Brainy 7.30 shipped opt-in subtype enforcement; SDK 3.20.0 then registered
SDK_CORE_VOCABULARY on every consumer's brain (Event, Collection, Message,
Contract, Media, Document NounTypes). On 2026-06-08 Venue's /book flow went 500
because their brain.add({ type: NounType.Event, ... }) call sites lacked
subtype. An audit of Brainy's OWN source revealed 14 HIGH-risk internal write
paths that also omit subtype — any consumer running the same vocabulary would
have hit Brainy's infrastructure paths next. 7.30.1 closes both gaps before
8.0 makes strict mode the default.
Additive across the board. Zero behavior change for consumers not using strict
mode. Every change is JS-side — Cortex needs no work for 7.30.1.
NEW — brain.audit() diagnostic
- Read-only method walking storage.getNouns() / getVerbs() pagination
- Returns { entitiesWithoutSubtype: { type: count }, relationshipsWithoutSubtype,
total, scanned, recommendation }
- VFS infrastructure entities excluded by default (they bypass enforcement via
isVFSEntity marker); pass { includeVFS: true } to surface them
- The companion to migrateField (7.x) and fillSubtypes (8.0): tells consumers
exactly what would break under strict enforcement, deterministically
NEW — Improved enforcement error messages
- Caller's source location extracted from Error().stack so users see their own
call site, not a Brainy internal frame
- Specific guidance branches: registered vocabulary → "Pass one of: a, b, c";
brain-wide strict mode → mentions the except clause; otherwise → registration
recipe via brain.requireSubtype()
- Documentation link to the canonical migration recipe
- Same shape for noun and verb enforcement
NEW — CLI --subtype flag
- brainy add and brainy relate gain -s/--subtype <value>
- Defaults to 'cli-add' / 'cli-relate' so the CLI works against strict-mode
brains without the user needing to know the vocabulary in advance
INTERNAL — every Brainy write path now sets subtype
- VFS Contains edges (5 sites at lines 503/905/1694/1772/1886) → 'vfs-contains'
- VFS symlink entity → 'vfs-symlink' (NEW — distinct from 'vfs-file')
- VFS copy-file → preserves source subtype, falls back to 'vfs-file'
- VFS symlink also adopts the isVFSEntity infrastructure marker so it bypasses
enforcement in strict mode
- Aggregation materializer (Measurement entities) → 'materialized-aggregate'
- ImportCoordinator (3 sites): document → 'import-source'; entities →
options.defaultSubtype ?? 'imported'; placeholder → 'import-placeholder'
- SmartImportOrchestrator (4 entity sites + 2 batch relate sites): same
precedence (extractor → options.defaultSubtype → 'imported')
- EntityDeduplicator → candidate.subtype ?? 'imported'
- UniversalImportAPI → extractor → 'extracted' for both entities and relations
- NeuralImport → adds defaultSubtype to NeuralImportOptions; precedence same
- GoogleSheetsIntegration → request body 'subtype' ?? 'imported-from-sheets'
- ODataIntegration → request body 'Subtype' ?? 'imported-from-odata'
- MCP client message storage → 'mcp-message' (also fixes pre-existing missing
data field and missing type by aliasing from the prior text field)
Side-effect fix: storage.getNouns() paginated now surfaces subtype to top-level
- Single-noun getNoun() already did this in 7.30; the paginated path was missed
- Without this fix brain.audit() saw missing subtype on entities that actually
had one (caught by the strict-mode self-test before release)
NEW — tests/integration/strict-mode-self-test.test.ts (13 tests)
- Creates a brain under the exact SDK_CORE_VOCABULARY shape Venue hit + brain-
wide strict mode
- Exercises every internal Brainy path: VFS root + mkdir + writeFile + cp + mv
+ ln + symlink; aggregation engine; audit diagnostic with includeVFS toggle
- Validates error message UX: caller location, vocabulary guidance, brain-wide
strict mode guidance, off-vocabulary value reporting
Docs
- New "Strict mode in practice" section in docs/guides/subtypes-and-facets.md
covering the SDK_CORE_VOCABULARY pattern, 4-step migration recipe
(audit → migrateField → hand-fix → re-audit), the Brainy-internal label
reference table, and an 8.0 forward-look on fillSubtypes()
- docs/api/README.md: new audit() entry, strict-mode tips on add() and relate()
- RELEASES.md: full 7.30.1 entry
Cortex parity (forward-looking, not blocking 7.30.1)
- 6th open question added to .strategy/BRAINY-8.0-SUBTYPE-CONTRACT.md: native
fast path for audit() and fillSubtypes() via column-store null-subtype
bitmap for billion-scale brains
- Cortex should add a parity test mirroring strict-mode-self-test.test.ts
against their native paths to catch any latent bug where native writes
bypass JS validation
- Brainy-internal subtype labels become a documented part of the 8.0 contract
(useful for Cortex telemetry surfacing Brainy-managed infrastructure %)
Verification
- npx tsc --noEmit: clean
- npm test: 1468/1468 unit
- 7.29 noun integration suite: 26/26 (no regression)
- 7.30 verb subtype + enforcement integration suite: 30/30 (no regression)
- New strict-mode-self-test integration suite: 13/13
- npm run build: clean
- Closed-source product reference audit: clean
Addresses VE-SUBTYPE-MIGRATION (Venue's reported request) and ships internal
labels Venue did NOT ask for but that would have broken them next under their
own vocabulary registration.
