, about $0.1017 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 2026-08-30.

Related

Other instructions, from other repositories