argent-react-native-optimization
Optimizes a React Native app by profiling first to find real bottlenecks, then sweeping for mechanical issues.
Skill by gmarcospires
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/gmarcospires-argent-react-native-optimization
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About
Use cases: frontend
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/argent-react-native-optimization
What's inside
- Skill name
argent-react-native-optimization- Description
- Optimizes a React Native app by profiling first to find real bottlenecks, then sweeping for mechanical issues. Entry-point for all performance work. Use when the app feels slow, user asks to optimize, fix re-renders, reduce jank, or improve startup. Delegates to argent-react-native-profiler for measurement.
- License
- MIT
- Instructions
- 61 lines in SKILL.md · view on GitHub
Files (4)
- SKILL.md
- fix-reference.md · references/
- lint-rules.md · references/
- semantic-checklist.md · references/
SKILL.md (first lines)
## Rules - Do not apply shotgun optimizations. Measure first, define what "good enough" looks like (target metric + threshold), fix the top offender, re-measure honestly. - **Quick scan** — `react-profiler-renders` for a live render count table. Identifies hot components instantly. - **Deep measure** — load `argent-react-native-profiler` skill. `react-profiler-start` → interact → `react-profiler-stop` → `react-profiler-analyze`. - **Inspect** — `react-profiler-component-source` per finding. `react-profiler-fiber-tree` to trace component ancestry and render cost. - **Verify correctness** - before fixing, recollect information from steps above and make a logical conclusion whether the approach is worth undertaking. - **Fix** — apply one fix. Validate with `debugger-evaluate` before committing. - **Re-measure** — report whether the target metric improved, regressed, or stayed flat. Check for regressions in other areas. If no net benefit or unacceptable tradeoffs, revert. - **Profile for discovery, not only verification.** Use the profiler to find issues static analysis missed, not only to confirm fixes. - **One fix per cycle for architectural changes.** Mechanical batch fixes (inline styles, index keys) can be grouped — re-profile once after the batch. When the measurement involves device interaction, record it as a flow (`argent-create-flow` skill) before the first run so all subsequent cycles replay identical steps. - **React Compiler**: if `react-profiler-analyze` reports `reactCompilerEnabled: true`, do NOT propose `useCallback`/`useMemo`/`React.memo` unless you confirmed compiler bail-out via `react-profiler-fiber-tree` (absent `useMemoCache`). - **Sub-agents**: Phases 1–2 dispatch sub-agents — one per file for lint results, one per checklist item for semantic. Sub-agents CANNOT touch the device - all profiling and E2E verification must happen in the main agent. ## Pipeline **Lint and semantic sweeps catch deterministic issues cheaply. Profiling finds runtime bottlenecks that static analysis misses. Do both.** Copy this checklist into your TODO list: ``` Optimization Progress: - [ ] Phase 1: Lint sweep (deterministic — catch mechanical issues without a running app) - [ ] Phase 2: Semantic sweep (judgment — memoization, lists, animations, etc.) - [ ] Phase 3: Baseline profile (find real bottlenecks, fix top offenders) - [ ] Phase 4: Verify no regressions (crashes, errors, red screens) ``` ### Phase 1: Lint sweep Run ESLint once at the project root with a comprehensive RN performance ruleset. Dispatch sub-agents to fix results — one per file. See [references/lint-rules.md](references/lint-rules.md) for ruleset and procedure. ### Phase 2: Semantic sweep Review each area requiring judgment — memoization, list rendering, animations, async patterns, effect cleanup, state hygiene, context architecture. Dispatch one sub-agent per checklist item. See [references/semantic-checklist.md](references/semantic-checklist.md) for full checklist. ### Phase 3: Visual profiling 1. Load `argent-react-native-profiler` skill, start dual profiling 2. Exercise key user flows (navigate screens the user specified, or all major flows) 3. Analyze with `react-profiler-analyze` + `native-profiler-analyze` + `profiler-combined-report` 4. Cross-reference profiling results with Phase 1–2 findings 5. Fix highest-impact issues. Re-profile after architectural changes; batch mechanical fixes. If a recorded flow breaks after a fix (e.g., UI layout changed), follow `argent-create-flow` skill to repair the flow rather than silently discarding it. ### Phase 4: Verify no regressions Navigate every screen and UI flow within scope, confirm each renders without errors. If no scope was specified, verify the entire app — cover all reachable screens via `argent-device-interact`. Use `debugger-log-registry` to check for runtime errors (if it returns `status: "not_connected"` there is no log file — follow its `guidance` to reconnect first) and take screenshots to check for red/yellow error screens. Check for regressions introduced by fixes (e.g., fewer re-renders but higher CPU, or new jank in a different screen). Main agent only. ## App-wide optimization 1. **Phase 1**: run lint centrally (one command), dispatch sub-agents to fix per-file in parallel 2. **Phase 2**: one sub-agent per checklist item for semantic sweep 3. **Phase 3**: main agent profiles top offending screens; fixes architectural issues top-down 4. **Phase 4**: main agent navigates all screens to verify nothing crashes After the entire run, run lint again to verify no new issues were introduced with your changes. This also helps ensure you haven't missed any issues which could've been fixed.
From gmarcospires/tento-truco, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 30, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/gmarcospires/tento-truco
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Debug a JS runtime via CDP using argent debugger tools.
SkillBFreshness: BClaude Code +9 - 0.529score
argent-device-interact
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Interact with an iOS simulator, Android emulator, or Chromium (CDP) app using argent MCP tools.
SkillBFreshness: BClaude Code +9 - 0.529score
argent-create-flow
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Create, record, edit, replay, or repair reusable Argent flow YAML files.
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argent-react-native-profiler
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Profile a React Native Hermes app to measure re-render and CPU performance using argent profiler tools.
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argent-lens
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Propose multiple visual design variants for on-screen elements and let the human pick in the Argent Lens window.
SkillBFreshness: BClaude Code +9 - 0.524score
argent-android-emulator-setup
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Set up and connect to an Android emulator using argent MCP tools.
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Cite this page
argent-react-native-optimization skill. Agent Mart. https://agentmart.dev/skills/gmarcospires-argent-react-native-optimization (last updated 2026-10-24)