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conductor-rewrite-performance

Use when building or optimizing a local-first desktop app with React, dealing with excessive re-renders during navigation, slow chat/list UIs with streaming content, or profiling a Tauri app without native Chrome DevTools access.

Revisar el código fuente Ver en GitHub

Precio sin confirmar★ 289 Estrellas de GitHubRegistro actualizado · 6 sept 2026agent-skill

Resumen

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

When to use this skill

You're building a local-first desktop application with React and experiencing performance bottlenecks
Navigation or route changes trigger cascading re-renders across multiple mounted components
You have a chat interface or long list that streams content and re-renders become sluggish
You're using Tauri and need to profile React performance but can't access Chrome DevTools
Multiple heavy views are mounted simultaneously (sidebar, nav, chat, terminal, editor) and all re-render on state changes
You need to manage multiple heavyweight child processes without exhausting system memory

Core principles

Local-first eliminates an entire category of performance problems. When SQLite is your source of truth and the UI never waits on the network, the bottleneck moves up into the rendering layer—every unnecessary re-render becomes the slowest thing users feel.
Unstable references cascade re-renders through the entire component tree. When router hooks return fresh objects on every render, every component reading them re-renders even when values haven't changed, and those re-renders propagate to all children.
Virtualization plus memoization is the only way to make streaming lists fast. Render only what's on screen (15 messages instead of 500), and ensure only the actively changing item re-renders while the rest stay memoized.
The fastest operation is the one the user never waits on. Move expensive synchronous work (like git checkpoints) off the critical path so the first token arrives immediately.

Tactics

Shim the Tauri bridge to profile in Chrome

When you can't use Safari's Web Inspector to debug React performance in a Tauri webview, create a development shim that lets the same client run in Chrome with full DevTools access.

// Conductor's UI reaches the Rust core through Tauri's invoke() bridge.
// In a real browser there's no Tauri runtime: __TAURI_INTERNALS__ is
// undefined and every invoke() throws. So in dev we shim that single
// entry point and boot the exact same client in Chrome, where the
// Chrome profiler AND the React DevTools profiler both work.

import { invoke as tauriInvoke } from "@tauri-apps/api/core";

export function invoke<T>(cmd: string, args?: Record<string, unknown>): Promise<T> {
  // Packaged app: use the native bridge.
  if ("__TAURI_INTERNALS__" in window) return tauriInvoke<T>(cmd, args);

  // Dev in Chrome: stand in for the Rust backend. Proxy to a dev server
  // running the real commands, or return canned data for the surface
  // you're profiling.
  return fetch(`/__backend__/${cmd}`, {
    method: "POST",
    body: JSON.stringify(args ?? {}),
  }).then((r) => r.json());
}

Steps:

Identify the single bridge function your UI uses to talk to the native layer (e.g., Tauri's invoke())
Check for the presence of the native runtime object (__TAURI_INTERNALS__)
In production, call through to the real bridge
In development, proxy to a local server or return mock data
Boot the client in Chrome and use React DevTools Profiler to identify bottlenecks

Replace react-router with TanStack Router for stable references

When navigation produces fresh param/search references that cascade re-renders, switch to a router that provides structural sharing and stable references.

Before with react-router:

// Before with react-router

import { useSearchParams } from "react-router-dom";

function WorkspaceView() {
  const [searchParams] = useSearchParams();

  // useSearchParams() returns a NEW URLSearchParams every render,
  // and this parsed object is a new reference every render too.
  const filters = {
    agent: searchParams.get("agent"),
    status: searchParams.get("status"),
  };

  useEffect(() => {
    refetchAgents(filters);
  }, [filters]); // new object each render → fires on EVERY render

  return <AgentList filters={filters} />; // child re-renders every time
}

After with TanStack Router:

// After with tanstack router

import { createFileRoute } from "@tanstack/react-router";

export const Route = createFileRoute("/workspace")({
  // parse + validate search once, fully typed
  validateSearch: (s): { agent?: string; status?: string } => ({
    agent: s.agent as string | undefined,
    status: s.status as string | undefined,
  }),
});

function WorkspaceView() {
  // structural sharing: SAME reference unless agent/status actually change
  const filters = Route.useSearch();

  useEffect(() => {
    refetchAgents(filters);
  }, [filters]); // fires only when a value really changes

  return <AgentList filters={filters} />; // no re-render!
}

Steps:

