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structured memory for AI agent systems — pluggable SQLite or Postgres backend, LLM context bridge","maintainers":[{"name":"bmmayer","email":"bmmayer@gmail.com"}],"readme":"# latticesql\n\n**Persistent memory for AI agents.** Keeps a SQLite **or Postgres** database and a set of context files in sync — so every agent session starts with accurate state, and agent output becomes permanent data.\n\n[![npm version](https://img.shields.io/npm/v/latticesql.svg)](https://www.npmjs.com/package/latticesql)\n[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE)\n[![Node.js >=18](https://img.shields.io/badge/node-%3E%3D18-brightgreen.svg)](https://nodejs.org)\n\n**[latticeSQL.com](https://latticeSQL.com)** — docs, examples, and guides\n\n---\n\n## What it does\n\nEvery AI agent session starts cold — no memory of what happened yesterday, what state the system is in, or what other agents have done. Lattice solves this with a minimal, generic engine that:\n\n1. **Renders** DB rows into agent-readable text files (Markdown, JSON, or any format you define)\n2. **Watches** for DB changes and re-renders automatically\n3. **Ingests** agent-written output back into the DB via the writeback pipeline\n4. **Manages** state with full CRUD, natural-key operations, seeding, and soft-delete\n5. **Optimizes** context with token budgets, relevance filtering, enrichment pipelines, and reward-scored memory\n6. **Searches** full-text (FTS5 / `tsvector`, with a LIKE fallback), semantically (bring-your-own embeddings, chunked + indexed), **hybrid** (Reciprocal Rank Fusion), and **graph-augmented** — with retrieval **eval metrics**, a health **`doctor`**, and a reproducible **benchmark** (see [docs/retrieval.md](docs/retrieval.md))\n7. **Organizes** everything into `.lattice` workspaces with a local browser GUI, a workspace dashboard, changelog/version history, and a SQL↔markdown context bridge that auto-renders on every write\n\nLattice has no opinions about your schema, your agents, or your file format. You define the tables. You control the rendering. Lattice runs the sync loop.\n\n**New in 4.2 (additive — every 4.1 caller runs unchanged):** **import structured\ndata by dropping a file into the assistant.** The **structured-source importer**\nturns a JSON or `.xlsx` source into a schema (entities / dimensions / junctions)\nand materializes it: Excel sheets become records (header + data-region detection),\n**Word/PowerPoint tables are extracted row-for-row** (a document of tabular data\nimports every row, not a lossy sample), per-slice tabs become read-only **views**\n(no duplicated rows), an **as-of date**\nis detected (contents → name → Excel preamble → Claude fallback, or per-row from a\ndate column) so re-importing a newer period keeps a **point-in-time snapshot**\nbeside the prior one, and a re-upload is fingerprinted + matched to existing tables\n(new snapshot, not duplicate tables). It's reachable only by dropping a file in the\nassistant rail, and a **brand-new dataset imports silently** — every base table +\nrow, plus any detected computed views, applied directly with a compact live-progress\ncard and no confirm gate; only genuinely uncertain choices interrupt (marginal links\nbecome questions in the assistant panel, and re-importing a **known** dataset with no\ndetectable date asks which snapshot to file it under). Applied via\n`POST /api/import/apply`; the freshly-imported model is auto-tidied by the data-model\nplanner. New exports: `inferSchema`,\n`inferFieldType`, `normalizeName`, `sourceRecords`, `materializeImport`,\n`detectAsOf`, `detectAsOfCandidates`, `detectAsOfColumns`, `parseCellDate`,\n`matchSchemaToExisting`, `renameEntities`, `excelToRecords`,\n`dedupeAndDetectViews` (+ types). See **[docs/importing.md](docs/importing.md)**.