### Start Frontend Application

Source: https://github.com/eigent-ai/eigent/blob/main/server/README_EN.md

Commands to install dependencies and start the frontend development server.

```bash
npm install
npm run dev
```

--------------------------------

### Quick Start Cloud-Connected Installation

Source: https://github.com/eigent-ai/eigent/blob/main/README.md

Commands to clone the repository and start the development environment for cloud-connected usage.

```bash
git clone https://github.com/eigent-ai/eigent.git
cd eigent
npm install
npm run dev
```

--------------------------------

### Install Stack Auth Wizard

Source: https://github.com/eigent-ai/eigent/blob/main/package/@stackframe/react/README.md

Run this command to start the Stack Auth installation wizard.

```bash
npx @stackframe/init-stack@latest
```

--------------------------------

### Setup and Basic Presentation

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/pptx/pptxgenjs.md

Initializes PptxGenJS, sets presentation properties, adds a slide with text, and saves the presentation to a file. Ensure 'pptxgenjs' is installed via npm.

```javascript
const pptxgen = require("pptxgenjs");

let pres = new pptxgen();
pres.layout = 'LAYOUT_16x9';  // or 'LAYOUT_16x10', 'LAYOUT_4x3', 'LAYOUT_WIDE'
pres.author = 'Your Name';
pres.title = 'Presentation Title';

let slide = pres.addSlide();
slide.addText("Hello World!", { x: 0.5, y: 0.5, fontSize: 36, color: "363636" });

pres.writeFile({ fileName: "Presentation.pptx" });
```

--------------------------------

### Clone and Run Eigent Project

Source: https://github.com/eigent-ai/eigent/blob/main/CONTRIBUTING.md

Steps to clone the repository, install dependencies, and start the development server for the frontend and backend.

```bash
git clone https://github.com/eigent-ai/eigent.git
cd eigent
npm install
npm run dev

# In a separate terminal, start the backend server
cd server
docker compose up -d
# Stream the logs if you needed
docker compose logs -f
```

--------------------------------

### Install Harbor CLI and Set API Key

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/harbor/README.md

Install the Harbor CLI using 'uv tool install harbor' and set your API key for authentication.

```bash
# Install Harbor CLI
uv tool install harbor

# Set your API key
export ANTHROPIC_API_KEY=your-key-here
```

--------------------------------

### Start Backend and Frontend

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/README.md

Run the backend and frontend services from the main project directory.

```bash
npm run dev
```

--------------------------------

### Start Services with Docker

Source: https://github.com/eigent-ai/eigent/blob/main/server/README_EN.md

Commands to initialize the environment variables and start the backend services using Docker Compose.

```bash
cd server
# Copy .env.example to .env(or create .env according to .env.example)
cp .env.example .env
# Environment variables from .env are automatically passed to Docker images
docker-compose up --build -d
```

--------------------------------

### Test Event Sequence for Installation Flow

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Verifies that the correct sequence of events (start, log, complete) is emitted during the dependency installation process.

```typescript
it('should handle complete installation flow', async () => {
  const events: string[] = [];

  // Set up event tracking
  electronAPI.onInstallDependenciesStart(() => events.push('start'));
  electronAPI.onInstallDependenciesLog(() => events.push('log'));
  electronAPI.onInstallDependenciesComplete(() => events.push('complete'));

  // Trigger installation
  await electronAPI.checkAndInstallDepsOnUpdate();

  // Verify event sequence
  expect(events).toEqual(['start', 'log', 'log', 'complete']);
});
```

--------------------------------

### Test Handling of Concurrent Installation Attempts

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Ensures that multiple simultaneous attempts to start the installation process are handled gracefully without causing issues.

```typescript
it('should handle concurrent installation attempts', async () => {
  const store = useInstallationStore.getState();

  // Start multiple installations
  const promise1 = store.performInstallation();
  const promise2 = store.performInstallation();

  // Should handle gracefully
  const [result1, result2] = await Promise.all([promise1, promise2]);

  expect(store.state).toBe('completed');
});
```

--------------------------------

### Run Installation Tests

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Execute specific unit tests for installation-related modules.

```bash
npm test test/unit/store/installationStore.test.ts
npm test test/unit/hooks/useInstallationSetup.test.ts
npm test test/unit/electron/install-deps.test.ts
```

