grepai-watch-daemon

This skill covers the grepai watch command and daemon management for real-time code indexing.

yoanbernabeu/grepai-skillsUpdated Apr 8, 2026

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Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-watch-daemon

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Installation Guide

How to use grepai-watch-daemon on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add grepai-watch-daemon
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-watch-daemon

Fetches grepai-watch-daemon from yoanbernabeu/grepai-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/grepai-watch-daemon

Restart Cursor to activate grepai-watch-daemon. Access via /grepai-watch-daemon in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

GrepAI Watch Daemon

This skill covers the grepai watch command and daemon management for real-time code indexing.

When to Use This Skill

  • Starting initial code indexing
  • Setting up real-time file monitoring
  • Running the daemon in background
  • Troubleshooting indexing issues

What the Watch Daemon Does

The watch daemon:

  1. Scans all source files in your project
  2. Chunks code into segments (~512 tokens)
  3. Generates embeddings via your configured provider
  4. Stores vectors in your configured backend
  5. Monitors for file changes in real-time
  6. Updates the index when files change

Basic Usage

Start Watching (Foreground)

cd /your/project
grepai watch

Output:

🔍 GrepAI Watch
   Scanning files...
   Found 245 files
   Processing chunks...
   ████████████████████████████████ 100%
   Indexed 1,234 chunks
   Watching for changes...

Press Ctrl+C to stop.

Start in Background

grepai watch --background

Output:

🔍 GrepAI Watch (background)
   Daemon started with PID 12345
   Log file: ~/.grepai/daemon.log

Check Daemon Status

grepai watch --status

Output:

✅ GrepAI Daemon Running

   PID: 12345
   Started: 2025-01-28 10:30:00
   Project: /path/to/project

   Statistics:
   - Files indexed: 245
   - Chunks: 1,234
   - Last update: 2 minutes ago

Stop the Daemon

grepai watch --stop

Output:

✅ Daemon stopped (PID 12345)

Command Reference

Command Description
grepai watch Start daemon in foreground
grepai watch --background Start daemon in background
grepai watch --status Check daemon status
grepai watch --stop Stop running daemon

Configuration

Watch Settings

# .grepai/config.yaml
watch:
  # Debounce delay in milliseconds
  # Groups rapid file changes together
  debounce_ms: 500

Debounce Explained

When you save a file, editors often write multiple times quickly. Debouncing waits for changes to settle:

Value Behavior
100 More responsive, more reindexing
500 Balanced (default)
1000 Less responsive, fewer reindexing

Initial Indexing

What Gets Indexed

The daemon indexes files:

  • Matching supported extensions (.go, .js, .ts, .py, etc.)
  • Not in ignore patterns (node_modules, .git, etc.)
  • Respecting .gitignore

Indexing Progress

Large codebases show progress:

Scanning files...
Found 10,245 files
Processing chunks...
████████████████░░░░░░░░░░░░░░░░ 50% (5,122/10,245)

Indexing Time Estimates

Codebase Files Time (Ollama) Time (OpenAI)
Small 100 ~30s ~10s
Medium 1,000 ~5min ~1min
Large 10,000 ~30min ~5min

Real-Time Monitoring

After initial indexing, the daemon watches for:

  • File creation
  • File modification
  • File deletion
  • File renames

File Change Detection

Uses OS-native file watching:

  • macOS: FSEvents
  • Linux: inotify
  • Windows: ReadDirectoryChangesW

What Triggers Reindexing

Action Result
Save existing file Re-embed file chunks
Create new file Index new chunks
Delete file Remove from index
Rename file Update path, keep vectors

Background Daemon Management

Starting on System Boot

macOS (launchd)

Create ~/Library/LaunchAgents/com.grepai.watch.plist:

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
    <key>Label</key>
    <string>com.grepai.watch</string>
    <key>ProgramArguments</key>
    <array>
        <string>/usr/local/bin/grepai</string>
        <string>watch</string>
    </array>
    <key>WorkingDirectory</key>
    <string>/path/to/your/project</string>
    <key>RunAtLoad</key>
    <true/>
    <key>KeepAlive</key>
    <true/>
</dict>
</plist>

Load:

launchctl load ~/Library/LaunchAgents/com.grepai.watch.plist

Linux (systemd)