\n4.2 also tightens correctness and the read/egress posture: **retrieval bounding**\n(`/api/history` clamps its `limit`; semantic search clamps `topK` before the\ncandidate fan-out; the no-index embedding scan takes an opt-in `maxScanChunks`\nthat fails loudly with `EmbeddingScanTooLargeError` rather than silently truncate\n— off by default), an **import file-size cap enforced on BOTH the upload and the\napply-time read** (50 MB), a **genuinely failable retrieval-quality gate**\n(cross-topic golden corpus + a generated sub-perfect committed baseline +\n`npm run eval:gate` in CI; the benchmark now asserts a real pgvector index before\ntiming the vector phase; an advisory `npm run slo:gate`), **per-recipient scoping\nof realtime delete events** (a deleted row's pk/existence is no longer fanned out\nto members who couldn't read it), **symmetric many-to-many junction rendering**\n(both sides show the remote entity), and a **Windows credential-store fix** (the\ncross-process lock now retries transient `EPERM`/`EACCES`). All opt-in; absent the\nopt-in, behavior is byte-identical to 4.1.\n\n**New in 4.1 (additive — every 4.0 caller runs unchanged):** a measurable,\nproduction-grade **retrieval & data substrate**. Retrieval gets _measurable_:\n`evaluateRetrieval` reports the standard IR metrics (Precision@k / Recall@k / MRR /\nnDCG / MAP) over any ranked retriever, `lattice doctor` reports index/embedding\nhealth, and `benchmarkRetrieval` produces reproducible latency/throughput numbers.\nSearch gets _better_: **chunked + contextual embeddings** (`semanticChunker`,\n`EmbeddingsConfig.chunker`), an opt-in **indexed vector** path (`buildVectorIndex` —\npgvector HNSW / sqlite-vec, with the in-process scan as fallback), **hybrid search**\n(`hybridSearch` — Reciprocal Rank Fusion of vector + full-text) with **ranking\nsignals** + an optional **reranker**, and **graph-augmented retrieval** (a typed-edge\ngraph with bounded BFS + `graphSearch` adjacency boosting). The query surface grows:\n**bounded reads** (`maxRows` / `defaultMaxRows` → `BoundedReadError`), **projection**,\n**OR/AND + `jsonPath` filters**, **SQL-side `aggregate`**, **keyset `queryPage`**,\n**`distinctOn`**, and batched relation **`include`**. Plus governance (**immutable\nprovenance** + a **trust/verification** workflow), reliability (**`withRetry`** +\n**online resumable migrations**), **computed columns / materialized rollups**, and\nseamless **keyless cloud file-byte access** (an in-database SigV4 presigner). All\nopt-in per table/call; absent the opt-in, behavior is byte-identical to 4.0.\n\n**New in 5.1 (additive — every 5.0 caller runs unchanged).** A **deterministic data-model planner**: after an ingest or a source connect (and on workspace open), a rules engine profiles the model through bounded, dialect-stable reads and **auto-applies the reversible fix of relating tables** when a column's values resolve to another table's key (behind a false-positive gate), while surfacing heavier changes — extract a dimension, dedupe rows, merge near-duplicate tables, retype a column — as one-click **Apply / Dismiss** suggestions in the Data Model tab (`GET /api/data-model/plan`, `POST /api/data-model/apply`, `POST /api/data-model/dismiss`). It adds **traceable rendered context + traceable chat answers**: rendered context and chat replies carry `lattice://` links back to the exact source rows (inline trace chips / word-links that open a provenance card and can scroll-flash a specific field). **Frictionless desktop auto-update on macOS**: the app downloads, verifies (same signing identity + Gatekeeper), and swaps the whole **signed, notarized** bundle in the background with a progress bar and a one-click restart — falling back to the signed installer when the frictionless swap isn't available. Existing 5.0 configs and data are unaffected. See **[CHANGELOG.md](CHANGELOG.md)** for the full list.\n\n**New in 5.0 (major release).