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 skills/lykhoyda/rn-dev-agent/rn-feature-developmentnpx skills add Lykhoyda/rn-dev-agent --skill rn-feature-developmentgit clone --depth 1 https://github.com/Lykhoyda/rn-dev-agentWrote 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/lykhoyda/rn-dev-agent/rn-feature-development)<a href="https://agentmods.dev/skills/lykhoyda/rn-dev-agent/rn-feature-development"><img src="https://agentmods.dev/badge/skills/lykhoyda/rn-dev-agent/rn-feature-development.svg" alt="Measured on agentmods" 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 | $0.00086 | $0.06493 |
| Opus 5 | $0.00043 | $0.03247 |
| Sonnet 5 | $0.00017 | $0.01299 |
| Haiku 4.5 | $0.00009 | $0.00649 |
Grade A, and why
rn-feature-development 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.
How it starts
The opening of the file, as written. The whole thing — 567 lines — stays where its author put it; the contents beside it link to each section on GitHub.
React Native Feature Development (8-Phase Pipeline)
You are helping a developer implement a new feature in a React Native app. Follow this systematic approach: understand the codebase deeply, ask about all ambiguities, design an elegant architecture, implement, verify live on the simulator, review quality, and produce E2E proof with screenshots.
Core Principles
- NEVER skip phases: Every phase (1-8) must be executed. Do NOT bypass explorer agents (Phase 2), architect agents (Phase 4), reviewer agents (Phase 6), or proof capture (Phase 8) even when the codebase is familiar. Speed comes from parallel agent launches, not phase elimination.
- Ask clarifying questions: Identify all ambiguities and edge cases before implementing. Wait for user answers before proceeding.
- Understand before acting: Read and comprehend existing code patterns first.
- Read files identified by agents: When launching agents, ask them to return lists of important files. After agents complete, read those files yourself.
- Simple and elegant: Prioritize readable, maintainable code.
- Use TodoWrite: Track all progress through the phases.
- Verify on device: After implementation, prove it works with a live screenshot and CDP state checks.
- Cross-platform visual verification: When both iOS and Android are available, compare screenshots element-by-element. A screen that renders without crashing but has missing icons/images is a FAIL, not a PASS.
- Evaluator hook: if
dev/evaluator.mdexists in the plugin root, log every phase's events per its matching Phase section there (it defines what each phase records; re-verification logs as Phase 5.5-retry); Phase 7 finalizes the report and opens or updates GitHub Issues for high-confidence bugs.
Phase 1: Discovery
Goal: Understand what needs to be built.
Actions:
- Create a todo list with all 9 phases (1, 2, 3, 4, 5, 5.5, 6, 7, 8)
- If the feature is unclear, ask the user:
- What problem does this solve?
- What screen is the entry point?
- Does this touch the store — if so which slice?
- Are there API calls involved?
- Summarize your understanding and confirm with the user
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 567 lines · 86 tokens per session scan A 520bff5e394f
rn-feature-development is a skill published in the GitHub repository Lykhoyda/rn-dev-agent (11 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 6,493 once invoked, about $0.0004 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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