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by justinlords
148 days ago
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This is exactly what I've been screaming about, AI coding assistants are basically playing guess the impact with our production code. The fact that you're exposing actual call graphs and blast radius through MCP tools instead of making Claude hallucinate dependencies is huge from my pov. Installing this now to test with our multi-repo setup. Does the telemetry integration for dead code detection require specific instrumentation? does it hook into existing APM tools? |
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See docs: https://codeknowledge.dev/docs/Federation
On dead code detection: CKB has two modes:
1. Static analysis (findDeadCode tool, v7.6+) - requires zero instrumentation. Uses the SCIP index to find symbols with no inbound references in the codebase. Good for finding obviously dead exports, unused internal functions, etc. No telemetry needed. 2. Telemetry-enhanced (findDeadCodeCandidates, v6.4+) - ingests runtime call data to find code that exists but is never executed in production. This is where APM integration comes in.
For the telemetry integration: It hooks into any OTEL-compatible collector. No custom instrumentation required, it parses standard OTLP metrics:
- span.calls, http.server.request.count, rpc.server.duration_count, grpc.server.duration_count - Extracts function/namespace/file from span attributes (configurable via telemetry.attributes.functionKeys, etc.)
You'd configure a pipeline from your APM (Datadog, Honeycomb, Jaeger, whatever) to forward aggregated call counts to CKB's ingest endpoint. The matcher then correlates runtime function names to SCIP symbol
IDs with confidence scoring (exact: file+function+line, strong: file+function, weak: namespace+function only).
Full setup: https://codeknowledge.dev/docs/Telemetry
The static analysis mode is probably enough to start with. Telemetry integration is for when you want "this code hasn't been called in 90 days" confidence rather than "this code has no static references."