** 5.0 reframes the GUI around an **Analytics view** — ask a question about your data and Lattice answers, building a **dashboard** when a picture answers best (the docked assistant is **\"Ask Lattice\"**). It adds **connected external data**: link a Postgres/other database or an **MCP server** and its tables mirror in as **typed, read-only** tables grouped under the source's name; **import intelligence** (`import_spreadsheet`, faithful every-row import, multi-table Excel sheets); **computed tables** (live read-only projections); and a rebuilt **chat** that acknowledges instantly and streams the answer in the background (reload never cancels an in-flight turn). **Breaking / consumer-facing changes:** the bespoke **Jira/Trello connector exports are removed** (connectors are now MCP-based); the per-user **Anthropic API-key** assistant path is retired in favor of built-in **OAuth** plus a generic **\"Other AI Endpoint\"** provider (base URL + key + model); and the inference-aggressiveness slider is gone (a fixed high default). Existing 3.0+/4.x configs and data silently upgrade on GUI open. Under the hood, four substrate pieces also land: (1) A **native vector search substrate**: the pgvector / sqlite-vec index now **stays in sync with writes** (inserts/updates/deletes mirror incrementally; a freshness guard falls back to an exact scan rather than ever serving a stale index), **semantic + hybrid search work for scoped cloud members** confined to the rows they may see (via a `SECURITY DEFINER` path keyed on the member's own role — an exact scan with no over-fetch inference channel), and the index is **tunable + observable** (`embeddings.index = { m, efConstruction }`, query-time `efSearch`, an internal index registry, and `lattice reindex` / `lattice index status` / `lattice doctor --fix`), and can be stored at **16-bit half precision** (`embeddings.index.quantization = 'halfvec'`, pgvector ≥ 0.7) to roughly halve its memory while the exact-scan fallback stays full precision. All opt-in; omit the knobs and the build/query is byte-identical to before. (2) A **live force-directed brain graph** across all three GUI graph surfaces (schema, per-object, and folder) — a dependency-free physics engine + live SVG renderer with drag-to-pin, zoom, neighbor highlight, and fly-in growth. (3) **Auto-update is now visible on every surface** (npm, desktop, and dev builds — previously only the npm-supervised CLI surfaced the pill), a long-open desktop window notices new releases on its own, and a `--no-auto-update` / `LATTICE_NO_AUTO_UPDATE=1` switch (default on) pins the version for testing, air-gapped, and reproducible-demo runs. (4) **Data provenance + lineage.** Every object's page now traces where its data came from across three tiers — **raw** (files / connectors), **computed** (imports / artifacts), and **observation** (AI / learning-loop edits) — via `GET /api/provenance`, shown as a force-directed graph or a grouped source table, with a per-row provenance panel; an additive internal lineage substrate (`__lattice_lineage` + an audit `source` column) records source→object edges. Relatedly, the brain graph now shows **object↔object relationships only** (`files` is a source, not a node) and the sidebar groups are collapsible. See **[docs/retrieval.md](docs/retrieval.md)** and **[docs/desktop.md](docs/desktop.md)**.\n\n**New in 4.0 (major release — mostly drop-in):** a major version that decomposes the three largest internal modules and hardens the cloud path for many simultaneous users, while keeping the `Lattice` / GUI surface stable. **Existing 3.0+ configs and databases are migrated forward SILENTLY on open** — you usually need to do nothing. The breaking changes are auto-handled on open (or clearly documented): the per-field `ref:` shorthand is still parsed (and the GUI rewrites it to the explicit `relations:` block on disk); a legacy empty-string `deleted_at` is normalized to `NULL`; a legacy `files.path`-only row is backfilled into the reference model; the render manifest is v2-only and self-upgrades on first render. The one consumer-code change: the exported `MEMBER_GROUP` constant is replaced by **`memberGroupFor(db)`** (the member group role is now **per-cloud** — derived from the database/schema — so unrelated clouds on one Postgres cluster no longer share a group). Opening a cloud workspace is now **much faster** (one batched schema introspection instead of per-table round-trips; the owner-side RLS/grant convergence runs in the background since the owner is BYPASSRLS). See **[docs/MIGRATING-4.0.md](docs/MIGRATING-4.0.md)** for the (mostly no-op) migration and the manual steps for library/non-GUI consumers.