--------------------------------

### Test Installation Store State Transitions

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Tests the state machine of the installation store, ensuring transitions between idle, checking permissions, showing carousel, installing, error, and completed states are handled correctly.

```typescript
import { useInstallationStore } from '@/store/installationStore';

it('should transition through all states', () => {
  const store = useInstallationStore.getState();

  expect(store.state).toBe('idle');

  store.startInstallation();
  expect(store.state).toBe('installing');

  store.setError('Installation failed');
  expect(store.state).toBe('error');

  store.retryInstallation();
  expect(store.state).toBe('installing');

  store.setSuccess();
  expect(store.state).toBe('completed');
});
```

--------------------------------

### Quick Start: Generate and Run Harbor Tasks

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/harbor/README.md

Navigate to the adapter directory, generate Harbor tasks, and then run them using the Harbor CLI with an oracle and an agent.

```bash
cd backend/benchmark/harbor

# 1. Generate Harbor tasks
python run_adapter.py

# 2. Verify with oracle (should score 1.0)
harbor run \
    -p datasets/eigent-bench \
    -a oracle \
    --env docker

# 3. Run with an agent
harbor run \
    -p datasets/eigent-bench \
    -a claude-code \
    -m anthropic/claude-sonnet-4-20250514 \
    --env docker
```

--------------------------------

### Test Uvicorn Startup with Dependency Installation

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Ensures that Uvicorn can detect missing dependencies during startup and trigger the necessary installation process.

```typescript
it('should handle uvicorn starting with dependency installation', async () => {
  // Simulate uvicorn detecting missing dependencies
  TestScenarios.uvicornDepsInstall(electronAPI);

  // Trigger uvicorn startup
  electronAPI.simulateUvicornStartup();

  // Wait for installation events
  await waitFor(() => {
    expect(mockInstallationStore.startInstallation).toHaveBeenCalled();
  });
});
```

--------------------------------

### Simulate Electron Installation Events

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Simulates various installation events and system changes using the mocked Electron API. Use these to test how the application responds to different states.

```typescript
// Simulate installation events
electronAPI.simulateInstallationStart();
electronAPI.simulateInstallationLog('stdout', 'Installing packages...');
electronAPI.simulateInstallationComplete(true); // or false for failure

// Simulate system changes
electronAPI.simulateVersionChange('2.0.0');
electronAPI.simulateVenvRemoval();
electronAPI.simulateUvicornStartup();
```

--------------------------------

### Markdown Skill Structure Example

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-creator/SKILL.md

Illustrates a high-level guide pattern for a skill, linking to separate reference files for advanced features like form filling or API documentation. This keeps the main SKILL.md concise.

```markdown
# PDF Processing

## Quick start

Extract text with pdfplumber:
[code example]

## Advanced features

- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
```

--------------------------------

### Initialize Document and Packer with docx-js

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/docx/SKILL.md

Sets up a new Document object and configures the Packer to write the document to a file. Ensure 'docx' is installed via npm.

```javascript
const { Document, Packer, Paragraph, TextRun, Table, TableRow, TableCell, ImageRun,
        Header, Footer, AlignmentType, PageOrientation, LevelFormat, ExternalHyperlink,
        TableOfContents, HeadingLevel, BorderStyle, WidthType, ShadingType,
        VerticalAlign, PageNumber, PageBreak } = require('docx');

const doc = new Document({ sections: [{ children: [/* content */] }] });
Packer.toBuffer(doc).then(buffer => fs.writeFileSync("doc.docx", buffer));
```

--------------------------------

### SKILL.md Frontmatter Example

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-creator/SKILL.md

Illustrates the required YAML frontmatter for a SKILL.md file, including 'name' and 'description'. The 'license' field is optional.

```yaml
name: skill-creator
description: Guide for creating effective skills.
license: Proprietary. LICENSE.txt has complete terms
```

--------------------------------

### Commit Message Examples

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-creator/references/output-patterns.md

Provide input/output pairs to guide the generation of commit messages. Follow the specified style for type, scope, and description.

```markdown
feat(auth): implement JWT-based authentication

Add login endpoint and token validation middleware
```

```markdown
fix(reports): correct date formatting in timezone conversion

Use UTC timestamps consistently across report generation
```

