Borrowing it
Nothing to install: this file belongs to brilliantlabsAR/brilliant_sdk. 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/brilliantlabsAR/brilliant_sdk/main/.claude/skills/glasses-app/SKILL.mdgit clone --depth 1 https://github.com/brilliantlabsAR/brilliant_sdkWrote 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/brilliantlabsar/brilliant_sdk/glasses-app)<a href="https://agentmods.dev/skills/brilliantlabsar/brilliant_sdk/glasses-app"><img src="https://agentmods.dev/badge/skills/brilliantlabsar/brilliant_sdk/glasses-app/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/brilliantlabsar/brilliant_sdk/glasses-app"><img src="https://agentmods.dev/badge/skills/brilliantlabsar/brilliant_sdk/glasses-app.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 | $0.00063 | $0.01270 |
| Opus 5 | $0.00032 | $0.00635 |
| Sonnet 5 | $0.00013 | $0.00254 |
| Haiku 4.5 | $0.00006 | $0.00127 |
Grade A, and why
glasses-app 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 11d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building a glasses app
Every app is two programs: a host program (Python / Dart / TypeScript) and a device-side Lua app running in the glasses' Lua 5.4 VM. They exchange messages over BLE, identified by a single-byte message code that must match on both sides. Get this pairing right and everything else is bookkeeping.
Choose the path
- Just poking the device (show text, read battery, run a Lua snippet)?
Use the
*_blelayer alone and send raw Lua to the REPL — no Lua app needed. Seepython/packages/brilliant_ble/examples/hello_world.py. - A real app (camera, audio, sprites, IMU, interaction)? Use the
*_msglayer and the lifecycle below. - Copy an existing example rather than starting blank — indexes:
python/packages/brilliant_msg/examples/EXAMPLES.md,flutter/packages/simple_brilliant_app/example/EXAMPLES.md,webbluetooth/packages/brilliant-msg/example/EXAMPLES.md.
Per-SDK minimal working apps with file-by-file explanations:
- references/python-quickstart.md
- references/flutter-quickstart.md
- references/webbluetooth-quickstart.md
On-device API: references/frame-api.md (condensed
frame.* reference and Halo/Frame differences).
The canonical lifecycle (identical in all SDKs; camelCase in Dart/TS)
connect()
upload_stdlua_libs(['data', <per-message-type libs>]) # e.g. 'plain_text', 'camera'
upload_frame_app('lua/<name>_frame_app.lua') # your device-side app
attach_print_response_handler() # see device print()/errors
start_frame_app() # runs it; blocks until it prints ready
send_message(code, msg.pack()) / attach Rx receivers # the app conversation
stop_frame_app(); disconnect()
The data Lua lib is always needed: it reassembles BLE-chunked messages into
data.app_data[code] (or raw items) on the device. Each Tx*/Rx* message
class has a same-named Lua lib that parses/renders it — upload the ones you
use. While the frame app runs, the REPL is busy: no more raw send_lua()
without a break signal.
What ships with it
4 files 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.
- 11d ago First seen · 102 lines · 63 tokens per session scan A 71c55e0bad23
glasses-app is a skill published in the GitHub repository brilliantlabsAR/brilliant_sdk (101 stars, last pushed 15d ago), licensed BSD-3-Clause. It adds 63 tokens to every session and 1,270 once invoked, about $0.0003 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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