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Semantic Search

Find what you mean, not just what you say. Search by concept, not keywords.

Why Semantic Search Matters

Traditional keyword search is like looking for exact matches in a dictionary. Semantic search understands what you're actually looking for.

Keyword Search

  • ✗ Only finds exact word matches
  • ✗ Misses synonyms and related concepts
  • ✗ Fails with natural questions

Semantic Search

  • ✓ Understands meaning and context
  • ✓ Finds conceptually similar content
  • ✓ Works with natural language

Example

Search for "authentication" and you'll also find conversations about "login flows", "OAuth", "user sessions", and "JWT tokens" - even if those exact words weren't in your query.

Understanding Search Scores

Each result has a score showing how well it matches your query. Focus on results above 0.7 - those are almost always relevant.

0.85+Excellent - Use these

Directly relevant. These are what you're looking for.

0.70-0.84Good - Worth checking

Related content. May have useful context.

Below 0.70Weak - Usually skip

Probably not what you need.

Search Examples

See how semantic search finds related concepts, not just exact matches:

text
"How do I handle user authentication?"

Will also find conversations about:

  • • OAuth 2.0 implementation
  • • Login/signup flows
  • • JWT token management
  • • Session handling
  • • Password reset flows
text
"database performance issues"

Will also find conversations about:

  • • Slow query optimization
  • • Index creation
  • • N+1 query problems
  • • Connection pooling
  • • Database scaling

Query vs Browse

Spaces has two ways to find your snapshots:

query-workspace

Best when searching for something specific

javascript
query-workspace({
  query: "authentication decisions"
})
  • ✓ Semantic similarity ranking
  • ✓ Natural language queries
  • ✓ Finds related concepts

list-snapshots

Best for browsing or filtering

javascript
list-snapshots({
  category: "implementation",
  limit: 20
})
  • ✓ Chronological ordering
  • ✓ Category/scope filtering
  • ✓ Pagination support

Writing Better Queries

Good Queries

  • "How did we implement authentication?"
  • "database performance optimization approaches"
  • "What framework did we choose for the frontend?"
  • "discussions about API versioning"

Why they work: Natural language, specific topics, complete thoughts

Less Effective Queries

  • "auth" - Too broad, lacks context
  • "fix bug yesterday" - Temporal references don't help
  • "that thing we talked about" - Too vague

Tip: Be specific about technical topics, not time or vague references