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 perasyudha/Nyxora --skill findmygit clone --depth 1 https://github.com/perasyudha/NyxoraWrote 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/perasyudha/nyxora/findmy)<a href="https://agentmods.dev/skills/perasyudha/nyxora/findmy"><img src="https://agentmods.dev/badge/skills/perasyudha/nyxora/findmy/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/perasyudha/nyxora/findmy"><img src="https://agentmods.dev/badge/skills/perasyudha/nyxora/findmy.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.00954 |
| Opus 5 | $0.00009 | $0.00477 |
| Sonnet 5 | $0.00003 | $0.00191 |
| Haiku 4.5 | $0.00002 | $0.00095 |
Grade A, and why
findmy 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 10d 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.
This is a copy
91% identical to findmy — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Find My (Apple)
Track Apple devices and AirTags via the FindMy.app on macOS. Since Apple doesn't provide a CLI for FindMy, this skill uses AppleScript to open the app and screen capture to read device locations.
Prerequisites
- macOS with Find My app and iCloud signed in
- Devices/AirTags already registered in Find My
- Screen Recording permission for terminal (System Settings → Privacy → Screen Recording)
- Optional but recommended: Install
peekaboofor better UI automation:brew install steipete/tap/peekaboo
When to Use
- User asks "where is my [device/cat/keys/bag]?"
- Tracking AirTag locations
- Checking device locations (iPhone, iPad, Mac, AirPods)
- Monitoring pet or item movement over time (AirTag patrol routes)
Method 1: AppleScript + Screenshot (Basic)
Open FindMy and Navigate
# Open Find My app
osascript -e 'tell application "FindMy" to activate'
# Wait for it to load
sleep 3
# Take a screenshot of the Find My window
screencapture -w -o /tmp/findmy.png
Then use vision_analyze to read the screenshot:
vision_analyze(image_url="/tmp/findmy.png", question="What devices/items are shown and what are their locations?")
Switch Between Tabs
# Switch to Devices tab
osascript -e '
tell application "System Events"
tell process "FindMy"
click button "Devices" of toolbar 1 of window 1
end tell
end tell'
# Switch to Items tab (AirTags)
osascript -e '
tell application "System Events"
tell process "FindMy"
click button "Items" of toolbar 1 of window 1
end tell
end tell'
Method 2: Peekaboo UI Automation (Recommended)
If peekaboo is installed, use it for more reliable UI interaction:
# Open Find My
osascript -e 'tell application "FindMy" to activate'
sleep 3
# Capture and annotate the UI
peekaboo see --app "FindMy" --annotate --path /tmp/findmy-ui.png
# Click on a specific device/item by element ID
peekaboo click --on B3 --app "FindMy"
# Capture the detail view
peekaboo image --app "FindMy" --path /tmp/findmy-detail.png
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.
- 10d ago First seen · 132 lines · 17 tokens per session scan A 03ee41613c1c
findmy is a skill published in the GitHub repository perasyudha/Nyxora (5 stars, last pushed 10d ago), licensed MIT. It adds 17 tokens to every session and 954 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to findmy, differing in 6 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-ransomware-payment-wallets
Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware…
amazon-alexa
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
analyzing-uefi-bootkit-persistence
Analyzes UEFI bootkit persistence mechanisms including firmware implants in SPI flash, EFI System Partition (ESP) modifications, Secure Boot bypass techniques, and UEFI variable manipulation. Covers detection of known bootkit families (BlackLotus, LoJax, MosaicRegressor, MoonBounce, CosmicStrand), ESP partition…
arm-cortex-expert
Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).
airflow-dag-patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
eide
A build tool for EIDE projects, an embedded-development extension for Visual Studio Code. It finds EIDE project settings and builds firmware using ARM CC or GCC.