Promotes `subtype?: string` to a top-level standard field on every entity,
alongside `type` / `confidence` / `weight`. Flat string, no hierarchy — the
consumer-chosen vocabulary for sub-classifying entities within a NounType
(Person → employee/customer, Document → invoice/contract, etc.).
Layer 1 — subtype field + rollup
- HNSWNounWithMetadata.subtype + STANDARD_ENTITY_FIELDS entry
- Entity / Result / AddParams / UpdateParams / FindParams threading
- add()/update() persist subtype on storageMetadata + entityForIndexing
- get()/find() route through the standard-field fast path
- subtypeCountsByType (Map<NounTypeIdx, Map<subtype, count>>) on
BaseStorage, mirrored after nounCountsByType with the same self-heal
rebuild and persisted to _system/subtype-statistics.json
- brain.counts.bySubtype(type, subtype?) — O(1) point + breakdown
- brain.counts.topSubtypes(type, n) — top-N by count
- brain.subtypesOf(type) — distinct subtypes seen
- find({ type, subtype }) and find({ subtype: ['a','b'] }) on the fast path
Layer 2 — trackField for other facets
- brain.trackField(name, { perType?, values? }) registers a field for
cardinality + per-NounType breakdown stats. Backed by the aggregation
engine (auto-defines __fieldCounts__<name>), backfill-on-define applies.
- brain.counts.byField(name, { type? }) returns value frequencies
- Optional vocabulary whitelist rejects off-vocabulary writes at add/update
Layer 3 — generic migrateField
- brain.migrateField({ from, to, readBoth?, batchSize?, onProgress? })
streams every entity, copies the value from one path to another, and
(unless readBoth) clears the source. Supports top-level standard fields,
metadata.X, and data.X paths. Idempotent — safe to re-run.
Docs
- New guide: docs/guides/subtypes-and-facets.md (Layer 1 + 2 + 3)
- README, DATA_MODEL, QUERY_OPERATORS, api/README, finite-type-system,
quick-start all treat subtype as a core primitive with anonymous example
vocabularies (employee/customer/invoice/milestone).
Tests
- 26 new integration tests covering write/read/update/delete round-trips,
counts rollup decrement + re-route on mutation, trackField + byField
with and without perType, vocabulary whitelist enforcement, and
migrateField for metadata.X → subtype and data.X → subtype paths
including readBoth deprecation-window semantics.
Unit suite: 1468/1468 passing. Type-check + build clean.
Add YAML frontmatter (slug, public, category, template, order) to 8
existing docs and 2 new getting-started guides (installation, quick-start).
Include docs/**/*.md in npm package files so the portal sync-docs script
can read them from node_modules after publish.
Update CLAUDE.md with docs pipeline trigger phrases and release checklist.
Add a write-time incremental aggregation engine that maintains running
totals on every add/update/delete for O(1) read performance. Integrates
into brain.find({ aggregate }) for a unified query API.
Core features:
- AggregationIndex with defineAggregate()/removeAggregate() API
- Five aggregation operations: SUM, COUNT, AVG, MIN, MAX
- GROUP BY with multiple dimensions including time windows
- Time window bucketing: hour, day, week, month, quarter, year, custom
- Materialization of results as NounType.Measurement entities
- Debounced persistence of definitions and state to storage
- Definition change detection via FNV-1a hashing with auto-rebuild
- Infinite loop prevention for materialized entities
- 'aggregation' plugin provider key for native acceleration
- Lazy initialization (created on first defineAggregate() call)
- 73 tests (unit + integration) covering all functionality
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Store data opaquely in add() and update() instead of spreading object
properties into top-level metadata. data is for semantic search (HNSW),
metadata is for structured where-filter queries (MetadataIndex).
- Fix numeric range queries in MetadataIndex — use numeric-aware comparison
instead of lexicographic string comparison for normalized values.
- Add data field to RelateParams and Relation types for relationship content.
- Add where.type → where.noun alias in metadata-only find() path.
- Rewrite README: focused ~350 lines from 791, quick start first, feature
showcase with mini-snippets, organized doc links, no version callouts.
- Add DATA_MODEL.md and QUERY_OPERATORS.md reference docs.
- Remove 10 outdated/redundant doc files consolidated into API reference.
- Improve JSDoc on Entity, Relation, AddParams, FindParams, and core methods.
- Fix tests asserting data properties appear in metadata (data model violation).
- Deprecate verb.source/target in favor of from/to (public) and sourceId/targetId (storage).
