- GETTING_STARTED.md: rewrite to cover both ruvector-core (VectorDB) and
rvf-runtime (RvfStore) APIs, add package registry table, fix SearchQuery
fields (ef_search not include_vectors), results use .score not .distance
- INSTALLATION.md: update crate version 0.1.0 -> 2.0, fix npm scoped
package names (@ruvector/*), remove non-existent Docker image, update
Rust version requirement to 1.80+, fix CLI docs to match actual subcommands
- BASIC_TUTORIAL.md: fix SearchQuery.include_vectors -> ef_search, fix
result.distance -> result.score, fix HnswConfig/QuantizationConfig field
access patterns (options.hnsw -> options.hnsw_config, wrap in Some())
- ADVANCED_FEATURES.md: same field name fixes, fix QuantizationConfig
wrapping in Some(), remove references to non-existent mmap_vectors field
- docs/README.md: update version to 2.0.4/0.1.100, update date
Co-Authored-By: claude-flow <ruv@ruv.net>
Research three GitHub projects sharing the OpenFang name:
- RightNow-AI/openfang: Rust-based Agent OS (most significant)
- anmaped/openfang: Camera firmware for Ingenic T20 (dormant)
- danshorstein/OpenFang: Python AI assistant fork
https://claude.ai/code/session_015KgxqLUhevxop1jhiZY2Y4
Implement trait-based IntelligenceProvider extension point for external
quality signals. Addresses PR #190 proposal (renumbered from ADR-029 to
avoid collision with existing ADR-029-rvf-canonical-format).
- IntelligenceProvider trait with load_signals() and quality_weights()
- FileSignalProvider built-in for JSON file-based signal exchange
- IntelligenceLoader for multi-provider registration and aggregation
- QualitySignal, QualityFactors, ProviderQualityWeights types
- calibration_bias() on TaskComplexityAnalyzer for router feedback
- 12 unit tests (all passing)
Co-Authored-By: claude-flow <ruv@ruv.net>
- solver_benchmark.rs: Store benchmark results in RVF for analysis
- Updated solver_witness.rs with refinements
- Updated examples/rvf/Cargo.toml with 3 new [[example]] entries
- Updated examples/rvf/src/lib.rs with new example documentation
- Refined AGI sublinear optimization review
https://claude.ai/code/session_01TiqLbr2DaNAntQHaVeLfiR
- All 10 ADR-STS documents updated from Proposed to Accepted
- Added implementation status sections reflecting delivered solver crate
- Updated SOTA research analysis to v3.0 with implementation realization
- Updated optimization guide to v2.0 with realized optimizations
- Updated executive summary, performance, algorithm, and testing docs
- Added solver_witness.rs RVF example
https://claude.ai/code/session_01TiqLbr2DaNAntQHaVeLfiR
Add 15 architecture and design documents covering the sublinear-time solver
integration into RuVector's 79-crate ecosystem:
ADR Documents (12):
- ADR-STS-001: Core integration architecture with trait hierarchy and event sourcing
- ADR-STS-002: Algorithm selection and sublinear routing with SONA adaptive learning
- ADR-STS-003: Memory management strategy with arena allocator and HNSW integration
- ADR-STS-004: WASM and cross-platform compilation with SIMD per architecture
- ADR-STS-005: Security model with STRIDE/DREAD analysis and witness chain audit
- ADR-STS-006: Benchmark framework with 6 Criterion.rs suites and CI regression
- ADR-STS-007: Feature flag and progressive rollout strategy
- ADR-STS-008: Error handling and fault tolerance with fallback chains
- ADR-STS-009: Concurrency model with Rayon+SIMD two-level parallelism
- ADR-STS-010: API surface design for Rust/WASM/NAPI/REST/MCP
- SOTA research analysis surveying 20+ papers and competitive landscape
- Optimization guide with SIMD/memory/algorithm/platform strategies
DDD Documents (3):
- Strategic design: 6 bounded contexts, context map, ubiquitous language
- Tactical design: aggregates, entities, value objects, domain services
- Integration patterns: ACLs, shared kernel, published language, event-driven
https://claude.ai/code/session_01TiqLbr2DaNAntQHaVeLfiR
Maps 7 concrete integration points between rvDNA genomics suite and
sublinear-time-solver: protein contact graph PageRank (500x speedup),
sparse attention solve in RVDNA format, joint variant calling with LD
(+15-30% sensitivity), sublinear Horvath clock regression, HNSW graph
optimization for pangenome k-mer search, network-based cancer detection
(3-5x sensitivity), and DNA storage/computation convergence.
Includes phased integration roadmap and scale impact analysis.
https://claude.ai/code/session_01WY4MpWoe2LMzkYUHLxhPHX
10 breakthrough vectors mapping concrete code paths to 50-year-ahead SOTA:
sub-constant time via predictive precomputation, self-discovering algorithms,
photonic-native vector ops, self-booting mathematical universes, neuromorphic
sublinear computing, hyperbolic sublinear geometry, cryptographic proof of
computation, temporal-causal vector spaces, infinite-scale sublinear consensus,
and the convergence of database + intelligence into a single substrate.
5-horizon roadmap from integration (2026) through convergence (2076).
https://claude.ai/code/session_01WY4MpWoe2LMzkYUHLxhPHX
Complete mathematical analysis of all 7 sublinear algorithms mapped to
ruvector's 9 subsystems. Top findings: Forward Push for hybrid graph
search (O(1/eps) vs O(k*d^L)), Conjugate Gradient for PDE attention
(quadratic to near-linear), Neumann Series for spectral filtering.