Define routes with createFileRoute and add a validateSearch function that parses and types search params
Replace useSearchParams() with Route.useSearch() to get a stable reference
Remove manual useMemo wrappers around parsed params—structural sharing handles it
Verify with React DevTools Profiler that only components with actual changes re-render on navigation

Virtualize + memoize streaming chat lists

When a chat UI with hundreds of messages re-renders on every token, combine virtualization (render only visible items) with memoization (skip unchanged items).

Before:

// Before: the simple approach where each message/token rerenders everything

function Chat({ messages }) {
  return (
    <div>
      {messages.map((m) => (
        <Message key={m.id} message={m} /> // all N re-render on each token
      ))}
    </div>
  );
}

After:

// After: virtualize the list + memoize each row

const Message = React.memo(function Message({ message }) {
  return <MarkdownContent text={message.content} />; 
});

function Chat({ messages }) {
  // VirtuosoMessageList is a component from Virtuoso
  return (
    <VirtuosoMessageList
      data={messages}
      itemContent={(_, m) => <Message message={m} />}
    />
  );
}

Steps:

Wrap each message component in React.memo so it only re-renders when its props change
Replace the .map() loop with react-virtuoso's VirtuosoMessageList (or Virtuoso for general lists)
Pass the full message array as data and render each item via itemContent
Let Virtuoso handle scroll anchoring, bottom-stick during streaming, and dynamic height measurement
Verify that only the streaming message re-renders while the rest stay memoized

Move expensive synchronous work off the critical path

When a blocking operation (like a git checkpoint) sits between user input and the first response token, move it to the background.

Pattern:

Before: User hits enter → synchronous git add -A → send prompt → first token arrives
After: User hits enter → send prompt immediately → first token arrives → checkpoint runs in background

Steps:

Identify synchronous operations on the critical path (e.g., file snapshots, database writes)
Fire them asynchronously after the user-facing action completes
Ensure the background task still completes before the next checkpoint is needed
If resumption depends on the checkpoint, pass a --resume <uuid> flag so the session can restart from disk

Manage memory for multiple heavyweight child processes

When your app spawns multiple long-lived processes (e.g., agent sessions), shut down idle ones and resume on demand.

Steps:

Track the last activity timestamp for each child process
After a threshold of inactivity (e.g., 5 minutes), kill the process and reclaim memory
Persist session state to disk with a unique identifier (e.g., --resume <uuid>)
When the user returns to that workspace, spawn a new process with the resume flag
Verify in Activity Monitor / Task Manager that idle workspaces don't hold memory

Anti-patterns

❌ Don't wrap every unstable reference in useMemo manually—fix the root cause by switching to a library that provides stable references (like TanStack Router's structural sharing).

❌ Don't render all list items and rely on CSS overflow: scroll—virtualize so only visible items exist in the DOM.

❌ Don't block the UI thread with synchronous git operations or file I/O on the critical path—move them to background tasks.

❌ Don't let heavyweight child processes accumulate indefinitely—implement idle shutdown and resume-on-demand.

❌ Don't skip profiling because your webview doesn't support Chrome DevTools—shim the native bridge and run the same client in Chrome for development.

❌ Don't assume local-first means fast by default—once network latency is gone, rendering bottlenecks become the new constraint.

Source

The Conductor Rewrite: What They Changed to Make It Fast

Ver fuente ↗

Metadatos del archivo

name: conductor-rewrite-performance
description: "Use when building or optimizing a local-first desktop app with React, dealing with excessive re-renders during navigation, slow chat/list UIs with streaming content, or profiling a Tauri app without native Chrome DevTools access."