\n\n**New in 3.4:** the browser GUI now **updates itself** — launched from an npm install it silently installs the latest published version and keeps checking in the background, relaunching on the same port while the open tab auto-reloads onto the new build (a git checkout / `npx` copy is left untouched); **file loopback** — editing a rendered `.md` context file on disk flows back into the database through the normal write path (changelog/versioned/undoable, live in the GUI), with a public [`reverseSyncFromFiles()`](docs/api-reference.md) for embedders; on a cloud, a member's **rendered context is now scoped to their own visibility** (rendered through their RLS connection + masking view, so their assistant only ever reads rows they may see); the assistant gains a **`get_row_context`** tool (reads a record's pre-joined rendered context in one call) and **`add_column`** (add a field to an existing table on request); and the cloud gets resilience + search fixes — the open-time converge is **per-table fault-isolated** (one un-manageable table no longer breaks the whole workspace), `migrate-to-cloud` now builds the full-text index (with a public [`rebuildFtsIndexes()`](docs/api-reference.md)), and a plaintext `postgres://` URL in a config is healed into an encrypted credential reference on open. New `GET /api/version`, `GET /api/update/status`, and `POST /api/workspaces/reload` endpoints. See [docs/workspaces.md](docs/workspaces.md), [docs/cloud.md](docs/cloud.md), and [docs/assistant.md](docs/assistant.md).\n\n**New in 2.1:** the GUI search box now asks the **assistant** (it answers using a full-text `search` tool) instead of running a plain text match; the assistant gains a **guarded, reversible `delete_entity`** (empty tables go immediately, non-empty tables ask what to do with the data first); new chat threads are named from a short AI summary; ingest failures are surfaced loudly instead of swallowed; and the activity feed, voice-note composer, upload timer, and live counts get a round of fixes. See [docs/assistant.md](docs/assistant.md).\n\n**New in 1.16:** the `.lattice` workspace model + auto-render, full-text search, sources/references, a workspace dashboard, a **multiplayer cloud-editing** experience (live share/de-share, \"last edited by\", change-flash + counts, and an offline edit queue that replays on reconnect), and a much richer **Data Model editor** in the GUI — a force-directed schema graph, bidirectional many-to-many links, and a soft-delete model where every schema change (create/rename/delete a table, column, or link) is tracked in version history and **reversible** (deletes never destroy data; revert restores it), with session-scoped undo/redo. All with no AI dependency. See [docs/workspaces.md](docs/workspaces.md) and [docs/collaboration.md](docs/collaboration.md). The AI assistant, chat, and ingest summarization are exclusive to the 2.0 line (2.0 = the 1.16 feature set plus that AI layer).\n\n---\n\n## Table of contents\n\n- [Installation](#installation)\n- [Quick start](#quick-start)\n- [The sync loop](#the-sync-loop)\n- [API reference](#api-reference)\n  - [Constructor](#constructor)\n  - [define()](#definedefine)\n  - [defineMulti()](#definemulti)\n  - [defineEntityContext()](#defineentitycontext-v05)\n  - [defineWriteback()](#definewriteback)\n  - [init() / close()](#init--close)\n  - [migrate()](#migrate-v017)\n  - [CRUD operations](#crud-operations)\n  - [Query operators](#query-operators)\n  - [Render, sync, watch, and reconcile](#render-sync-watch-and-reconcile)\n  - [Events](#events)\n  - [Raw DB access](#raw-db-access)\n  - [Context optimization](#context-optimization-v13)\n  - [Semantic search](#semantic-search-v13)\n  - [Writeback validation](#writeback-validation-v13)\n- [Template rendering](#template-rendering)\n  - [Built-in templates](#built-in-templates)\n  - [Lifecycle hooks](#lifecycle-hooks)\n  - [Field interpolation](#field-interpolation)\n- [Entity context directories (v0.5+)](#entity-context-directories-v05)\n- [SESSION.md write pattern](#sessionmd-write-pattern)\n- [YAML config (v0.4+)](#yaml-config-v04)\n  - [lattice.config.yml reference](#latticeconfigyml-reference)\n  - [Init from config](#init-from-config)\n  - [Config API](#config-api-programmatic)\n- [CLI — the whole product, no browser](#cli--the-whole-product-no-browser)\n- [CLI — lattice generate](#cli--lattice-generate)\n- [CLI — lattice gui (v1.11+)](#cli--lattice-gui-v111)\n- [Schema migrations](#schema-migrations)\n- [Security](#security)\n- [Pluggable backends (v1.6+)](#pluggable-backends-v16)\n- [Architecture](#architecture)\n- [Examples](#examples)\n- [MCP Connectors](#mcp-connectors)\n- [Staying up to date](#staying-up-to-date)\n  - [Auto-update](#auto-update-v11)\n- [Telemetry](#telemetry)\n- [Contributing](#contributing)\n- [Changelog](#changelog)\n\n---\n\n## Installation\n\n```bash\nnpm install latticesql\n```\n\nRequires **Node.js 18+**. The default backend is SQLite (`better-sqlite3`) — no external database process needed.\n\n> **Prefer a desktop app?** Download a native, double-click build of the GUI (no terminal) for macOS or Windows from [latticesql.com/install](https://latticesql.com/install) — it runs the same GUI server. See [docs/desktop.md](docs/desktop.md).\n\nTo use the Postgres backend (for Supabase, Neon, RDS, or any other Postgres-compatible database), install the optional dependency:\n\n```bash\nnpm install latticesql pg\n```\n\n> Deploying Lattice Cloud on managed Postgres (AWS RDS / RDS Proxy, Cloud SQL, Neon)? See the [managed-Postgres deployment notes](docs/cloud.md#deploying-on-managed-postgres-aws-rds--rds-proxy) — in particular, point the realtime `LISTEN` connection at a session-mode / direct endpoint, not a transaction-mode proxy.\n\nThen pass a connection string instead of a file path:\n\n```ts\nimport { Lattice } from 'latticesql';\n\nconst lattice = new Lattice('postgres://user:pass@host:5432/db');\n// rest of your setup is identical to the SQLite path\n```\n\nSee [Pluggable backends](#pluggable-backends-v16) below for full details.\n\n---\n\n## Quick start\n\n```typescript\nimport { Lattice } from 'latticesql';\n\nconst db = new Lattice('./state.db');\n\ndb.define('agents', {\n  columns: {\n    id: 'TEXT PRIMARY KEY',\n    name: 'TEXT NOT NULL',\n    persona: 'TEXT',\n    active: 'INTEGER DEFAULT 1',\n  },\n  render(rows) {\n    return rows\n      .filter((r) => r.active)\n      .map((r) => `## ${r.name}\\n\\n${r.persona ?? ''}`)\n      .join('\\n\\n---\\n\\n');\n  },\n  outputFile: 'AGENTS.md',\n});\n\nawait db.init();\n\nawait db.insert('agents', { name: 'Alpha', persona: 'You are Alpha, a research assistant.' });\nawait db.insert('agents', { name: 'Beta', persona: 'You are Beta, a code reviewer.' });\n\n// Render DB → context files\nawait db.render('./context');\n// Writes: context/AGENTS.md\n\n// Watch for changes, re-render every 5 seconds\nconst stop = await db.watch('./context', { interval: 5000 });\n\n// Later:\nstop();\ndb.close();\n```\n\n**YAML config form** (v0.4+) — declare your schema in a file instead:\n\n```typescript\nconst db = new Lattice({ config: './lattice.config.yml' });\nawait db.init();\n// Tables and render functions are wired automatically from the config\n```\n\n---\n\n## The sync loop\n\n```\nYour DB (SQLite)\n     │  Lattice reads rows → render functions → text\n     ▼\nContext files (Markdown, JSON, etc.)\n     │  LLM agents read these at session start\n     ▼\nAgent output files\n     │  Lattice writeback pipeline parses these\n     ▼\nYour DB (rows inserted/updated)\n```\n\nLattice reads your database for rendering, provides a full CRUD API for managing state, and persists agent output back to the DB via the writeback pipeline.