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 johnmikel/zeno-mobile-runner --skill zmr-mobile-testinggit clone --depth 1 https://github.com/johnmikel/zeno-mobile-runnerWrote 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/johnmikel/zeno-mobile-runner/zmr-mobile-testing)<a href="https://agentmods.dev/skills/johnmikel/zeno-mobile-runner/zmr-mobile-testing"><img src="https://agentmods.dev/badge/skills/johnmikel/zeno-mobile-runner/zmr-mobile-testing/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/johnmikel/zeno-mobile-runner/zmr-mobile-testing"><img src="https://agentmods.dev/badge/skills/johnmikel/zeno-mobile-runner/zmr-mobile-testing.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 | $0.00050 | $0.01277 |
| Opus 5 | $0.00025 | $0.00639 |
| Sonnet 5 | $0.00010 | $0.00255 |
| Haiku 4.5 | $0.00005 | $0.00128 |
Grade A, and why
zmr-mobile-testing 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ZMR Mobile Testing
Use ZMR as the typed mobile control plane for agent-led app verification. Keep model reasoning outside the runner; use ZMR for device discovery, observations, actions, waits, assertions, traces, diagnostics, and redacted evidence.
Start From App-Local State
-
Look for
.zmr/config.jsonin the app checkout. -
If it is missing, scaffold it:
zmr init --app --app-id com.example.mobiletest -
Run setup diagnostics before touching a device:
zmr doctor --json --config .zmr/config.json zmr validate --json .zmr/android-smoke.json zmr validate --json .zmr/ios-smoke.json
Use zmr doctor --strict --json for CI-style gates.
Agent Session Pattern
Prefer a long-running JSON-RPC session for interactive agent work:
zmr serve --transport stdio --config .zmr/config.json --trace-dir traces/zmr-agent
Call methods in this order:
runner.capabilitiessession.createobserve.semanticSnapshotfor planning, orobserve.snapshotfor raw adapter data- one typed action, wait, or assertion
observe.semanticSnapshottrace.eventswhile the session is activetrace.exportwith redaction enabledsession.close
Do not scrape terminal output when CLI JSON, snapshots, action results, or trace events contain the same information.
For MCP-capable agents, start:
zmr mcp --config .zmr/config.json --trace-dir traces/zmr-agent
Use the semantic_snapshot, tap, type, wait_visible, trace_events, and
trace_explore, trace_discover, and trace_export tools. Prefer
semantic_snapshot because it normalizes Android and iOS hierarchy classes
into roles, selectors, bounds, and recommended actions.
After a session has produced trace artifacts, prefer the review-first exploration handoff when a goal should travel with the generated scenario candidate:
{"method":"trace.explore","params":{"out":".zmr/discovered/login-smoke.json","goal":"find a stable login smoke","includeActions":true,"validate":true,"force":true}}
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 · 154 lines · 50 tokens per session scan A d41f769d4d7e
zmr-mobile-testing is a skill published in the GitHub repository johnmikel/zeno-mobile-runner (5 stars, last pushed 26d ago), licensed MIT. It adds 50 tokens to every session and 1,277 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 2026-08-31.
Other skills, from other repositories
android-e2e-readiness
Use when Android mobile E2E flows are flaky, Compose and View screens disagree with automation, hybrid screens are ambiguous, retries hide the real issue, or the team keeps collapsing the problem to selector-vs-timing without checking Android-specific readiness contracts.
ios-e2e-readiness
Use when iOS mobile E2E flows are flaky, SwiftUI and UIKit surfaces disagree with automation, mixed screens are ambiguous, retries hide the real issue, or the team keeps collapsing the problem to timing-only or SwiftUI-only without checking iOS-specific readiness contracts.
mobile-e2e-readiness-baseline
Use when mobile E2E flows are flaky across Android and iOS, visible screens are not reliably actionable, retries hide the real problem, or a team needs a platform-neutral readiness review before platform-specific guidance.
maestro-mobile-testing
Maestro mobile E2E testing patterns for React Native/Expo apps: YAML test flows, testID selectors, adaptive auth state, optimistic update verification, GraalJS scripting, cross-platform stability, CI/CD integration, Maestro Cloud, and MCP server integration.
argent-test-ui-flow
Autonomously test an app UI (iOS or Android) by running interact-screenshot-verify loops using argent MCP tools. Use when testing UI flows, verifying login works, testing navigation, running end-to-end UI test scenarios, manual QA steps, visible UI changes, or visual behavior.
mobile-automation
Control Android and iOS devices, emulators and simulators — launch apps, tap, swipe, type, take screenshots, read the accessibility tree. Use when a task involves a mobile device or app, mobile UI testing, or reproducing a bug on a phone.