Borrowing it
Nothing to install: this file belongs to himanshugoel2797/LLMarr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/himanshugoel2797/LLMarr/main/AGENTS.mdgit clone --depth 1 https://github.com/himanshugoel2797/LLMarrWrote 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/instructions/himanshugoel2797/llmarr/agents-md)<a href="https://agentmods.dev/instructions/himanshugoel2797/llmarr/agents-md"><img src="https://agentmods.dev/badge/instructions/himanshugoel2797/llmarr/agents-md.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 | $0.03838 | $0.03838 |
| Opus 5 | $0.01919 | $0.01919 |
| Sonnet 5 | $0.00768 | $0.00768 |
| Haiku 4.5 | $0.00384 | $0.00384 |
Grade A, and why
LLMarr AGENTS.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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — guidance for coding agents working on LLMarr
LLMarr is an MCP server that replicates Sonarr/Radarr-style media automation but is driven entirely by an LLM: TMDB metadata → Prowlarr torrent search → qBittorrent grab → hardlink import into an organised library → Plex scan, plus a background RSS auto-grab loop. TV and movies are both supported. Prowlarr is assumed to be available.
Ground rules
- Python 3.11+, stdlib style. Match the surrounding code: type hints,
from __future__ import annotations, module-level docstrings explaining why. - Everything is configurable through MCP tools. If you add a setting, add the config field and a tool to change it, and make sure it round-trips through the YAML store.
- Never break offline testability. All network I/O goes through a small
number of seams (see below) that tests fake. Don't call
httpx/clients from places that can't be mocked. - Run
pytestbefore finishing. Keep it green and add tests for new behaviour.
Layout
llmarr/
config.py pydantic models + ConfigStore (YAML, thread-safe, secret redaction)
db.py SQLite: series, episodes, movies, downloads, grab_history, kv (+ migrations)
pathmap.py translate() paths between container namespaces (single-host = passthrough)
metadata/ MetadataProvider ABC + TMDB (TV+movies) + Jikan/Tenrai (anime)
indexers/ Prowlarr search client + Release model
download/ DownloadClient ABC + qBittorrent (resolves .torrent host-side)
notify/ Plex library scan + catalog + show_episodes
importer.py hardlink/copy/move into <root>/Show (Year)/Season NN/… + movie layout
selector.py quality filter + ranking (lightweight, NOT Sonarr custom formats)
parsing.py SxxExx / season-pack / resolution / anime absolute+range parsing
core.py App engine — the glue used by BOTH tools and the RSS poller
rss/poller.py asyncio background loop (auto-grab + import), reads config each tick
auth.py mode-aware bearer/OAuth middleware for the HTTP transport
oauth.py self-contained OAuth 2.1 authorization + resource server
plexauth.py plex.tv PIN (browser) login flow
setup.py build_status() — powers the setup_status onboarding tool
server.py FastMCP instance + all ~54 tools + lifespan (starts poller)
__main__.py stdio (default) or streamable-http entrypoint
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.
- 7d ago First seen · 235 lines · 3,838 tokens per session scan A d7b20142b0f3
LLMarr AGENTS.md is an instructions file published in the GitHub repository himanshugoel2797/LLMarr (0 stars, last pushed 1mo ago), licensed MIT. It adds 3,838 tokens to every session, about $0.0192 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.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.