Use this when deciding between semantic search and grep/glob for code discovery. Apply for concept-based queries (find payment processing), intent-based searches (how is auth implemented), or when user doesn't know exact class names. Use grep for exact matches like specific function names
Scanned 9/8/2026
Install to Claude Code
npx -y skills add mattnigh/skills_collection --skill collection --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Collection?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/mattnigh-collection-0797420b)More formats (shields.io, HTML) on the badges page.
---
name: "semantic-search"
description: "Use this when deciding between semantic search and grep/glob for code discovery. Apply for concept-based queries (find payment processing), intent-based searches (how is auth implemented), or when user doesn't know exact class names. Use grep for exact matches like specific function names"
categories: ["pattern", "technique", "search"]
tags: ["semantic-search", "weaviate", "embeddings", "discovery"]
version: "1.0.0"
---
# Semantic Search Technique
## Purpose
Decision framework and execution guide for using semantic search effectively in CodeCompass.
## When to Use Semantic Search
### ✅ Use Semantic Search When
**1. Concept-based Queries**
- "Find code that handles payment processing"
- "Where do we validate email addresses?"
- "Show me error handling patterns"
**2. Intent-based Queries**
- "How is user authentication implemented?"
- "What code calculates shipping costs?"
- "Find business rules for order approval"
**3. Cross-language/Cross-file**
- Searching across PHP, TypeScript, config files
- Pattern discovery across multiple modules
- Finding similar implementations
**4. Fuzzy/Exploratory**
- User doesn't know exact class/function names
- Exploring unfamiliar codebase
- "Code that does something like X"
**5. Natural Language**
- "Show me all database migrations"
- "Find controllers that handle file uploads"
- "Where are API rate limits defined?"
### ❌ Use Grep/Glob When
**1. Exact Matches**
- "Find class named `PaymentController`"
- "Where is `processPayment` function defined?"
- "Find all imports of `UserService`"
**2. Syntax Patterns**
- "Find all functions starting with `get`"
- "Show me all `@Injectable()` decorators"
- "Find TypeScript interfaces"
**3. Performance Critical**
- Quick lookups in known files
- Repeated searches in tight loops
- When you know exact location
**4. Structural Queries**
- "Find all `.ts` files in `src/modules`"
- "List all test files"
- "Show directory structure"
## Execution Guide
### Step 1: Formulate Effective Query
**❌ Bad Queries** (too vague):
- "payment"
- "code"
- "function"
**✅ Good Queries** (specific context):
- "business logic for processing customer payments and updating order status"
- "validation rules for user email and password requirements"
- "error handling patterns for database connection failures"
**Why**: More context = better semantic matching
**Formula**:
```
[Action/Purpose] for [Specific Entity] with [Context/Constraints]
```
**Examples**:
- "Extract business capabilities from Yii2 controllers"
- "Validation logic for user registration with email verification"
- "Database migration patterns for schema versioning"
### Step 2: Verify Indexing
**Before searching**, ensure codebase is indexed:
```bash
# Check if indexed
curl http://localhost:8081/v1/schema
# Should show collections like:
# - CodeContext
# - AtlasCode
```
**If not indexed**:
```bash
codecompass batch:index <path-to-codebase>
```
### Step 3: Execute Search
```bash
codecompass search:semantic "business logic for payment processing"
```
**Alternative** (if using as library):
```typescript
const results = await searchService.semanticSearch({
query: "business logic for payment processing",
limit: 10,
certainty: 0.7 // Minimum relevance score
});
```
### Step 4: Interpret Results
**Check relevance scores**:
- **>0.8**: Highly relevant (exact match)
- **0.7-0.8**: Good match (related)
- **0.6-0.7**: Moderate match (possibly relevant)
- **<0.6**: Weak match (may be noise)
**Verify context**:
- Does the returned code actually match intent?
- Are results from expected modules?
