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.
git clone --depth 1 https://github.com/nexus-labs-automation/mobile-observabilityWrote 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/commands/nexus-labs-automation/mobile-observability/instrument)<a href="https://agentmods.dev/commands/nexus-labs-automation/mobile-observability/instrument"><img src="https://agentmods.dev/badge/commands/nexus-labs-automation/mobile-observability/instrument/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/commands/nexus-labs-automation/mobile-observability/instrument"><img src="https://agentmods.dev/badge/commands/nexus-labs-automation/mobile-observability/instrument.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 | $0.00000 | $0.01274 |
| Opus 5 | $0.00000 | $0.00637 |
| Sonnet 5 | $0.00000 | $0.00255 |
| Haiku 4.5 | $0.00000 | $0.00127 |
Grade A, and why
instrument 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.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrument Command
Generate a comprehensive instrumentation plan for a mobile codebase.
Usage
/instrument [platform] [--vendor=<vendor>]
Arguments:
platform:ios,android,react-native,flutter, orauto(detect from codebase)- Invalid values: Error with "Invalid platform. Use: ios|android|react-native|flutter|auto"
--vendor: Optional.sentry,datadog,embrace,bugsnag,bitdrift,firebase,newrelic,opentelemetry,measure- Format:
--vendor=sentryor--vendor sentry(both accepted) - Invalid values: Warning with "Unknown vendor, using generic patterns"
- Format:
Examples:
/instrument ios
/instrument android --vendor=sentry
/instrument flutter --vendor=firebase
/instrument auto
Workflow
Step 1: Detect Platform
If platform is auto or not specified:
- Search for platform indicators:
- iOS:
*.swift,*.xcodeproj,Podfile,Package.swift - Android:
*.kt,build.gradle,AndroidManifest.xml - React Native:
react-nativeinpackage.json,metro.config.js - Flutter:
flutterinpubspec.yaml,lib/main.dart
- iOS:
- If multiple platforms detected (e.g., React Native or Flutter with native modules):
- Default to highest-level platform (Flutter/React Native > native)
- Inform user: "Detected [Flutter/React Native] with iOS/Android modules. Use
/instrument [flutter/react-native]or/instrument iosfor native-only."
- If no platform detected:
- Error: "Unable to detect platform. Please specify:
/instrument ios|android|react-native|flutter" - Show project structure to help diagnose
- Error: "Unable to detect platform. Please specify:
- Confirm with user if ambiguous
Step 2: Analyze Codebase
Launch the codebase-analyzer agent to identify:
- Entry points (AppDelegate, Application class, App component)
- Architecture patterns (MVVM, TCA, MVI, etc.)
- Navigation layer
- Network layer
- Data persistence
- Existing telemetry (if any)
Step 3: Load Reference Context
Based on detected platform, read:
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 · 171 lines · 0 tokens per session scan A c2894524bcea
instrument is a command published in the GitHub repository nexus-labs-automation/mobile-observability (116 stars, last pushed 17d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,274 tokens. 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.
Other commands, from other repositories
feature-learn
View and manage patterns learned from feature builds. Shows extracted instincts, confidence scores, and feature completeness history.
feature-build
Build a complete mobile feature from description to running code with E2E tests. Orchestrates 6 phases - planning, implementation, testing, build-fix, quality gate, and verification. Auto-detects platform.
feature-plan
Plan a mobile feature with architecture decisions, file breakdown, dependency analysis, and test strategy. Produces a structured plan document reviewed by an architecture agent.
feature-implement
Implement a planned mobile feature using parallel specialized agents for network, data, architecture, UI, and wiring layers. Requires an approved feature plan.
feature-status
Show the current status of a feature build - which phase is active, what has completed, what remains, and any blockers.
feature-test
Create all tests for an implemented feature - unit tests (ViewModel, UseCase, Repository), Compose UI tests, and E2E user flow tests.