grepai-config-reference

yoanbernabeu/grepai-skills · updated Apr 8, 2026

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$npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-config-reference
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summary

This skill provides a complete reference for all GrepAI configuration options in .grepai/config.yaml.

skill.md

GrepAI Configuration Reference

This skill provides a complete reference for all GrepAI configuration options in .grepai/config.yaml.

When to Use This Skill

  • Understanding all available configuration options
  • Optimizing GrepAI for your specific use case
  • Troubleshooting configuration issues
  • Setting up advanced configurations

Configuration File Location

/your/project/.grepai/config.yaml

Complete Configuration Schema

version: 1

# ═══════════════════════════════════════════════════════════════
# EMBEDDER CONFIGURATION
# Converts code text into vector embeddings
# ═══════════════════════════════════════════════════════════════
embedder:
  # Provider: ollama | openai | lmstudio
  provider: ollama

  # Model name (depends on provider)
  # Ollama: nomic-embed-text, bge-m3, mxbai-embed-large
  # OpenAI: text-embedding-3-small, text-embedding-3-large
  # LM Studio: nomic-embed-text-v1.5, bge-small-en-v1.5
  model: nomic-embed-text

  # API endpoint URL
  # Ollama default: http://localhost:11434
  # LM Studio default: http://localhost:1234
  # OpenAI: uses official API
  endpoint: http://localhost:11434

  # Vector dimensions (auto-detected if omitted)
  # nomic-embed-text: 768
  # text-embedding-3-small: 1536
  # text-embedding-3-large: 3072
  dimensions: 768

  # API key (for OpenAI, supports env vars)
  api_key: ${OPENAI_API_KEY}

  # Parallel requests (OpenAI only, for speed)
  parallelism: 4

# ═══════════════════════════════════════════════════════════════
# STORE CONFIGURATION
# Where vector embeddings are stored
# ═══════════════════════════════════════════════════════════════
store:
  # Backend: gob | postgres | qdrant
  backend: gob

  # PostgreSQL configuration (when backend: postgres)
  postgres:
    dsn: postgres://user:password@localhost:5432/grepai

  # Qdrant configuration (when backend: qdrant)
  qdrant:
    endpoint: localhost
    port: 6334
    use_tls: false
    api_key: your-qdrant-api-key  # Optional

# ═══════════════════════════════════════════════════════════════
# CHUNKING CONFIGURATION
# How code files are split for embedding
# ═══════════════════════════════════════════════════════════════
chunking:
  # Tokens per chunk (smaller = more precise, larger = more context)
  # Recommended: 256-1024
  size: 512

  # Overlap between chunks (preserves context at boundaries)
  # Recommended: 10-20% of size
  overlap: 50

# ═══════════════════════════════════════════════════════════════
# WATCH CONFIGURATION
# File watching daemon settings
# ═══════════════════════════════════════════════════════════════
watch:
  # Debounce delay in milliseconds
  # Groups rapid file changes together
  debounce_ms: 500

# ═══════════════════════════════════════════════════════════════
# TRACE CONFIGURATION
# Call graph analysis settings
# ═══════════════════════════════════════════════════════════════
trace:
  # Extraction mode: fast | precise
  # fast: Uses regex, no dependencies, faster
  # precise: Uses tree-sitter AST parsing, more accurate
  mode: fast

  # Languages to analyze for call graphs
  enabled_languages:
    - .go
    - .js
    - .ts
    - .jsx
    - .tsx
    - .py
    - .php
    - .c
    - .h
    - .cpp
    - .hpp
    - .cc
    - .cxx
    - .rs
    - .zig
    - .cs
    - .pas
    - .dpr

  # Patterns to exclude from trace analysis
  exclude_patterns:
    - "*_test.go"
    - "*.spec.ts"
    - "*.test.js"

# ═══════════════════════════════════════════════════════════════
# SEARCH CONFIGURATION
# Search result scoring and ranking
# ═══════════════════════════════════════════════════════════════
search:
  # Score boosting configuration
  boost:
    enabled: true

    # Reduce scores for certain paths
    penalties:
      - pattern: /tests/
        factor: 0.5
      - pattern: _test.
        factor: 0.5
      - pattern: .spec.
        factor: 0.5
      - pattern: /docs/
        factor: 0.6
      - pattern: /vendor/
        factor: 0.3
      - pattern: /node_modules/
        factor: 0.3

    # Increase scores for certain paths
    bonuses:
      - pattern: /src/
        factor: 1.1
      - pattern: /lib/
        factor: 1.1
      - pattern: /core/
        factor: 1.2
      - pattern: /app/
        factor: 1.1

  # Hybrid search (vector + keyword)
  hybrid:
    enabled: false
    k: 60  # BM25 parameter

# ═══════════════════════════════════════════════════════════════
# IGNORE CONFIGURATION
# Files and directories to exclude from indexing
# ═══════════════════════════════════════════════════════════════
ignore:
  # Directories
  - .git
  - .grepai
  - .svn
  - .hg
  - node_modules
  - vendor
  - target
  - __pycache__
  - .pytest_cache
  - dist
  - build
  - out
  - .next
  - .nuxt

  # Files
  - "*.min.js"
  - "*.min.css"
  - "*.bundle.js"
  - "*.map"
  - "*.lock"
  - package-lock.json
  - yarn.lock
  - pnpm-lock.yaml
  - go.sum

  # Generated
  - "*.generated.*"
  - "*.pb.go"
  - "*.d.ts"

Configuration by Use Case

Small Personal Project

version: 1
embedder:
  provider: ollama
  model: nomic-embed-text
store:
  backend: gob
chunking:
  size: 512
  overlap: 50

Large Codebase

version: 1
embedder:
  provider: ollama
  model: bge-m3  # Larger model
  parallelism: 4
store:
  backend: pos
how to use grepai-config-reference

How to use grepai-config-reference 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 development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add grepai-config-reference
2

Execute installation 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-config-reference

The skills CLI fetches grepai-config-reference from GitHub repository yoanbernabeu/grepai-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/grepai-config-reference

Reload or restart Cursor to activate grepai-config-reference. Access the skill through slash commands (e.g., /grepai-config-reference) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

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

Installation Steps

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

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.626 reviews
  • Sakura Chawla· Dec 12, 2024

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

  • Ama Garcia· Nov 3, 2024

    grepai-config-reference reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Kwame Robinson· Oct 22, 2024

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

  • Rahul Santra· Sep 17, 2024

    grepai-config-reference reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Noah Desai· Sep 13, 2024

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

  • Pratham Ware· Aug 8, 2024

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

  • Olivia Chen· Aug 4, 2024

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

  • Yash Thakker· Jul 27, 2024

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

  • Noah Tandon· Jul 23, 2024

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

  • Dhruvi Jain· Jun 18, 2024

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

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