--------------------------------

### Running the EigenT AI Backend

Source: https://github.com/eigent-ai/eigent/blob/main/backend/README.md

Three options for starting the backend server using 'uv'. If 'uv run' hangs, consider using the virtual environment directly or deleting lock files.

```bash
# Option 1: Start with uvicorn directly
uv run uvicorn main:api --port 5001
```

```bash
# Option 2: Standalone mode (no Electron dependency)
uv run python main.py
```

```bash
# Option 3: If uv run hangs, delete lock files and retry, or use venv directly:
.venv/bin/python main.py
# or
.venv/bin/uvicorn main:api --port 5001 --host 0.0.0.0
```

```bash
# If uv hangs, delete lock files first: rm -f uv_installing.lock uv_installed.lock
```

--------------------------------

### Common Insecure Configuration Examples

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-security-auditor/SKILL.md

Examples of common misconfigurations in application settings that can pose security risks. These should be avoided in production environments.

```yaml
# Common misconfigurations to flag:
DEBUG: true                    # Debug mode in production
ALLOWED_HOSTS: ["*"]          # Unrestricted host access
CORS_ALLOW_ALL_ORIGINS: true  # Open CORS policy
SECRET_KEY: "default"         # Default or weak secret key
SSL_VERIFY: false             # Disabled TLS verification
```

--------------------------------

### Setup Electron Mocks and Environment

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Sets up Electron API mocks and the mock environment for testing. This is typically done in a `beforeEach` block in test suites.

```typescript
import { setupElectronMocks, TestScenarios } from '../mocks/electronMocks';
import { setupMockEnvironment } from '../mocks/environmentMocks';

describe('My Installation Test', () => {
  let electronAPI: MockedElectronAPI;
  let mockEnv: ReturnType<typeof setupMockEnvironment>;

  beforeEach(() => {
    // Set up mocks
    const { electronAPI: api } = setupElectronMocks();
    electronAPI = api;
    mockEnv = setupMockEnvironment();
  });

  it('should handle version update', async () => {
    // Apply scenario
    TestScenarios.versionUpdate(electronAPI);

    // Your test code here
  });
});
```

--------------------------------

### Benchmark JSON Configuration

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/README.md

Example structure for a benchmark dataset JSON file. Includes data, metadata, model arguments, and test script paths.

```json
{
  "data": {
    "name": "<n>",
    "question": "Your task description",
    "env": {}
  },
  "metadata": {
    "difficulty": "easy|medium|hard",
    "description": "Brief description of what this benchmark tests",
    "tags": ["tag1", "tag2"]
  },
  "model_kwargs": {
    "model_platform": "openai",
    "model_type": "gpt-4o"
  },
  "tests": {
    "grader": ["benchmark/grader/<n>.py"],
    "checker": ["benchmark/checker/<n>.py"]
  }
}
```

--------------------------------

### Proposed CSS token examples

Source: https://github.com/eigent-ai/eigent/blob/main/docs/design-system/index.html

Concrete examples of the proposed CSS token naming grammar applied to spacing, radius, elevation, and component properties.

```css
--ds-ref-space-8: 0.5rem;
--ds-radius-panel: var(--ds-ref-radius-16);
--ds-elevation-floating: var(--ds-ref-shadow-3);
--ds-button-md-height: var(--ds-control-height-md);
```

--------------------------------

### Framework-Specific Skill Organization Example

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-creator/SKILL.md

Shows organizing a skill that supports multiple frameworks by variant. The main SKILL.md includes workflow and provider selection, while separate reference files detail patterns for each provider (e.g., AWS, GCP, Azure).

```directory
cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
    ├── aws.md (AWS deployment patterns)
    ├── gcp.md (GCP deployment patterns)
    └── azure.md (Azure deployment patterns)
```

