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ForwardLane Hybrid Code Search
x402
ForwardLane Hybrid Code Search is a paid API for AI agents from agents.forwardlane.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-19).
Performs hybrid BM25 plus vector search with reciprocal rank fusion over Function and Class nodes in code repositories, with filtering by repo, domain, ontology concept, confidence, and test coverage.
Price / call$0.05
Success—
StatusUnknown
How this service works
BM25 plus vector search with reciprocal rank fusion over Function and Class nodes, with repository, domain, ontology concept, confidence, and test-coverage filters.
Output
Returns a ranked list of Function or Class code nodes with associated metadata including repository, confidence scores, ontology concept links, test coverage status, and relevance rankings derived from reciprocal rank fusion of BM25 and vector similarity scores.
Example use cases
Find tested payment functions in a repo
“Search the 'payments-core' repository for Function nodes related to 'charge processing' using hybrid search, only show me results that have test coverage and a confidence score above 0.75, top 20 results.”
Semantic code discovery by ontology concept
“Find all Class nodes in my codebase that are linked to the ontology concept URI 'http://schema.org/Person' — use hybrid search mode and return the top 15 matches across any repository.”
Cross-domain function search for an agent
“I need to find functions in the 'data-pipeline' domain related to 'schema validation' — use hybrid search, filter node type to Function, and give me up to 30 results ranked by relevance.”
Technical details
Endpoint
GEThttps://agents.forwardlane.com/api/search/hybridWhen to prefer
Choose this endpoint when you need the best of both keyword and semantic code search — it combines BM25 lexical matching with vector similarity and fuses rankings, outperforming either alone. Prefer it over the pure vector search sibling when exact identifiers or method names matter alongside conceptual similarity. Use when you need fine-grained filters like confidence thresholds, test coverage, ontology concept alignment, or repository scoping.
Side effects
- Missing required query parameter 'q' returns a 400 validation error
- Invalid node_type value returns a schema validation error
- Unknown repository name in 'repo' filter returns empty results
- ontology_concept_uri that doesn't match any indexed concept returns empty list
- top_k out of range (below 1 or above 200) returns a 422 error
- Payment of 0.05 USDC not completed returns 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Tags
x402
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