rn-tester

A React Native testing agent that checks app features on a simulator or emulator, including the screen, user actions, and internal state.

In plain words
What is it for?
Use it to verify that a React Native feature displays correctly, responds to user flows, and leaves the app in the expected state.
Why use it?
It helps catch problems after a feature is built without relying only on code inspection. It must run in the main coding-agent session because its device tools are unavailable to spawned agents.

Agent

Part of the rn-dev-agent plugin — 11 skills, 16 commands, 5 agents, 6 hooks shipped together

Install

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.

agentmods
npx agentmods add agents/lykhoyda/rn-dev-agent/rn-tester
Clone the repo
git clone --depth 1 https://github.com/Lykhoyda/rn-dev-agent

Or install rn-dev-agent, the plugin that ships this one along with the rest of its 11 skills, 16 commands, 5 agents, 6 hooks.

Per session 337 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,995 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00337 $0.05995
Opus 5 $0.00169 $0.02998
Sonnet 5 $0.00067 $0.01199
Haiku 4.5 $0.00034 $0.00600

Measured 3d ago against content hash fc6f635857af, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rn-tester 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 3d 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.

packages/claude-plugin/agents/rn-tester.md · 526 lines

How it starts

The opening of the file, as written. The whole thing — 526 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a React Native feature testing agent. After a feature is implemented, you verify it works correctly on a real simulator/emulator.

CRITICAL — Invocation Constraint (GH #31): This agent uses MCP tools (cdp_*, device_*) which only work when invoked in the parent Claude Code session, not when spawned as a subagent via the Task tool. MCP stdio connections do not propagate across subprocess boundaries.

  • DO invoke this agent's protocol inline from a slash command (/rn-dev-agent:test-feature) or from the parent session directly
  • DO NOT spawn this agent via Task(subagent_type='rn-dev-agent:rn-tester') — the spawned subagent will not have access to cdp_* / device_* tools

If you are reading this as a spawned subagent and notice you cannot call CDP/device tools, stop immediately. Return control to the parent session and ask it to run the testing protocol directly.

Your Testing Protocol

Step 0a: Reusable Action Scan (artifact-first)

Before composing ANY device_* sequence, scan for existing automation. This is the single highest-leverage rule in the plugin — a 7-minute manual walk has been documented for a flow that already existed as a 23-second Maestro replay. Codified in feedback_execute_artifacts_before_manual.md.

node "${CLAUDE_PLUGIN_ROOT}/rn-dev-agent-core/dist/learned-actions.js" \
  --json --section b --filter "<feature-keyword>" \
  --workspace-root "$PWD" --memory-cwd "$PWD" \
  > /tmp/learned-actions.json
jq '.sections.flows.items[] | {flow, path, params, replay}' /tmp/learned-actions.json

Decide:

  1. Exact match (filename or first-comment-block contains the feature keyword AND appId matches the test-app): replay it via /rn-dev-agent:run-action <flow-name> or cdp_run_action. A passing replay IS evidence — proceed to Step 6 (Generate / Refresh) and Step 7 (Report). Skip the rest.
  2. Partial match (covers part of the flow, e.g. login is automated but the feature is post-login): replay the prefix flow, then continue with device_* from where it left off.
  3. No match: continue to Step 0 below. You MUST persist the new flow in Step 6 so the next session can replay instead of recomposing.

Read the full file on GitHub · 526 lines

Changes

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.

  1. 3d ago First seen · 526 lines · 337 tokens per session scan A fc6f635857af

Subscribe to this mod's changes

rn-tester is an agent published in the GitHub repository Lykhoyda/rn-dev-agent (11 stars, last pushed 3d ago), licensed MIT. It adds 337 tokens to every session and 5,995 once invoked, about $0.0017 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.