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.
npx skills add autonomous-ai/autonomous-os --skill scenegit clone --depth 1 https://github.com/autonomous-ai/autonomous-osWrote 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/skills/autonomous-ai/autonomous-os/scene)<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/scene"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/scene/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/scene"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/scene.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.01139 |
| Opus 5.5 | $0.00023 | $0.00456 |
| Sonnet 5.5 | $0.00012 | $0.00228 |
| Haiku 4.5 | $0.00006 | $0.00114 |
Grade A, and why
scene scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**No exec/curl needed.** Inline marker at start of reply: How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lighting Scenes
Quick Start
Activate predefined lighting presets that set optimal color temperature and brightness for specific activities. Use this for ALL activity-based or environment lighting requests.
Workflow
- Determine which scene matches the user's request or activity
- Prefix reply with
[HW:/scene:{"scene":"name"}]— the device fires it before TTS - Confirm the scene activation to the user
- Optionally chain emotion:
[HW:/scene:{"scene":"night"}][HW:/emotion:{"emotion":"sleepy","intensity":0.7}]
Examples
Input: "Reading mode"
Output: [HW:/scene:{"scene":"reading"}] Reading mode activated — 80% brightness, neutral white.
Input: "Goodnight" / "good night" / "time to sleep"
Output: [HW:/scene:{"scene":"night"}][HW:/emotion:{"emotion":"sleepy","intensity":0.7}] Night mode on. Sweet dreams!
Input: "I want to relax" / "let me chill"
Output: [HW:/scene:{"scene":"relax"}] Relax mode — warm, gentle light at 40%.
Input: "Movie time" / "watching a movie"
Output: [HW:/scene:{"scene":"movie"}] Movie mode — dim amber bias lighting.
Input: "I need to focus"
Output: [HW:/scene:{"scene":"focus"}] Focus mode — full brightness, cool white.
Input: "Make it purple" Output: Do NOT use this skill. Use LED Control skill instead.
Input: Conversational reply needing emotion Output: Do NOT use this skill for emotion. Use Emotion skill instead (you CAN use both Scene + Emotion together).
How to Activate a Scene
No exec/curl needed. Inline marker at start of reply:
[HW:/scene:{"scene":"reading"}] Reading mode activated.
[HW:/scene:{"scene":"night"}][HW:/emotion:{"emotion":"sleepy","intensity":0.7}] Night mode on. Sweet dreams!
Available scenes
| Scene | Brightness | Color Temp | Best for |
|---|---|---|---|
reading |
80% | ~4000K neutral white | Reading, studying, desk work |
focus |
100% | ~5000K cool white | Deep work, coding, no distractions |
relax |
40% | ~2700K warm | Winding down, casual chat |
movie |
15% | ~2700K dim amber | Watching videos, bias lighting |
night |
5% | ~2200K very warm | Sleep-friendly, minimal light |
energize |
100% | ~6500K daylight | Morning wake-up, need energy |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed 04a387e56086
- 1mo ago First seen · 87 lines · 58 tokens per session scan A d47424f33879
scene is a skill published in the GitHub repository autonomous-ai/autonomous-os (378 stars, last pushed 18d ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,139 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
rosclaw-embodied
A set of rules for completing robot tasks in ROSClaw, a system for running and checking robot work. It covers approved robot files, acceptance evidence, and separate rules for simulation and real hardware.
srdf
MoveIt2 SRDF authoring, validation, and planning-semantics workflow. Use when creating, editing, inspecting, or validating .srdf files, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-paired planning semantics, or SRDF handoff for live review. Use the URDF…
urdf
URDF robot description authoring and validation. Use when creating, editing, inspecting, validating, or debugging .urdf files, robot links, joints, limits, inertials, visual/collision geometry, mesh references, frame conventions, or robot-description artifacts. Use the SRDF skill for MoveIt2 semantic groups and…
step-parts
Find, evaluate, and download common purchasable CAD parts from step.parts, including named off-the-shelf actuators, servos, motors, electronics boards, connectors, screws, bolts, nuts, washers, bearings, standoffs, and other catalog components. Use when Codex needs to search the hosted step.parts catalog before…
gcode
Slice 3D models into printer-ready G-code with OrcaSlicer, the open-source slicer with built-in profiles for most FDM printers (Prusa, Bambu Lab, Creality, Voron and more). Use when the user wants an .stl, .3mf or .obj model sliced for their printer, as a sliced .gcode.3mf or plain .gcode, headless with OrcaSlicer's…
evaluating-cosmos-policy
Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.