\n\n---\n\n## API reference\n\n### Constructor\n\n```typescript\nnew Lattice(path: string, options?: LatticeOptions)\nnew Lattice(config: LatticeConfigInput, options?: LatticeOptions)\n```\n\n| Overload                                          | Description                                   |\n| ------------------------------------------------- | --------------------------------------------- |\n| `new Lattice('./app.db')`                         | Open a SQLite file at the given path          |\n| `new Lattice(':memory:')`                         | In-memory database (useful for tests)         |\n| `new Lattice({ config: './lattice.config.yml' })` | Read schema + DB path from a YAML config file |\n\n**`LatticeOptions`**\n\n```typescript\ninterface LatticeOptions {\n  wal?: boolean; // WAL journal mode (default: true — recommended for concurrent reads)\n  busyTimeout?: number; // SQLite busy_timeout in ms (default: 5000)\n  renderSkipsEmpty?: boolean; // Skip the read + write for spec-less tables on render() (default: false)\n  security?: {\n    sanitize?: boolean; // Strip control characters from string inputs (default: true)\n    auditTables?: string[]; // Tables that emit 'audit' events on write\n    fieldLimits?: Record<string, number>; // Max characters per named column\n  };\n}\n```\n\n```typescript\nconst db = new Lattice('./app.db', {\n  wal: true,\n  busyTimeout: 10_000,\n  security: {\n    sanitize: true,\n    auditTables: ['users', 'credentials'],\n    fieldLimits: { notes: 50_000, bio: 2_000 },\n  },\n});\n```\n\n---\n\n### `define()`\n\n```typescript\ndb.define(table: string, definition: TableDefinition): this\n```\n\nRegister a table. Must be called before `init()`. Returns `this` for chaining.\n\n**`TableDefinition`**\n\n```typescript\ninterface TableDefinition {\n  /** Column name → SQLite type spec */\n  columns: Record<string, string>;\n\n  /**\n   * How rows become context text.\n   * - A render function: (rows: Row[]) => string\n   * - A built-in template name: 'default-list' | 'default-table' | 'default-detail' | 'default-json'\n   * - A template spec with hooks: { template: BuiltinTemplateName, hooks?: RenderHooks }\n   * Optional (v0.17+) — omit render and outputFile for schema-only tables.\n   */\n  render?: RenderSpec;\n\n  /** Output file path, relative to the outputDir passed to render()/watch(). Optional (v0.17+). */\n  outputFile?: string;\n\n  /** Optional row filter applied before rendering */\n  filter?: (rows: Row[]) => Row[];\n\n  /**\n   * Primary key column name or [col1, col2] for composite PKs.\n   * Defaults to 'id'. When 'id' is the PK and the field is absent on insert,\n   * a UUID v4 is generated automatically.\n   * Composite PKs (v0.17+): auto-generates a PRIMARY KEY(...) constraint —\n   * no need to add it manually via tableConstraints.\n   */\n  primaryKey?: string | string[];\n\n  /** Additional SQL constraints (e.g., UNIQUE, CHECK). No longer required for composite PKs (v0.17+). */\n  tableConstraints?: string[];\n\n  /** Declared relationships used by template rendering */\n  relations?: Record<string, Relation>;\n}\n```\n\n**Basic example:**\n\n```typescript\ndb.define('tasks', {\n  columns: {\n    id: 'TEXT PRIMARY KEY',\n    title: 'TEXT NOT NULL',\n    status: 'TEXT DEFAULT \"open\"',\n    due: 'TEXT',\n  },\n  render(rows) {\n    const open = rows.filter((r) => r.status === 'open');\n    return (\n      `# Open Tasks (${open.length})\\n\\n` +\n      open.map((r) => `- [ ] ${r.title}${r.due ? ` — due ${r.due}` : ''}`).join('\\n')\n    );\n  },\n  outputFile: 'TASKS.md',\n});\n```\n\n**Custom primary key:**\n\n```typescript\ndb.define('pages', {\n  columns: {\n    slug: 'TEXT NOT NULL',\n    title: 'TEXT NOT NULL',\n    content: 'TEXT',\n  },\n  primaryKey: 'slug', // <-- tell Lattice which column is the PK\n  render: 'default-list',\n  outputFile: 'pages.md',\n});\n\n// get/update/delete now use the slug value directly\nconst page = await db.get('pages', 'about-us');\nawait db.update('pages', 'about-us', { title: 'About' });\nawait db.delete('pages', 'about-us');\n```\n\n**Schema-only table (v0.17+):**\n\nTables without `render` and `outputFile` get full schema support (columns, indexes, constraints, CRUD) but produce no output files during `render()` or `watch()`. Useful for junction tables, internal tracking tables, or any table that doesn't need a context file.