Review fixes:
- Fix XSS vulnerability in PlanetDashboard.ts (sanitize innerHTML with API data)
- Fix SNR variance calculation in planet_detection.rs (use out-of-transit only)
- Fix sort comparator for string columns in PlanetDashboard.ts
- Fix material/texture memory leaks in PlanetSystem3D.ts (dispose on clearSystem/destroy)
- Fix camera auto-rotate drift by storing intended radius
- Use Kepler's third law for semi-major axis calculation
- Seed orbit eccentricity/inclination from candidate ID for reproducibility
- Add metadata field constants (replace magic numbers)
- Document synthetic embedding limitation
- Fix ADR-040 typo ("two-machinevisu" → "two-machine")
New feature:
- Add microlensing_detection.rs example with M0-M3 pipeline for rogue planet
and exomoon candidate detection using synthetic OGLE/MOA-style light curves
with Paczynski PSPL fitting, residual anomaly detection, and coherence gating
https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- Single-file HTML demo with modern dark theme UI
- Drag & drop image upload + camera capture
- Real-time embedding extraction and visualization
- Similarity matrix comparing multiple images
- Performance metrics display (~5ms per image)
- Falls back to demo mode if WASM fails to load
- ADR-089 documenting the approach
Deploy to: https://ruvnet.github.io/ruvector/demo/cnn/
Co-authored-by: Reuven <cohen@ruv-mac-mini.local>
Defines a cognition kernel for the Agentic Age with 6 primitives
(task, capability, region, queue, timer, proof), 12 syscalls, and
RVF as the native boot object. Includes coherence-aware scheduler,
proof-gated mutation as kernel invariant, seL4-inspired capabilities,
io_uring-style queue IPC, 8 demo applications, and a two-phase build
path (Linux-hosted nucleus → bare metal AArch64).
Co-Authored-By: claude-flow <ruv@ruv.net>
Adds browser WASM bindings for neural-trader-core, coherence, and replay
crates using the established wasm-bindgen pattern. Includes BigInt-safe
serialization, hex ID helpers, 10 unit tests, 43 Node.js smoke tests,
comprehensive README, and animated dot-matrix visuals for π.ruv.io.
Co-Authored-By: claude-flow <ruv@ruv.net>
- Rename ADR-084-neural-trader to ADR-085 (ADR-084 is taken by ruvllm-wasm-publish)
- Move serde_json to dev-dependencies in neural-trader-core (only used in tests)
- Remove unused neural-trader-core dependency from neural-trader-coherence
Co-Authored-By: claude-flow <ruv@ruv.net>
Bridge the gap between "stores knowledge" and "learns from knowledge":
- Background training loop (tokio::spawn, 5 min interval) runs SONA
force_learn + domain evolve_population when new data arrives
- POST /v1/train endpoint for on-demand training cycles
- `ruvector brain train` CLI command with --json support
- `brain_train` MCP tool for agent-triggered training
- Vote dedup: 24h TTL on ip_votes entries, author exemption from IP check
- ADR-082 updated, ADR-083 created
Results: Pareto frontier grew 0→24 after 3 cycles. SONA activates
after 100+ trajectory threshold (natural search/share usage).
Publish ruvector@0.2.11.
* feat: proxy-aware fetch + brain API improvements — publish v0.2.7
Add proxyFetch() wrapper to cli.js and mcp-server.js that detects
HTTPS_PROXY/HTTP_PROXY/ALL_PROXY env vars, uses undici ProxyAgent
(Node 18+) or falls back to curl. Handles NO_PROXY patterns.
Replaced all 17 fetch() call sites with timeouts (15-30s).
Brain server API:
- Search returns similarity scores via ScoredBrainMemory
- List supports pagination (offset/limit), sorting (updated_at/quality/votes), tag filtering
- Transfer response includes warnings, source/target memory counts
- New POST /v1/verify endpoint with 4 verification methods
Co-Authored-By: claude-flow <ruv@ruv.net>
* feat: brain server bug fixes, GET /v1/pages, 9 MCP page/node tools — v0.2.10
Fix proxyFetch curl fallback to capture real HTTP status instead of
hardcoding 200, add 204 guards to brainFetch/fetchBrainEndpoint/MCP
handler, fix brain_list schema (missing offset/sort/tags), fix
brain_sync direction passthrough, add --json to share/vote/delete/sync.
Add GET /v1/pages route with pagination, status filter, sort.
Add 9 MCP tools: brain_page_list/get/create/update/delete,
brain_node_list/get/publish/revoke (previously SSE-only).
Polish: delete --json returns {deleted:true,id} not {}, page get
unwraps .memory wrapper for formatted display.
112 MCP tools, 69/69 tests pass. Published v0.2.10 to npm.
Co-Authored-By: claude-flow <ruv@ruv.net>
- Introduced QUICKSTART.md for RuVector, detailing setup, usage, and architecture.
- Added ruvector-knowledge.rvf.json for comprehensive project metadata, including architecture overview, crate taxonomy, and critical decisions.
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>
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
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
Complete the QR Cognitive Seed pipeline with zero external dependencies:
- Pure SHA-256 (FIPS 180-4) verified against NIST test vectors
- HMAC-SHA256 (RFC 2104) verified against RFC 4231 test cases
- LZ77 compression (SCF-1 format) with 4KB sliding window
- Seed crypto: content hashing, signing, layer verification
- C FFI (5 extern "C" functions) for App Clip / mobile integration
- SeedBuilder.build_and_sign() with automatic hashing and signing
- ParsedSeed.verify_all() with full integrity and signature checks
- ParsedSeed.decompress_microkernel() using built-in LZ
- 11 end-to-end integration tests with real cryptography
- Updated ADR-034 with App Clip, PWA, Android delivery paths
- Example updated with full real-crypto round-trip demo
Total: 381 tests passing (183 types + 154 runtime + 11 e2e + 33 manifest)
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
Three fixes to ADR-033:
1. ResultQuality split into RetrievalQuality (per-candidate) and
ResponseQuality (per-response at API boundary). ResponseQuality
survives serialization across JSON/gRPC/MCP. DegradationReason
provides structured, inspectable evidence for why quality dropped.
2. Brute-force safety net dual-budgeted: max 5ms wall-clock AND max
50K candidates, whichever hits first. Both configurable via
QueryOptions. Budget=0 disables fallback entirely. Prevents O(N)
DoS from adversarial queries on large hot caches.
3. Mandatory acceptance test: malicious tail manifest with valid CRC
but redirected hotset pointers must fail deterministically under
Strict policy with a logged, stable error code. Separate test for
re-signed forgery (wrong signer vs no signature distinction).
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
Addresses four structural weaknesses in the progressive indexing system:
1. Content-addressed centroid stability — hotset pointers verified by
SHAKE-256 content hashes, not just byte offsets. Compaction becomes
physically destructive but logically stable.
2. Adversarial distribution resilience — distance entropy detection
with adaptive n_probe widening. Silent recall collapse replaced by
detected degradation with ResultQuality signaling.
3. Honest recall framing — empirical targets scoped to distribution
classes (natural/synthetic/adversarial). Monotonic recall improvement
property proven from append-only invariant. Brute-force safety net
when candidate count is insufficient.
4. Mandatory manifest signatures — SecurityPolicy defaults to Strict.
No signature = no mount in production. Prevents segment-swap attacks
on hotset pointers. CRC32C catches corruption; ML-DSA-65 catches
adversaries.
https://claude.ai/code/session_01RnwD4x5cbpB7FPvoyYQz8G
