Borrowing it
Nothing to install: this file belongs to habedi/omni-lpr. 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/habedi/omni-lpr/main/AGENTS.mdgit clone --depth 1 https://github.com/habedi/omni-lprWrote 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/habedi/omni-lpr/agents-md)<a href="https://agentmods.dev/instructions/habedi/omni-lpr/agents-md"><img src="https://agentmods.dev/badge/instructions/habedi/omni-lpr/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 | $0.01309 | $0.01309 |
| Opus 5 | $0.00655 | $0.00655 |
| Sonnet 5 | $0.00262 | $0.00262 |
| Haiku 4.5 | $0.00131 | $0.00131 |
Grade A, and why
omni-lpr 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 8d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to coding agents collaborating on this repository.
Mission
Omni-LPR is a self-hostable server that provides automatic license plate recognition (ALPR) capabilities. It exposes processing endpoints through a REST API and the Model Context Protocol (MCP), enabling integration with general software applications and AI agents.
Priorities, in order:
- Correctness of license plate detection, text recognition, and model configurations.
- Standard-compliant implementations of the REST API and the MCP interface.
- Test suite coverage, including unit, integration, and E2E cases.
- Structured logging, detailed error handling, and schema validation.
Core Rules
- Use English for code, comments, docs, and tests.
- Prefer small, focused changes over broad refactoring.
- Add comments only when they clarify non-obvious behavior.
- Do not add features, error handling, or abstractions beyond what is needed for the current task.
- Keep dependencies small. Do not add heavy ML libraries, external packages, or extra services without prior discussion.
Writing Style
- Use Oxford commas in inline lists: "a, b, and c" not "a, b, c".
- Do not use em dashes. Restructure the sentence, or use a colon or semicolon instead.
- Avoid colorful adjectives and adverbs. Write "graph generator" not "powerful graph generator".
- Prefer using noun phrases for checklist items, not imperative verbs. Write "negative weight detection" not "detect negative weights".
- Headings in Markdown files must be in title case: "Build from Source" not "Build from source". Minor words (a, an, the, and, but, or, for, in, on, at, to, by, of, from, and with) stay lowercase unless they are the first word.
- Write correct and complete sentences.
- Avoid made-up words, abbreviations, and colons in the middle of sentences.
- Don't use pretentious language and made-up words.
Repository Layout
src/omni_lpr/__init__.py: Package initialization and metadata.src/omni_lpr/__main__.py: CLI entry point and server startup logic.src/omni_lpr/api_models.py: Pydantic data schemas for API requests and responses.src/omni_lpr/errors.py: Exception definitions and API error handlers.src/omni_lpr/event_store.py: Client event log store.src/omni_lpr/mcp.py: MCP server implementation.src/omni_lpr/rest.py: Starlette REST API endpoints and Swagger documentation configuration.src/omni_lpr/settings.py: Application configuration settings parsing environment variables.src/omni_lpr/tools.py: Core ALPR operations, model management, and backend interfaces.tests/: Test suite containing unit, integration, and end-to-end test cases.examples/: Client integration examples for the REST and MCP endpoints.docs/: Repository documentation.Dockerfile: Deployment container definitions.Makefile: Script runner definitions for development tasks.
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.
- 8d ago First seen · 134 lines · 1,309 tokens per session scan A bcf6e5fea13c
omni-lpr AGENTS.md is an instructions file published in the GitHub repository habedi/omni-lpr (26 stars, last pushed 2mo ago), licensed MIT. It adds 1,309 tokens to every session, about $0.0065 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 2026-08-30.
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