This skill covers the grepai init command and project initialization.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongrepai-initExecute the skills CLI command in your project's root directory to begin installation:
Fetches grepai-init from yoanbernabeu/grepai-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate grepai-init. Access via /grepai-init in your agent's command palette.
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.
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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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This skill covers the grepai init command and project initialization.
grepai init createscd /path/to/your/project
grepai init
Running grepai init creates the .grepai/ directory with:
.grepai/
├── config.yaml # Configuration file
├── index.gob # Vector index (created by watch)
└── symbols.gob # Symbol index for trace (created by watch)
The generated config.yaml:
version: 1
embedder:
provider: ollama
model: nomic-embed-text
endpoint: http://localhost:11434
store:
backend: gob
chunking:
size: 512
overlap: 50
watch:
debounce_ms: 500
trace:
mode: fast
enabled_languages:
- .go
- .js
- .ts
- .jsx
- .tsx
- .py
- .php
- .c
- .h
- .cpp
- .hpp
- .cc
- .cxx
- .rs
- .zig
- .cs
- .pas
- .dpr
ignore:
- .git
- .grepai
- node_modules
- vendor
- target
- __pycache__
- dist
- build
| Setting | Default | Purpose |
|---|---|---|
provider |
ollama |
Local embedding generation |
model |
nomic-embed-text |
768-dimension model |
endpoint |
http://localhost:11434 |
Ollama API URL |
| Setting | Default | Purpose |
|---|---|---|
backend |
gob |
Local file storage |
| Setting | Default | Purpose |
|---|---|---|
size |
512 |
Tokens per chunk |
overlap |
50 |
Overlap for context |
| Setting | Default | Purpose |
|---|---|---|
debounce_ms |
500 |
Wait time before re-indexing |
Default patterns exclude:
.git.grepainode_modules, vendortarget, dist, build__pycache__Edit .grepai/config.yaml to customize:
embedder:
provider: openai
model: text-embedding-3-small
api_key: ${OPENAI_API_KEY}
store:
backend: postgres
postgres:
dsn: postgres://user:pass@localhost:5432/grepai
ignore:
- .git
- .grepai
- node_modules
- "*.min.js"
- "*.bundle.js"
- coverage/
- .nyc_output/
For monorepos, init at the root:
cd /path/to/monorepo
grepai init
Or use workspaces for separate indices:
grepai workspace create my-workspace
grepai workspace add my-workspace /path/to/project1
grepai workspace add my-workspace /path/to/project2
If you need to reset:
# Remove existing config
rm -rf .grepai
# Re-initialize
grepai init
Warning: This deletes your index. You'll need to re-run grepai watch.
After init, verify with:
# Check config exists
cat .grepai/config.yaml
# Check status (will show no index yet)
grepai status
❌ Problem: .grepai already exists
✅ Solution: Delete it first or edit existing config:
rm -rf .grepai && grepai init
❌ Problem: Config created but Ollama not running
✅ Solution: Start Ollama before running grepai watch:
ollama serve
❌ Problem: Wrong directory initialized
✅ Solution: Remove .grepai and init in correct directory
.grepai/ to .gitignore: Index is machine-specific# GrepAI
.grepai/
After successful initialization:
✅ GrepAI Initialized
Config: .grepai/config.yaml
Default settings:
- Embedder: Ollama (nomic-embed-text)
- Storage: GOB (local file)
- Chunking: 512 tokens, 50 overlap
Next steps:
1. Ensure Ollama is running: ollama serve
2. Start indexing: grepai watch
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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I recommend grepai-init for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: grepai-init is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: grepai-init is focused, and the summary matches what you get after install.
We added grepai-init from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added grepai-init from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: grepai-init is the kind of skill you can hand to a new teammate without a long onboarding doc.
grepai-init reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for grepai-init matched our evaluation — installs cleanly and behaves as described in the markdown.
grepai-init fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
grepai-init fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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