Ver texto original

---
name: conductor-rewrite-performance
description: "Use when building or optimizing a local-first desktop app with React, dealing with excessive re-renders during navigation, slow chat/list UIs with streaming content, or profiling a Tauri app without native Chrome DevTools access."
---

## When to use this skill

- You're building a local-first desktop application with React and experiencing performance bottlenecks
- Navigation or route changes trigger cascading re-renders across multiple mounted components
- You have a chat interface or long list that streams content and re-renders become sluggish
- You're using Tauri and need to profile React performance but can't access Chrome DevTools
- Multiple heavy views are mounted simultaneously (sidebar, nav, chat, terminal, editor) and all re-render on state changes
- You need to manage multiple heavyweight child processes without exhausting system memory

## Core principles

1. **Local-first eliminates an entire category of performance problems.** When SQLite is your source of truth and the UI never waits on the network, the bottleneck moves up into the rendering layer—every unnecessary re-render becomes the slowest thing users feel.

2. **Unstable references cascade re-renders through the entire component tree.** When router hooks return fresh objects on every render, every component reading them re-renders even when values haven't changed, and those re-renders propagate to all children.

3. **Virtualization plus memoization is the only way to make streaming lists fast.** Render only what's on screen (15 messages instead of 500), and ensure only the actively changing item re-renders while the rest stay memoized.

4. **The fastest operation is the one the user never waits on.** Move expensive synchronous work (like git checkpoints) off the critical path so the first token arrives immediately.

## Tactics

### Shim the Tauri bridge to profile in Chrome

When you can't use Safari's Web Inspector to debug React performance in a Tauri webview, create a development shim that lets the same client run in Chrome with full DevTools access.

```typescript
// Conductor's UI reaches the Rust core through Tauri's invoke() bridge.
// In a real browser there's no Tauri runtime: __TAURI_INTERNALS__ is
// undefined and every invoke() throws. So in dev we shim that single
// entry point and boot the exact same client in Chrome, where the
// Chrome profiler AND the React DevTools profiler both work.

import { invoke as tauriInvoke } from "@tauri-apps/api/core";

export function invoke<T>(cmd: string, args?: Record<string, unknown>): Promise<T> {
  // Packaged app: use the native bridge.
  if ("__TAURI_INTERNALS__" in window) return tauriInvoke<T>(cmd, args);

  // Dev in Chrome: stand in for the Rust backend. Proxy to a dev server
  // running the real commands, or return canned data for the surface
  // you're profiling.
  return fetch(`/__backend__/${cmd}`, {
    method: "POST",
    body: JSON.stringify(args ?? {}),
  }).then((r) => r.json());
}
```

**Steps:**
1. Identify the single bridge function your UI uses to talk to the native layer (e.g., Tauri's `invoke()`)
2. Check for the presence of the native runtime object (`__TAURI_INTERNALS__`)
3. In production, call through to the real bridge
4. In development, proxy to a local server or return mock data
5. Boot the client in Chrome and use React DevTools Profiler to identify bottlenecks

### Replace react-router with TanStack Router for stable references

When navigation produces fresh param/search references that cascade re-renders, switch to a router that provides structural sharing and stable references.

**Before with react-router:**

```tsx
// Before with react-router

import { useSearchParams } from "react-router-dom";

function WorkspaceView() {
  const [searchParams] = useSearchParams();

  // useSearchParams() returns a NEW URLSearchParams every render,
  // and this parsed object is a new reference every render too.
  const filters = {
    agent: searchParams.get("agent"),
    status: searchParams.get("status"),
  };

  useEffect(() => {
    refetchAgents(filters);
  }, [filters]); // new object each render → fires on EVERY render

  return <AgentList filters={filters} />; // child re-renders every time
}
```

**After with TanStack Router:**

```tsx
// After with tanstack router

import { createFileRoute } from "@tanstack/react-router";

export const Route = createFileRoute("/workspace")({
  // parse + validate search once, fully typed
  validateSearch: (s): { agent?: string; status?: string } => ({
    agent: s.agent as string | undefined,
    status: s.status as string | undefined,
  }),
});

function WorkspaceView() {
  // structural sharing: SAME reference unless agent/status actually change
  const filters = Route.useSearch();

  useEffect(() => {
    refetchAgents(filters);
  }, [filters]); // fires only when a value really changes

  return <AgentList filters={filters} />; // no re-render!
}
```

**Steps:**
1. Define routes with `createFileRoute` and add a `validateSearch` function that parses and types search params
2. Replace `useSearchParams()` with `Route.useSearch()` to get a stable reference
3. Remove manual `useMemo` wrappers around parsed params—structural sharing handles it
4. Verify with React DevTools Profiler that only components with actual changes re-render on navigation

### Virtualize + memoize streaming chat lists

When a chat UI with hundreds of messages re-renders on every token, combine virtualization (render only visible items) with memoization (skip unchanged items).