The __words__ keyword index stores 50-5000 entries per entity (one per
word), which inflated avg entries/entity well above the corruption
threshold of 100. This caused:
1. validateConsistency() to falsely detect corruption on every startup,
triggering unnecessary clearAllIndexData() + rebuild() cycles
2. getStats() to log false "Metadata index may be corrupted" warnings
and report inflated totalEntries/totalIds stats
Both methods now skip __words__ when counting, so stats and health
checks reflect metadata fields only (noun, type, createdAt, etc.).
Keyword search is unaffected since the __words__ field index itself
is not modified.
Replace document-centric categories (prose/heading/code/label) with a
universal set that works across documents, code, and UI:
- title: headings, identifiers, labels, JSON keys
- annotation: comments, docstrings, captions, alt text
- content: paragraphs, list items, flowing text
- value: string literals, numbers, form values
- code: unparsed code blocks
- structural: keywords, operators, punctuation
Built-in extractors now produce title/content/code. All 6 categories
are available for custom parsers (e.g. tree-sitter).
Also adds inline code detection in Markdown: backtick spans within
prose lines are split into separate code/content segments.
Fix highlight() hanging on structured text input by addressing 3 root causes:
1. embedBatch() now uses native WASM batch API (single forward pass instead
of N individual embed() calls via Promise.all)
2. highlight() auto-detects content type (plain text, rich-text JSON, HTML,
Markdown) and extracts meaningful text segments. Supports TipTap, Slate.js,
Lexical, Draft.js, and Quill Delta formats. New contentType hint and
contentExtractor callback for custom parsers.
3. Semantic matching phase has 10s timeout - falls back to text-only matches
instead of hanging indefinitely.
Also fixes extractTextContent() array check: uses type-based detection
(typeof data[0] === 'number') instead of length-based (data.length > 10)
so arrays of objects are properly indexed for text search.
New types: ContentType, ContentCategory, ExtractedSegment
New fields: HighlightParams.contentType, HighlightParams.contentExtractor,
Highlight.contentCategory
- Add textMatches, textScore, semanticScore, matchSource to search results
- Add highlight() method for zero-config text + semantic highlighting
- Increase word indexing limit to 5000 (handles articles/chapters)
- Optimize findMatchingWords() with O(1) fast path for semantic-only results
- Add production safety limits (500 chunks for highlight)
- Add comprehensive tests for new features (35 tests)
- Update docs with match visibility and highlight() API
New public APIs:
- embedBatch(texts): Batch embed multiple texts efficiently
- similarity(textA, textB): Calculate semantic similarity (0-1 score)
- indexStats(): Get comprehensive index statistics with memory usage
- neighbors(entityId, options): Get graph neighbors with direction/depth/filter
- findDuplicates(options): Find semantic duplicates by embedding similarity
- cluster(options): Cluster entities by semantic similarity with centroids
All APIs:
- Added to BrainyInterface for type safety
- Documented in docs/API_REFERENCE.md and docs/api/README.md
- Include JSDoc examples and parameter descriptions
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Process mkdir operations sequentially first (sorted by path depth)
- Then process write/delete/update operations in parallel batches
- Prevents duplicate directory entities when mkdir and write for
related paths are in the same batch
- Add comprehensive tests for bulkWrite race condition scenarios
- Update API documentation for accuracy
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
VFS files store content in BlobStorage, but versioning was capturing
stale embedding text from entity.data instead of actual file content.
Changes:
- VersionManager.save() now reads fresh content via vfs.readFile()
- VersionManager.restore() writes content back via vfs.writeFile()
- Text files stored as UTF-8, binary as base64 with encoding flag
- Added comprehensive VFS versioning test suite (10 tests)
- Updated API docs with VFS file versioning example
Fixes: Workshop team bug report where all VFS file versions had
identical data despite different metadata.size values.
- Fixed imports in examples/tests/ to use correct Brainy import
- Fixed imports in tests/benchmarks/ to use correct paths
- Updated bin/brainy-interactive.js to use Brainy instead of BrainyData
- Corrected documentation references throughout codebase
- Removed duplicate imports in benchmark files
- All files now consistently use 'Brainy' class from dist/index.js
- Add @deprecated JSDoc tags to TypeScript definitions
- Update all documentation examples to use modern add() and relate() API
- Preserve batch operations (addNouns, addVerbs) as they remain current
- Mark deprecated methods in both source and compiled definitions
Migration guide:
- addNoun(data, type, metadata) → add(data, { nounType: type, ...metadata })
- addVerb(source, target, type, metadata) → relate(source, target, type, metadata)
Major enhancements for type safety and developer experience:
- Add BrainyTypes static API for type management and AI-powered suggestions
- Implement strict type validation for all 31 NounType categories
- Remove dangerous generic add() method that bypassed type safety
- Add intelligent type inference with confidence scoring
- Provide helpful error messages with typo suggestions using Levenshtein distance
- Update all internal code, examples, and documentation to use typed methods
- Enhance CLI with new type management commands (types, suggest, validate)
Breaking changes:
- Remove deprecated add() method - use addNoun() with explicit type parameter
- All addNoun() calls now require explicit type as second parameter
This release significantly improves type safety across the entire system while
maintaining backward compatibility for properly typed method calls.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
