ai-drone-toolkit: Instructions file for Codex

AGENTS.md

ai-drone-toolkit AGENTS.md is an instructions file for Codex, OpenCode from robotto-xyz/ai-drone-toolkit. It costs 3,816 tokens per session, scanned A, original, MIT.

A project guide for AI coding agents working on a toolkit for understanding and controlling drone systems. It explains the repository layout, setup commands, architecture, safety rules, and current development roadmap.

In plain words
What is it for?
Use it to orient agents in the repository, choose the right code areas, run common commands, and avoid unsafe or incorrect changes to drone data and simulation features.
Why use it?
It gives coding agents the project context and non-negotiable rules they need before changing code, reducing misunderstandings and repeated bugs.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md.

This is robotto-xyz/ai-drone-toolkit's own configuration. It tells Codex and OpenCode how to work on ai-drone-toolkit itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-drone-toolkit configures →

Reuse

Borrowing it

Nothing to install: this file belongs to robotto-xyz/ai-drone-toolkit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/robotto-xyz/ai-drone-toolkit/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/robotto-xyz/ai-drone-toolkit

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Per session 3,816 This file is loaded in full into every session.
When invoked 3,816 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.03816 $0.03816
Opus 5 $0.01908 $0.01908
Sonnet 5 $0.00763 $0.00763
Haiku 4.5 $0.00382 $0.00382

Measured 7d ago against content hash 2d7782e049ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ai-drone-toolkit 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.

AGENTS.md · 281 lines

How it starts

The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — AI Drone Toolkit

Grounding file for AI coding agents (Cursor, Claude Code, etc.) working in this repository. Read this before writing code. It encodes the architecture, the hard rules, the domain landmines, and the roadmap so suggestions land in the right place and don't reintroduce bugs we've already fixed.


1. What this project is

Robotto (https://robotto.xyz) is building "the intelligence layer for the physical world," starting with drones. This repository — AI Drone Toolkit — is the open-source flagship: a suite of Model Context Protocol (MCP) servers and libraries that let AI assistants (Cursor, Claude, etc.) understand, debug, and eventually command drone systems.

The toolkit has two product tracks:

  1. Read / diagnose — backward-looking analysis of flight data. Offline, zero-risk. Shipping today: px4-ulog-mcp (PX4 .ulg flight-log inspection).
  2. Command — natural-language → simulated drone control. The mirror image: intent → bounded action tools → PX4 SITL → telemetry back. Shipping today: px4-sitl-mcp (simulation-only PX4 SITL command). It is code-complete with simulator-free tests for the safety, frame, fleet, and connection logic; its live MAVSDK flight paths still need verification against a running PX4 SITL (see Roadmap).

The guiding product belief: two genuinely-finished, polished servers beat six toy repos. Finish things. Depth over breadth.


2. Repository layout

This is a uv workspace monorepo. Shared, MCP-agnostic logic lives in a core package; each tool is a thin, independently installable layer on top.

ai-drone-toolkit/
├── packages/
│   └── robotto-drone-core/   # Shared, MCP-AGNOSTIC parsers & utilities.
│                             # PX4 ULog parsing today; coordinate-frame,
│                             # telemetry, and SAFETY helpers as the toolkit grows.
├── tools/
│   ├── px4-ulog-mcp/         # MCP server: inspect PX4 .ulg logs.
│   └── px4-sitl-mcp/         # MCP server: command PX4 SITL only.
│                             # (future tools live here, one dir each)
├── examples/                 # Runnable scripts that drive core directly
│                             # (no MCP client needed).
├── docs/                     # Architecture & project-wide guides.
├── pyproject.toml            # Workspace root.
└── uv.lock

Read the full file on GitHub · 281 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. 7d ago First seen · 281 lines · 3,816 tokens per session scan A 2d7782e049ce

Subscribe to this mod's changes

ai-drone-toolkit AGENTS.md is an instructions file published in the GitHub repository robotto-xyz/ai-drone-toolkit (3 stars, last pushed 2mo ago), licensed MIT. It adds 3,816 tokens to every session, about $0.0191 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.

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