LetterFeed GEMINI.md

LetterFeed GEMINI.md is an instructions file for Gemini CLI from LeonMusCoden/LetterFeed. It costs 4,254 tokens per session, scanned A, original, MIT.

Project-specific instructions for the LetterFeed repository, whose backend uses FastAPI and whose frontend uses React with TypeScript. It lists commands and conventions for working across both parts of the application.

In plain words
What is it for?
Use it to start development servers, run tests and linting, build or run Docker environments, clean generated files, and follow existing test and mock conventions.
Why use it?
It gives coding agents a single reference for installing dependencies, running services, testing, linting, and using Docker, reducing guesswork about the repository's workflow.

Instructions file for Gemini CLI

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/leonmuscoden/letterfeed/gemini-md
Clone the repo
git clone --depth 1 https://github.com/LeonMusCoden/LetterFeed

Made for: Gemini CLI.

Wrote 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.

agentmods badge for LetterFeed GEMINI.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/leonmuscoden/letterfeed/gemini-md.svg)](https://agentmods.dev/instructions/leonmuscoden/letterfeed/gemini-md)
Your own site
<a href="https://agentmods.dev/instructions/leonmuscoden/letterfeed/gemini-md"><img src="https://agentmods.dev/badge/instructions/leonmuscoden/letterfeed/gemini-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 4,254 This file is loaded in full into every session.
When invoked 4,254 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 $0.04254 $0.04254
Opus 5 $0.02127 $0.02127
Sonnet 5 $0.00851 $0.00851
Haiku 4.5 $0.00425 $0.00425

Measured today against content hash 86ef8a40d7dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

LetterFeed GEMINI.md 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 today.

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.

GEMINI.md · 220 lines

How it starts

The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gemini Added Memories

  • ./backend contains the FastAPI backend. It uses uv as package manager.
  • ./frontend contains the TS React frontend. It uses ShadCN components.

Useful commands:

Run make with these targets: install Install all dependencies for frontend and backend dev Start the development servers for frontend and backend test Run tests for frontend and backend lint Lint the frontend and backend code docker-build Build the production Docker images docker-up Start the production application with Docker Compose docker-down Stop the production application docker-dev-up Start the development environment with Docker Compose docker-dev-down Stop the development environment clean Remove generated files and caches

Writing Tests

General Guidance

  • When adding tests, first examine existing tests to understand and conform to established conventions.
  • Pay close attention to the mocks at the top of existing test files; they reveal critical dependencies and how they are managed in a test environment.

Git Repo

The main branch for this project is called "master"

Backend

Of course. Here is a similar markdown for an AI agent on how to write Python code for a backend with FastAPI, SQLAlchemy, and Alembic:

Backend

When contributing to this Python, FastAPI, and SQLAlchemy codebase, please adhere to the following principles to ensure the code is robust, maintainable, and performs well. The focus is on leveraging modern Python features, functional programming concepts, and the specific strengths of our chosen frameworks.

Prefer Functional Approaches and Data Classes over Traditional Classes

While Python is a multi-paradigm language that fully supports object-oriented programming, for our backend services, we favor a more functional approach, especially for business logic and data handling.

Read the full file on GitHub · 220 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. today First seen · 220 lines · 4,254 tokens per session scan A 86ef8a40d7dc

Subscribe to this mod's changes

LetterFeed GEMINI.md is an instructions file published in the GitHub repository LeonMusCoden/LetterFeed (204 stars, last pushed 2mo ago), licensed MIT. It adds 4,254 tokens to every session, about $0.0213 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 2026-09-04.