--------------------------------

### Test UI Feedback for Installation States

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Validates that the user interface accurately reflects the current state of the installation process, including visibility and error messages.

```typescript
it('should show correct UI for each installation state', () => {
  const { result } = renderHook(() => useInstallationStore());

  // Test idle state
  expect(result.current.state).toBe('idle');
  expect(result.current.isVisible).toBe(false);

  // Test installing state
  act(() => result.current.startInstallation());
  expect(result.current.state).toBe('installing');
  expect(result.current.isVisible).toBe(true);

  // Test error state
  act(() => result.current.setError('Installation failed'));
  expect(result.current.state).toBe('error');
  expect(result.current.error).toBe('Installation failed');

  // Test completed state
  act(() => result.current.setSuccess());
  expect(result.current.state).toBe('completed');
  expect(result.current.progress).toBe(100);
});
```

--------------------------------

### Environment State Test Scenarios

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Predefined scenarios for testing various environment states using the mock environment utilities. These cover different installation conditions like fresh installs, updates, and network issues.

```typescript
// Fresh installation
mockEnv.scenarios.freshInstall();

// Version update
mockEnv.scenarios.versionUpdate('0.9.0', '1.0.0');

// .venv removed
mockEnv.scenarios.venvRemoved();

// Network issues
mockEnv.scenarios.networkIssues();

// Complete failure
mockEnv.scenarios.completeFailure();

// Uvicorn startup installation
mockEnv.scenarios.uvicornStartupInstall();

// Installation in progress
mockEnv.scenarios.installationInProgress();
```

--------------------------------

### Configuring RemoteHands for EigenT AI

Source: https://github.com/eigent-ai/eigent/blob/main/backend/README.md

Example commands to set up and enable RemoteHands mode for the EigenT AI backend. Ensure the configuration file path is correctly set.

```bash
cp backend/config/hands_clusters.example.toml ~/.eigent/hands_clusters.toml
export EIGENT_HANDS_MODE=remote
export EIGENT_HANDS_CLUSTER_CONFIG_FILE=~/.eigent/hands_clusters.toml
```

--------------------------------

### Setup for Rendering Icons to PNG

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/pptx/pptxgenjs.md

Provides utility functions to render React icons as SVG markup and then rasterize them into PNG format using the 'sharp' library. Requires 'react', 'react-dom/server', and 'sharp'.

```javascript
const React = require("react");
const ReactDOMServer = require("react-dom/server");
const sharp = require("sharp");
const { FaCheckCircle, FaChartLine } = require("react-icons/fa");

function renderIconSvg(IconComponent, color = "#000000", size = 256) {
  return ReactDOMServer.renderToStaticMarkup(
    React.createElement(IconComponent, { color, size: String(size) })
  );
}

async function iconToBase64Png(IconComponent, color, size = 256) {
  const svg = renderIconSvg(IconComponent, color, size);
  const pngBuffer = await sharp(Buffer.from(svg)).png().toBuffer();
  return "image/png;base64," + pngBuffer.toString("base64");
}
```

--------------------------------

### Domain-Specific Skill Organization Example

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-creator/SKILL.md

Demonstrates organizing a skill with multiple domains into a directory structure, where the main SKILL.md provides an overview and navigation, and separate files in a 'reference/' directory handle domain-specific details. This ensures only relevant context is loaded.

```directory
bigquery-skill/
├── SKILL.md (overview and navigation)
└── reference/
    ├── finance.md (revenue, billing metrics)
    ├── sales.md (opportunities, pipeline)
    ├── product.md (API usage, features)
    └── marketing.md (campaigns, attribution)
```

--------------------------------

### Python Docstring Args Section Example

Source: https://github.com/eigent-ai/eigent/blob/main/CONTRIBUTING.md

Document parameters in the 'Args:' section for constructors or functions. Each line should not exceed 79 characters, and continuation lines should be indented by 4 spaces. Specify parameter name, type, description, and default value if applicable.

```python
Args:
    system_message (BaseMessage): The system message for initializing
    the agent's conversation context.
    model (BaseModelBackend, optional): The model backend to use for
    response generation. Defaults to :obj:`OpenAIModel` with
    `GPT_4O_MINI`. (default: :obj:`OpenAIModel` with `GPT_4O_MINI`)
```

