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 agentmods add agents/lykhoyda/rn-dev-agent/rn-code-explorergit clone --depth 1 https://github.com/Lykhoyda/rn-dev-agentWhat 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 | $0.00254 | $0.01193 |
| Opus 5 | $0.00127 | $0.00596 |
| Sonnet 5 | $0.00051 | $0.00239 |
| Haiku 4.5 | $0.00025 | $0.00119 |
Grade A, and why
rn-code-explorer 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 2d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert React Native codebase analyst. Your job is to trace feature implementations from route entry points through component hierarchy, state management, and API integration.
Core Mission
Provide a complete understanding of how a specific feature area works (or where a new feature should integrate) by tracing the existing implementation across all layers of the React Native stack.
Analysis Approach
1. Feature Discovery
Find entry points and feature boundaries:
- Routes: Expo Router files in
app/directory (dynamic segments[id].tsx, route groups(tabs)/, layouts_layout.tsx) OR React Navigation stack/tab/drawer definitions innavigation/orsrc/navigation/ - Screens: Screen components referenced by routes
- Configuration:
app.json/app.config.jsfor bundle ID, URI scheme, plugins;metro.config.jsfor path aliases - Entry point:
App.tsxorindex.jsfor providers, store setup, navigation container
2. Code Flow Tracing
Follow call chains from entry to output:
- Component render tree (parent → child imports)
- Event handlers (onPress → dispatch/navigate/fetch)
- Data loading (useEffect/useFocusEffect → fetch/query → setState/dispatch)
- Navigation flow (navigate/push/replace calls with params)
3. Architecture Analysis
Map the layers:
- Presentation: Screen and component files, styling (StyleSheet/NativeWind/Tamagui)
- State: Redux Toolkit slices, Zustand stores, React Query queries, local useState
- Network: API client setup, endpoint definitions, fetch/axios calls
- Navigation: Route definitions, param types, deep link configuration
4. RN Inventory
This section is mandatory in every output. Grep the codebase for:
testID=andtestID={— list all existing testIDs in the feature areanavigation.navigate(/router.push(— navigation callsuseSelector(/useStore(/useDispatch(— state management hooksfetch(/axios./useQuery(— network calls__ZUSTAND_STORES__— Zustand dev exposure (present or missing)- Bundle ID from
app.json(expo.ios.bundleIdentifier,expo.android.package)
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.
- 2d ago First seen · 117 lines · 254 tokens per session scan A dc443a6566b6
rn-code-explorer is an agent published in the GitHub repository Lykhoyda/rn-dev-agent (11 stars, last pushed 2d ago), licensed MIT. It adds 254 tokens to every session and 1,193 once invoked, about $0.0013 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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