cursorrules

A set of coding rules for a Python web service built with FastAPI. It defines how to manage packages, format and type-check code, handle database access and secrets, and test endpoints.

In plain words
What is it for?
Use it when adding or changing FastAPI endpoints, database queries, configuration, dependencies, or tests in a Python 3.12 project using uv.
Why use it?
It gives an agent consistent project guidance and helps prevent common problems such as blocking web requests, untyped data, exposed credentials, and incomplete tests.

Cursor rule for Cursor

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 rules/seanleecoder/rule-trace/cursorrules
Clone the repo
git clone --depth 1 https://github.com/seanleecoder/rule-trace

Made for: Cursor.

Per session 159 This file is loaded in full into every session.
When invoked 159 The same file — it is already loaded in full.
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 $0.00159 $0.00159
Opus 5 $0.00079 $0.00079
Sonnet 5 $0.00032 $0.00032
Haiku 4.5 $0.00016 $0.00016

Measured yesterday against content hash eb5f429f5e74, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cursorrules 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.

evals/fixtures/cursorrules/.cursorrules · 10 lines

What it actually says

You are working on a Python FastAPI service.

Conventions:

  1. Python 3.12. Dependencies are managed with uv; add packages with uv add, never edit requirements by hand.
  2. Format with ruff and run ruff check --fix before committing. Type-check with mypy in strict mode.
  3. Every endpoint must have a Pydantic request and response model — no raw dicts in or out.
  4. All database queries are async (SQLAlchemy async session). Never block the event loop with sync I/O.
  5. Secrets come from environment variables loaded via the settings module; never hardcode credentials or read os.environ directly in handlers.
  6. Tests use pytest and must cover both the happy path and at least one failure path for each endpoint.
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 · 10 lines · 159 tokens per session scan A eb5f429f5e74

Subscribe to this mod's changes

cursorrules is a cursor rule published in the GitHub repository seanleecoder/rule-trace (5 stars, last pushed 1mo ago), licensed MIT. It adds 159 tokens to every session, about $0.0008 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.