- Multiple related files found (good signal)
- Or isolated random matches (refine query)
### Step 5: Refine if Needed
**Too many results** (>50):
- Add more specific context to query
- Increase certainty threshold
- Add domain constraints ("in authentication module")
**Too few results** (<3):
- Broaden query (less specific)
- Lower certainty threshold
- Check if area is actually indexed
- Try related terms/synonyms
**Wrong results**:
- Rephrase query with different terminology
- Add negative constraints
- Try breaking into multiple specific queries
## Behind the Scenes
### Architecture
```
Query Text
↓
Ollama Embedding (mxbai-embed-large)
↓
1024-dimensional vector
↓
Weaviate Vector Search (cosine similarity)
↓
Ranked Results
```
### Key Components
**From `.ai/capabilities.json`**:
- **Module**: `search`, `vectorizer`, `weaviate`
- **Embedding**: Ollama mxbai-embed-large (1024 dimensions)
- **Vector DB**: Weaviate with HNSW indexing
- **Collections**: `CodeContext`, `AtlasCode`
**Configuration** (from `.env`):
```bash
EMBEDDING_SERVICE=ollama
OLLAMA_EMBEDDING_MODEL=mxbai-embed-large
OLLAMA_URL=http://localhost:11434
CODECOMPASS_WEAVIATE_URL=http://localhost:8081
```
## Advanced Patterns
### Pattern 1: Multi-Query Exploration
For complex questions, break into multiple searches:
```bash
# Instead of:
"authentication and authorization and session management"
# Do:
codecompass search:semantic "user authentication login process"
codecompass search:semantic "authorization and access control"
codecompass search:semantic "session management and tokens"
```
### Pattern 2: Iterative Refinement
```bash
# 1. Broad search
codecompass search:semantic "payment processing"
# 2. Review results, identify specific module
# 3. Narrow search
codecompass search:semantic "payment gateway integration in PaymentController"
# 4. Pinpoint implementation
codecompass search:semantic "Stripe API call for processing credit cards"
```
### Pattern 3: Cross-Domain Search
Search across different aspects:
```bash
# Code implementation
codecompass search:semantic "email validation logic"
# Tests
codecompass search:semantic "test cases for email validation"
# Configuration
codecompass search:semantic "email service configuration"
```
## Common Pitfalls
### ❌ Pitfall 1: Searching Before Indexing
**Symptom**: No results or error
**Solution**: Run `codecompass batch:index` first
### ❌ Pitfall 2: Too Vague Queries
**Symptom**: Returns everything or nothing useful
**Solution**: Add specific context and intent
### ❌ Pitfall 3: Expecting Exact Matches
**Symptom**: "Why didn't it find function `processPayment`?"
**Reason**: Semantic search is for concepts, not exact names
**Solution**: Use grep for exact matches
### ❌ Pitfall 4: Ignoring Relevance Scores
**Symptom**: Reading irrelevant results
**Solution**: Filter by score >0.7, ignore weak matches
### ❌ Pitfall 5: Single Query for Complex Questions
**Symptom**: Poor results for multi-faceted questions
**Solution**: Break into multiple targeted queries
## Decision Tree
```
┌─────────────────────────────────────┐
│ I need to find code that... │
└─────────────────────────────────────┘
↓
┌─────────┐
│ Know │ Exact class/function name?
│ exact │
│ name? │
└─────────┘
↙ ↘
YES NO
↓ ↓
Use Grep ┌─────────┐
│ Concept │ Searching by meaning/purpose?
│ search? │
└─────────┘
↙ ↘
YES NO
↓ ↓
Semantic ┌─────────┐
Search │ Pattern │ Looking for code pattern?
│ match? │
└─────────┘
↙ ↘
YES NO
↓ ↓
Use Glob Use both
(Glob + Semantic)
```
## Performance Considerations
### Speed
- **Grep**: Milliseconds (fast, synchronous)
- **Semantic Search**: 100-500ms (embedding + vector search)
**Tradeoff**: Semantic is slower but finds conceptually related code
### Token Cost (Embeddings)
- Each query → 1 embedding generation
- Ollama local → No API cost
- But consumes local compute
### Scaling
- Small codebase (<1K files): Either method fine
- Medium codebase (1K-10K files): Semantic search advantage grows
- Large codebase (>10K files): Semantic search essential
## Integration with Other Tools
### With Yii2 Analysis
```bash
# 1. Analyze Yii2 project
codecompass analyze:yii2 <path>
# 2. Index results
codecompass batch:index <path>
# 3. Explore with semantic search
codecompass search:semantic "Yii2 controller actions for user management"
```
### With Requirements Extraction
```bash
# 1. Extract requirements
codecompass requirements:extract
# 2. Search extracted requirements
codecompass search:semantic "business rules for order validation"
```
### With Weaviate Direct Query
```bash
# Alternative: Query Weaviate GraphQL API directly
curl -X POST http://localhost:8081/v1/graphql \
-H "Content-Type: application/json" \
-d '{
"query": "{
Get {
CodeContext(
nearText: { concepts: [\"payment processing\"] }
limit: 10
) {
content
filePath
}
}
}"
}'
```
## Related Skills
- `0-discover-capabilities.md` - How to discover modules
- `analyze-yii2-project.md` - Uses semantic search in workflow
## Related Modules
From `.ai/capabilities.json`:
- `search` - SearchService, IntegratedSearchService
- `vectorizer` - Ollama embedding generation
- `weaviate` - Vector database client
- `indexing` - File indexing pipeline
---
**Remember**: Semantic search finds code by **meaning**, not by **name**. Choose the right tool for the job.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!