MCPInstall

grepai-config-reference

by yoanbernabeu

Complete configuration reference for GrepAI. Use this skill when you need to understand all available configuration options.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-config-reference
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads grepai-config-reference automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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: postgres  # Scalable storage
  postgres:
    dsn: postgres://user:pass@localhost:5432/grepai
chunking:
  size: 768  # Larger chunks
  overlap: 100

Team Environment

version: 1
embedder:
  provider: openai
  model: text-embedding-3-small
  api_key: ${OPENAI_API_KEY}
  parallelism: 8
store:
  backend: qdrant
  qdrant:
    endpoint: qdrant.internal.company.com
    port: 6334
    use_tls: true

Maximum Privacy

version: 1
embedder:
  provider: ollama
  model: nomic-embed-text
  endpoint: http://localhost:11434
store:
  backend: gob  # Local file only

Environment Variables

GrepAI supports environment variable substitution:

embedder:
  api_key: ${OPENAI_API_KEY}

store:
  postgres:
    dsn: ${DATABASE_URL}

Set in your shell:

export OPENAI_API_KEY="sk-..."
export DATABASE_URL="postgres://..."

Validating Configuration

Check your config is valid:

grepai status

If there are config errors, they'll be displayed.

Configuration Precedence

  1. .grepai/config.yaml in current directory
  2. Workspace configuration (if using workspaces)
  3. Default values

Best Practices

  1. Start simple: Use defaults, optimize later
  2. Match chunking to code style: Larger chunks for verbose code
  3. Use boosting: Penalize test/vendor, boost src/lib
  4. Secure API keys: Use environment variables, never commit
  5. Exclude noise: Ignore generated files, dependencies

Output Format

Valid configuration status:

✅ GrepAI Configuration Valid

   Embedder: ollama (nomic-embed-text)
   Storage: gob (.grepai/index.gob)
   Chunking: 512 tokens, 50 overlap
   Trace mode: fast
   Languages: 18 enabled
   Ignore patterns: 12 configured
   Boosting: enabled

FAQ

What does the grepai-config-reference skill do?

Complete configuration reference for GrepAI. Use this skill when you need to understand all available configuration options.

How do I install grepai-config-reference?

Run npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-config-reference in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/grepai-config-reference/ (personal) or .claude/skills/grepai-config-reference/ (project).

Which AI agents can use grepai-config-reference?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is grepai-config-reference safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains grepai-config-reference?

It is published by yoanbernabeu in yoanbernabeu/grepai-skills. It has 691 recorded installs.

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