This completes the 15-agent analysis swarm - all documents present:
00-executive-summary, 01-14 covering crates, npm, rvf, examples,
architecture, wasm, mcp, performance, security, algorithms, typescript,
testing, dependencies, and roadmap.
https://claude.ai/code/session_01WY4MpWoe2LMzkYUHLxhPHX
Integration test design, property-based testing for solver correctness,
WASM test strategies, performance regression testing, and CI/CD pipeline
integration recommendations.
https://claude.ai/code/session_01WY4MpWoe2LMzkYUHLxhPHX
Full dependency tree comparison between ruvector (79 workspace members)
and sublinear-time-solver (9 crates), version conflicts, feature flag
compatibility, and bundle size impact.
https://claude.ai/code/session_01WY4MpWoe2LMzkYUHLxhPHX
Initial batch of research documents from 15-agent analysis swarm analyzing
integration between ruvector and sublinear-time-solver. Covers NPM packages,
RVF format, architecture, and TypeScript type compatibility.
More documents pending from running agents (crates, WASM, MCP, performance,
security, algorithms, testing, dependencies, roadmap, executive summary).
https://claude.ai/code/session_01WY4MpWoe2LMzkYUHLxhPHX
Plans the integration path for .rvf acceptance test verification into
the npm ecosystem:
- npx ruvector rvf verify-witness <file.rvf> (N-API + WASM fallback)
- npx rvlite verify-witness <file.rvf> (WASM via cli-rvf.ts)
- rvlite SDK verifyWitnessChain() for browser-side verification
- MCP tool rvf_verify_witness for Claude Code agents
- 5-phase implementation plan, each independently shippable
Bridges the rvf_witness_verify WASM export (ADR-037) to end users
without requiring the Rust toolchain.
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
Plans the integration path for .rvf acceptance test verification into
the npm ecosystem:
- npx ruvector rvf verify-witness <file.rvf> (N-API + WASM fallback)
- npx rvlite verify-witness <file.rvf> (WASM via cli-rvf.ts)
- rvlite SDK verifyWitnessChain() for browser-side verification
- MCP tool rvf_verify_witness for Claude Code agents
- 5-phase implementation plan, each independently shippable
Bridges the rvf_witness_verify WASM export (ADR-037) to end users
without requiring the Rust toolchain.
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
- Resolve open questions: repo automation as first domain, four-level
AuthorityLevel enum, per-task ResourceBudget with hard caps,
CoherenceThresholds with validation
- Add AGI_MAX_CONTAINER_SIZE (16 GiB) with enforcement in validation
- Tighten ContainerSegments::validate: Verify/Live modes now require
world model data (VEC or INDEX segments), not just kernel/WASM
- Add ContainerError variants: InsufficientAuthority, BudgetExhausted
- Add to_flags support for orchestrator_present and world_model_present
- Add wire format section and cross-references to ADRs 029-033 in doc
- Add 2 new TLV tags: AUTHORITY_CONFIG (0x0110), DOMAIN_PROFILE (0x0111)
- Re-export new types from lib.rs
- Update rvf-runtime tests for tightened validation
- All 222 rvf-types + all rvf-runtime tests pass
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
- Resolve open questions: repo automation as first domain, four-level
AuthorityLevel enum, per-task ResourceBudget with hard caps,
CoherenceThresholds with validation
- Add AGI_MAX_CONTAINER_SIZE (16 GiB) with enforcement in validation
- Tighten ContainerSegments::validate: Verify/Live modes now require
world model data (VEC or INDEX segments), not just kernel/WASM
- Add ContainerError variants: InsufficientAuthority, BudgetExhausted
- Add to_flags support for orchestrator_present and world_model_present
- Add wire format section and cross-references to ADRs 029-033 in doc
- Add 2 new TLV tags: AUTHORITY_CONFIG (0x0110), DOMAIN_PROFILE (0x0111)
- Re-export new types from lib.rs
- Update rvf-runtime tests for tightened validation
- All 222 rvf-types + all rvf-runtime tests pass
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
Defines the full system boundary for portable intelligence:
- RuVector as existential substrate (world model, coherence signals)
- RVF as cognitive container format (packaging, witness chains, replay)
- Claude Code as control plane orchestrator (planning, tool use)
- Claude Flow as swarm coordinator (routing, shared memory, learning)
Key mechanisms:
- Structural health gates (min-cut coherence, contradiction pressure)
- Skill promotion with counterexample requirements
- Two execution modes: Replay (bit-identical) and Verify (same grades)
- 10 node types, 9 edge types, 4 invariants for the world model schema
- MCP tools: ruvector_query, ruvector_cypher, rvf_snapshot, eval_run
Acceptance test: same RVF artifact, two machines, 100 tasks,
95+ passing in verify mode, zero policy violations.
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
Defines the full system boundary for portable intelligence:
- RuVector as existential substrate (world model, coherence signals)
- RVF as cognitive container format (packaging, witness chains, replay)
- Claude Code as control plane orchestrator (planning, tool use)
- Claude Flow as swarm coordinator (routing, shared memory, learning)
Key mechanisms:
- Structural health gates (min-cut coherence, contradiction pressure)
- Skill promotion with counterexample requirements
- Two execution modes: Replay (bit-identical) and Verify (same grades)
- 10 node types, 9 edge types, 4 invariants for the world model schema
- MCP tools: ruvector_query, ruvector_cypher, rvf_snapshot, eval_run
Acceptance test: same RVF artifact, two machines, 100 tasks,
95+ passing in verify mode, zero policy violations.
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