--------------------------------

### Create New Excel File with Formulas and Formatting

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/xlsx/SKILL.md

Example using openpyxl to create a new Excel workbook, add data, insert a formula, and apply basic formatting and column width adjustments.

```python
# Using openpyxl for formulas and formatting
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook()
sheet = wb.active

# Add data
sheet['A1'] = 'Hello'
sheet['B1'] = 'World'
sheet.append(['Row', 'of', 'data'])

# Add formula
sheet['B2'] = '=SUM(A1:A10)'

# Formatting
sheet['A1'].font = Font(bold=True, color='FF0000')
sheet['A1'].fill = PatternFill('solid', start_color='FFFF00')
sheet['A1'].alignment = Alignment(horizontal='center')

# Column width
sheet.column_dimensions['A'].width = 20

wb.save('output.xlsx')
```

--------------------------------

### Semantic Text Component Usage

Source: https://github.com/eigent-ai/eigent/blob/main/docs/design-system/index.html

Example of using the Text component with the 'as' prop to define semantic HTML elements while maintaining design system roles.

```html
<Text as="h2" role="section">Project activity</Text>
<Text as="p" role="base">Latest changes from this run.</Text>
```

--------------------------------

### Test Installation Error Recovery

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Checks if the system can recover from installation errors by retrying the process after the environment is corrected.

```typescript
it('should recover from installation errors', async () => {
  // Set up error scenario
  TestScenarios.installationError(electronAPI);

  const store = useInstallationStore.getState();

  // Trigger installation
  await store.performInstallation();
  expect(store.state).toBe('error');

  // Simulate retry
  TestScenarios.allGood(electronAPI); // Fix the environment
  store.retryInstallation();

  await waitFor(() => {
    expect(store.state).toBe('completed');
  });
});
```

--------------------------------

### Initialize a New Skill

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-creator/SKILL.md

Use this script to generate a new skill template. It creates the necessary directory structure and boilerplate files. Run this from the skill-creator skill directory.

```bash
python scripts/init_skill.py <skill-name> --path <output-directory>
```

--------------------------------

### Configure Development Environment

Source: https://github.com/eigent-ai/eigent/blob/main/CONTRIBUTING.md

Instructions for configuring the `.env.development` file for local development, including proxy settings.

```bash
# Configure .env.development:
# Set VITE_USE_LOCAL_PROXY=true
# Set VITE_PROXY_URL=http://localhost:3001
```

--------------------------------

### Configure Frontend for Local Mode

Source: https://github.com/eigent-ai/eigent/blob/main/server/README_EN.md

Environment variables to set in .env.development to connect the frontend to the local backend.

```text
VITE_BASE_URL=/api
VITE_USE_LOCAL_PROXY=true
VITE_PROXY_URL=http://localhost:3001
```

--------------------------------

### Read/Analyze PPTX Content

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/pptx/SKILL.md

Use this command to extract text content from a .pptx file. Ensure the markitdown Python module is installed.

```bash
python -m markitdown presentation.pptx
```

--------------------------------

### Button component usage

Source: https://github.com/eigent-ai/eigent/blob/main/docs/design-system/design.md

Examples of using the Button component with various semantic axes including variant, tone, size, and buttonContent.

```tsx
<Button variant="primary" tone="neutral" size="md">
  Create task
</Button>

<Button
  variant="ghost"
  size="sm"
  buttonContent="icon-only"
  aria-label="Open settings"
>
  <Settings aria-hidden />
</Button>
```

--------------------------------

### Run Benchmarks

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/README.md

Execute benchmarks from the backend/ directory. Use the first command to run all benchmarks, or the second to run a specific benchmark defined by a JSON file.

```bash
python3 -m benchmark.main
```

```bash
python3 -m benchmark.main benchmark/dataset/0.json
```

--------------------------------

### Hex Color Format

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/pptx/pptxgenjs.md

Use hex colors without the '#' prefix to avoid file corruption. This example shows the correct and incorrect usage.

```javascript
color: "FF0000"      // ✅ CORRECT
color: "#FF0000"     // ❌ WRONG
```

--------------------------------

### Regular Expression Search Example

Source: https://github.com/eigent-ai/eigent/blob/main/backend/README.md

A simple bash command demonstrating a regular expression search for the word 'error' that is not followed by a closing bracket.

```bash
# regular search
\berror\b(?!\})
```

--------------------------------

### Accept Tracked Changes in DOCX

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/docx/SKILL.md

Accepts all tracked changes within a DOCX file, producing a clean output document. Requires LibreOffice to be installed.

```bash
python scripts/accept_changes.py input.docx output.docx
```