**Before:**

```tsx
// Before: the simple approach where each message/token rerenders everything

function Chat({ messages }) {
  return (
    <div>
      {messages.map((m) => (
        <Message key={m.id} message={m} /> // all N re-render on each token
      ))}
    </div>
  );
}
```

**After:**

```tsx
// After: virtualize the list + memoize each row

const Message = React.memo(function Message({ message }) {
  return <MarkdownContent text={message.content} />; 
});

function Chat({ messages }) {
  // VirtuosoMessageList is a component from Virtuoso
  return (
    <VirtuosoMessageList
      data={messages}
      itemContent={(_, m) => <Message message={m} />}
    />
  );
}
```

**Steps:**
1. Wrap each message component in `React.memo` so it only re-renders when its props change
2. Replace the `.map()` loop with `react-virtuoso`'s `VirtuosoMessageList` (or `Virtuoso` for general lists)
3. Pass the full message array as `data` and render each item via `itemContent`
4. Let Virtuoso handle scroll anchoring, bottom-stick during streaming, and dynamic height measurement
5. Verify that only the streaming message re-renders while the rest stay memoized

### Move expensive synchronous work off the critical path

When a blocking operation (like a git checkpoint) sits between user input and the first response token, move it to the background.

**Pattern:**
- **Before:** User hits enter → synchronous `git add -A` → send prompt → first token arrives
- **After:** User hits enter → send prompt immediately → first token arrives → checkpoint runs in background

**Steps:**
1. Identify synchronous operations on the critical path (e.g., file snapshots, database writes)
2. Fire them asynchronously after the user-facing action completes
3. Ensure the background task still completes before the next checkpoint is needed
4. If resumption depends on the checkpoint, pass a `--resume <uuid>` flag so the session can restart from disk

### Manage memory for multiple heavyweight child processes

When your app spawns multiple long-lived processes (e.g., agent sessions), shut down idle ones and resume on demand.

**Steps:**
1. Track the last activity timestamp for each child process
2. After a threshold of inactivity (e.g., 5 minutes), kill the process and reclaim memory
3. Persist session state to disk with a unique identifier (e.g., `--resume <uuid>`)
4. When the user returns to that workspace, spawn a new process with the resume flag
5. Verify in Activity Monitor / Task Manager that idle workspaces don't hold memory

## Anti-patterns

❌ **Don't wrap every unstable reference in `useMemo` manually**—fix the root cause by switching to a library that provides stable references (like TanStack Router's structural sharing).

❌ **Don't render all list items and rely on CSS `overflow: scroll`**—virtualize so only visible items exist in the DOM.

❌ **Don't block the UI thread with synchronous git operations or file I/O on the critical path**—move them to background tasks.

❌ **Don't let heavyweight child processes accumulate indefinitely**—implement idle shutdown and resume-on-demand.

❌ **Don't skip profiling because your webview doesn't support Chrome DevTools**—shim the native bridge and run the same client in Chrome for development.

❌ **Don't assume local-first means fast by default**—once network latency is gone, rendering bottlenecks become the new constraint.

## Source

[The Conductor Rewrite: What They Changed to Make It Fast](https://performance.dev/the-conductor-rewrite)

Revisar el código fuente

Precio y costes de ejecución

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Licencia: Apache-2.0
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Fuente del skill registrada

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Revisar antes de instalar: Evitar instalación automática

Licencia: Apache-2.0

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md appears truncated mid-sentence in the TanStack Router section, with the step-by-step list incomplete after 'Steps: 1'.
No explicit setup, operating environment, or limitations section is present in SKILL.md.
The Tauri bridge shim example proxies to a dev server endpoint, but the skill does not warn against accidentally shipping the dev shim or exposing backend commands in production.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 289 stars, 40 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