Create ~/.config/systemd/user/grepai-watch.service:

[Unit]
Description=GrepAI Watch Daemon
After=network.target

[Service]
Type=simple
WorkingDirectory=/path/to/your/project
ExecStart=/usr/local/bin/grepai watch
Restart=always

[Install]
WantedBy=default.target

Enable:

systemctl --user enable grepai-watch
systemctl --user start grepai-watch

Checking Logs

# Background daemon logs
tail -f ~/.grepai/daemon.log

# Or with systemd
journalctl --user -u grepai-watch -f

Multiple Projects

One Daemon Per Project

Run separate daemons for each project:

# Terminal 1: Project A
cd /path/to/project-a
grepai watch --background

# Terminal 2: Project B
cd /path/to/project-b
grepai watch --background

Using Workspaces

For multi-project setups:

grepai workspace create my-workspace
grepai workspace add my-workspace /path/to/project-a
grepai workspace add my-workspace /path/to/project-b
grepai watch --workspace my-workspace

Troubleshooting

Daemon Won't Start

Problem: "Another daemon is already running" ✅ Solution:

grepai watch --stop
grepai watch --background

Problem: "Config not found" ✅ Solution: Initialize first:

grepai init
grepai watch

Problem: "Embedder connection failed" ✅ Solution: Start your embedding provider:

ollama serve  # For Ollama

Indexing Issues

Problem: Files not being indexed ✅ Solution: Check ignore patterns in config, ensure file extension is supported

Problem: Indexing very slow ✅ Solutions:

  • Use OpenAI for faster cloud embeddings
  • Add more ignore patterns
  • Increase chunking size

Problem: Index seems outdated ✅ Solution: Clear and reindex:

rm .grepai/index.gob
grepai watch

File Watch Issues

Problem: Changes not detected ✅ Solutions:

  • Reduce debounce_ms
  • Check inotify limits (Linux):
    echo 65536 | sudo tee /proc/sys/fs/inotify/max_user_watches
    

Best Practices

  1. Run in background: For continuous monitoring
  2. Use workspace for monorepos: Better organization
  3. Set up auto-start: launchd or systemd
  4. Check logs periodically: Monitor for errors
  5. Reindex after config changes: Especially after changing embedding model

Status Check

Regular health check:

grepai status

Output:

✅ GrepAI Status

   Project: /path/to/project
   Config: .grepai/config.yaml

   Embedder: Ollama (nomic-embed-text)
   Storage: GOB (.grepai/index.gob)

   Index:
   - Files: 245
   - Chunks: 1,234
   - Size: 12.5 MB
   - Last updated: 2025-01-28 10:30:00

   Daemon: Running (PID 12345)

Output Format

Watch daemon status:

✅ Watch Daemon Active

   Mode: Background
   PID: 12345
   Project: /path/to/project

   Initial Index:
   - Files scanned: 245
   - Chunks created: 1,234
   - Duration: 45s

   Real-time Monitor:
   - Debounce: 500ms
   - Events processed: 23
   - Last event: 5 minutes ago

   Next steps:
   - Run 'grepai search "query"' to search
   - Run 'grepai watch --status' to check status
   - Run 'grepai watch --stop' to stop daemon

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.545 reviews
  • M
    Maya HaddadDec 20, 2024

    grepai-watch-daemon fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • K
    Kwame GhoshDec 20, 2024

    grepai-watch-daemon is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • N
    Nia ChoiDec 12, 2024

    We added grepai-watch-daemon from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • A
    Aisha ReddyDec 12, 2024

    I recommend grepai-watch-daemon for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • G
    Ganesh MohaneDec 4, 2024

    grepai-watch-daemon is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Z
    Zaid MartinezDec 4, 2024

    Solid pick for teams standardizing on skills: grepai-watch-daemon is focused, and the summary matches what you get after install.

  • N
    Nia PerezNov 27, 2024

    grepai-watch-daemon fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • R
    Rahul SantraNov 23, 2024

    Useful defaults in grepai-watch-daemon — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • A
    Alexander MalhotraNov 15, 2024

    I recommend grepai-watch-daemon for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • A
    Aanya GillNov 11, 2024

    We added grepai-watch-daemon from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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