--------------------------------

### Initialize TracerProvider on FastAPI Startup

Source: https://github.com/eigent-ai/eigent/blob/main/backend/app/utils/telemetry/README.md

This code snippet demonstrates how to initialize the TracerProvider once during FastAPI startup to ensure efficient telemetry processing and prevent resource leaks.

```python
@api.on_event("startup")
async def startup_event():
    from app.utils.telemetry.workforce_metrics import initialize_tracer_provider
    initialize_tracer_provider()
```

--------------------------------

### Identify Project Languages and Dependencies

Source: https://github.com/eigent-ai/eigent/blob/main/resources/example-skills/skill-security-auditor/SKILL.md

Commands to help understand the project's technology stack. The `find` command lists source files, while `cat` displays package manifest files.

```bash
# Identify languages, frameworks, and entry points
find . -type f -name "*.py" -o -name "*.js" -o -name "*.ts" -o -name "*.go" -o -name "*.java" | head -20
cat package.json pyproject.toml requirements.txt go.mod pom.xml 2>/dev/null
```

--------------------------------

### Log Mock State for Debugging

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Provides examples of how to log the current state of mock objects for the Electron API and environment, aiding in debugging test failures.

```typescript
// Log current mock state
console.log('Electron API State:', electronAPI.mockState);
console.log('Environment State:', mockEnv.mockState);

// Check what functions were called
console.log(
  'checkAndInstallDepsOnUpdate calls:',
  electronAPI.checkAndInstallDepsOnUpdate.mock.calls
);
```

--------------------------------

### Using the Host Abstraction Layer

Source: https://github.com/eigent-ai/eigent/blob/main/src/host/README.md

Import and use the `useHost` hook to access host functionalities. Check for specific environment APIs like `electronAPI` before calling them, as they might be null in Web environments.

```tsx
import { useHost } from '@/host';

function MyComponent() {
  const host = useHost();
  // host.electronAPI / host.ipcRenderer 在 Web 下为 null
  if (host?.electronAPI?.someMethod) {
    host.electronAPI.someMethod();
  }
}
```

--------------------------------

### Electron API Test Scenarios

Source: https://github.com/eigent-ai/eigent/blob/main/test/README.md

Predefined scenarios for testing various Electron API interactions during installation flows. Use these to quickly set up common or edge-case states.

```typescript
// Fresh installation - no .venv, no version file
TestScenarios.freshInstall(electronAPI);

// Version update - version file exists but version changed
TestScenarios.versionUpdate(electronAPI);

// .venv removed - version file exists but .venv is missing
TestScenarios.venvRemoved(electronAPI);

// Installation in progress - when user opens app during installation
TestScenarios.installationInProgress(electronAPI);

// Installation error scenario
TestScenarios.installationError(electronAPI);

// Uvicorn startup with dependency installation
TestScenarios.uvicornDepsInstall(electronAPI);

// All good - no installation needed
TestScenarios.allGood(electronAPI);
```

--------------------------------

### MCP Server Configuration JSON

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/README.md

This JSON payload configures an MCP server, specifying the environment file for credentials and the details for the installed MCP server, such as the command and arguments.

```json
{
  "data": {
    "name": "1",
    "question": "List all Notion pages",
    "env": {
      "env_file": "benchmark/envs/1.env",
      "installed_mcp": {
        "mcpServers": {
          "notion": {
            "command": "npx",
            "args": ["@modelcontextprotocol/server-notion"]
          }
        }
      }
    }
  },
  "tests": {
    "checker": ["benchmark/checker/1.py"]
  }
}
```

--------------------------------

### Generate Harbor Tasks with Custom Options

Source: https://github.com/eigent-ai/eigent/blob/main/backend/benchmark/harbor/README.md

Generate Harbor tasks using 'run_adapter.py'. Options include setting custom weights for checker and grader, and limiting the number of tasks generated.

```bash
cd backend/benchmark/harbor

# Default (all tasks, 50/50 weights)
python run_adapter.py

# Custom weights (70% checker, 30% grader)
python run_adapter.py --checker-weight 0.7 --grader-weight 0.3

# Limit number of tasks
python run_adapter.py --limit 2
```