This release includes breaking changes for platform teams planning a safe upgrade.
✓ No known CVEs patched in this version
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Summary
AI summaryGraphenium adds a provenance-aware trust model and architectural analysis capabilities.
Full changelog
Graphenium v0.2.0
Provenance-aware structural memory for AI coding agents.
This release upgrades Graphenium from a basic code indexer to an
agent-grade codebase intelligence engine. Every edge now carries
provenance metadata so agents know exactly how much to trust the graph.
New in v0.2.0
Graph provenance and trust model:
extractorandresolution_statusfields on every edge and node- Tree-sitter edges marked
[tree-sitter:resolved], LLM edges by confidence - Cross-file import resolver marks edges
resolvedorunresolved - Schema versioning in graph.json metadata (schema 0.2.0)
graph_statsreports provenance and confidence breakdowns
Architectural analysis:
- Directed graph projections from undirected petgraph
- PageRank for architectural importance scoring
- Reverse reachability for blast radius analysis
- Community boundary crossing scores
- Rooted dominators for mandatory gateway identification
chokepoint_reportcombining multiple ranking signals
Symbol diff and impact analysis:
gm diffcommand for graph snapshot comparison- Symbol inventory diff: added, removed, community-changed
- Downstream impact via reverse reachability
- Risk-sorted review order recommendations
Hybrid retrieval:
gm query --modeflag:lexical,structural,hybrid- TF-based text embeddings with cosine similarity
- Node2Vec structural embeddings from random walks
Runtime telemetry (experimental):
- OTEL-compatible trace import
- P50/P95/P99 latency percentile estimation
- Hot path and runtime-weighted traversal
- Import module marks
telemetryas experimental
Diagnostics and documentation:
gm doctorreports schema version, extraction modes, languages- Competitive positioning in README with comparison table
- AI Skill updated with provenance guidance
- All 315 tests pass, 22 files changed, 5 new modules
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