Indexado

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente: boraoztunc/skills
Licencia: Apache-2.0
Versión: 1.0.0
Último push de GitHub: 15 ago 2026
Registro actualizado: 6 sept 2026
Ruta de instrucciones: conductor-rewrite-performance/SKILL.md @ 645553ca7622

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

68/100

Prometedor

Confianza

52/100

Do not auto-install

Auditoría

71/100

Requiere revisión

Abrir auditoría completa Ver informe de evaluación

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md appears truncated mid-sentence in the TanStack Router section, with the step-by-step list incomplete after 'Steps: 1'.
No explicit setup, operating environment, or limitations section is present in SKILL.md.
The Tauri bridge shim example proxies to a dev server endpoint, but the skill does not warn against accidentally shipping the dev shim or exposing backend commands in production.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 289 stars, 40 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Resultados: —

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      }
    ],
    "handoff_url": "https://www.openagentskill.com/api/skills/boraoztunc-conductor-rewrite-performance/install",
    "manifest_url": "https://www.openagentskill.com/api/registry/manifest/boraoztunc-conductor-rewrite-performance"
  },
  "trust": {
    "score": 60,
    "label": "Manual review",
    "version": "trust-score-v4",
    "install_policy": "block",
    "evidence": {
      "stars": "289 GitHub stars",
      "repoActivity": "289 stars, 40 forks",
      "lastPushed": "2mo since push",
      "license": "Apache-2.0",
      "repository": "https://github.com/boraoztunc/skills/tree/main/conductor-rewrite-performance",
      "install": "npx skills add boraoztunc/skills --skill conductor-rewrite-performance",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Usable metadata, review docs",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "design-creative",
      "agent-skill"
    ],
    "known_risks": [
      "SKILL.md appears truncated mid-sentence in the TanStack Router section, with the step-by-step list incomplete after 'Steps: 1'.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Stars/forks activity: 289 stars, 40 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 71,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "SKILL.md appears truncated mid-sentence in the TanStack Router section, with the step-by-step list incomplete after 'Steps: 1'.",
      "No explicit setup, operating environment, or limitations section is present in SKILL.md.",
      "The Tauri bridge shim example proxies to a dev server endpoint, but the skill does not warn against accidentally shipping the dev shim or exposing backend commands in production.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Stars/forks activity: 289 stars, 40 forks; issue activity unavailable in current metadata"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 68,
    "label": "Promising"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Design and creative",
    "maintenance": "2mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "SKILL.md appears truncated mid-sentence in the TanStack Router section, with the step-by-step list incomplete after 'Steps: 1'.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "No explicit setup, operating environment, or limitations section is present in SKILL.md.",
    "The Tauri bridge shim example proxies to a dev server endpoint, but the skill does not warn against accidentally shipping the dev shim or exposing backend commands in production."
  ],
  "agent_contract": {
    "task_input": "Use conductor-rewrite-performance in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 60/100 Manual review",
      "Audit: 71/100 Needs review",
      "Safety: 23/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "boraoztunc-conductor-rewrite-performance (conductor-rewrite-performance)",
      "install_command": "npx skills add boraoztunc/skills --skill conductor-rewrite-performance",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "boraoztunc-conductor-rewrite-performance",
      "task": "Use conductor-rewrite-performance in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/boraoztunc-conductor-rewrite-performance",
    "api": "https://www.openagentskill.com/api/agent/skills/boraoztunc-conductor-rewrite-performance",
    "audit": "https://www.openagentskill.com/skills/boraoztunc-conductor-rewrite-performance/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=boraoztunc-conductor-rewrite-performance&task=Use%20conductor-rewrite-performance%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20conductor-rewrite-performance%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20conductor-rewrite-performance%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/boraoztunc-conductor-rewrite-performance/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/boraoztunc-conductor-rewrite-performance"
  }
}

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Creador: boraoztunc
Fuente: boraoztunc/skills
Indexado por: Índice comunitario de OpenAgentSkill

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Resumen

When to use this skill

Core principles

Tactics

Shim the Tauri bridge to profile in Chrome

Replace react-router with TanStack Router for stable references

Virtualize + memoize streaming chat lists

Move expensive synchronous work off the critical path

Manage memory for multiple heavyweight child processes

Anti-patterns

Source

Revisar el código fuente

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