\n\n```typescript\ndb.define('agent_skills', {\n  columns: {\n    agent_id: 'TEXT NOT NULL',\n    skill_id: 'TEXT NOT NULL',\n    proficiency: 'TEXT DEFAULT \"basic\"',\n  },\n  primaryKey: ['agent_id', 'skill_id'],\n  // No render, no outputFile — schema-only\n});\n```\n\n**Composite primary key:**\n\n```typescript\ndb.define('event_seats', {\n  columns: {\n    event_id: 'TEXT NOT NULL',\n    seat_no: 'INTEGER NOT NULL',\n    holder: 'TEXT',\n  },\n  primaryKey: ['event_id', 'seat_no'],\n  render: 'default-table',\n  outputFile: 'seats.md',\n});\n\n// Pass a Record for get/update/delete\nconst seat = await db.get('event_seats', { event_id: 'evt-1', seat_no: 12 });\nawait db.update('event_seats', { event_id: 'evt-1', seat_no: 12 }, { holder: 'Alice' });\nawait db.delete('event_seats', { event_id: 'evt-1', seat_no: 12 });\n```\n\n**Relationship declarations:**\n\n```typescript\ndb.define('comments', {\n  columns: {\n    id: 'TEXT PRIMARY KEY',\n    post_id: 'TEXT NOT NULL',\n    author_id: 'TEXT NOT NULL',\n    body: 'TEXT',\n  },\n  relations: {\n    post: { type: 'belongsTo', table: 'posts', foreignKey: 'post_id' },\n    author: { type: 'belongsTo', table: 'users', foreignKey: 'author_id' },\n    // hasMany: the other table holds the FK\n    likes: { type: 'hasMany', table: 'comment_likes', foreignKey: 'comment_id' },\n  },\n  render: {\n    template: 'default-detail',\n    hooks: { formatRow: '{{author.name}}: {{body}}' },\n  },\n  outputFile: 'comments.md',\n});\n```\n\n---\n\n### `defineMulti()`\n\n```typescript\ndb.defineMulti(name: string, definition: MultiTableDefinition): this\n```\n\nProduces one output file per _anchor entity_ — useful for per-agent or per-project context files.\n\n```typescript\ndb.defineMulti('agent-context', {\n  // Returns the anchor entities (one file will be created per agent)\n  keys: () => db.query('agents', { where: { active: 1 } }),\n\n  // Derive the output file path from the anchor entity\n  outputFile: (agent) => `agents/${agent.slug as string}/CONTEXT.md`,\n\n  // Extra tables to query and pass into render\n  tables: ['tasks', 'notes'],\n\n  render(agent, { tasks, notes }) {\n    const myTasks = tasks.filter((t) => t.assigned_to === agent.id);\n    const myNotes = notes.filter((n) => n.agent_id === agent.id);\n    return [\n      `# ${agent.name} — context`,\n      '',\n      '## Pending tasks',\n      myTasks.map((t) => `- ${t.title}`).join('\\n') || '_none_',\n      '',\n      '## Notes',\n      myNotes.map((n) => `- ${n.body}`).join('\\n') || '_none_',\n    ].join('\\n');\n  },\n});\n```\n\n---\n\n### `defineEntityContext()` (v0.5+)\n\n```typescript\ndb.defineEntityContext(table: string, def: EntityContextDefinition): this\n```\n\nGenerate a **parallel file-system tree** for an entity type — one subdirectory per row, one file per declared relationship, and an optional combined context file. Can be called before or after `init()`.\n\n```typescript\ndb.defineEntityContext('agents', {\n  // Derive the subdirectory name for each entity\n  slug: (row) => row.slug as string,\n\n  // Default query options for all relationship sources (v0.6+)\n  sourceDefaults: { softDelete: true },\n\n  // Global index file listing all entities\n  index: {\n    outputFile: 'agents/AGENTS.md',\n    render: (rows) => `# Agents\\n\\n${rows.map((r) => `- ${r.name as string}`).join('\\n')}`,\n  },\n\n  // Files inside each entity's directory\n  files: {\n    'AGENT.md': {\n      source: { type: 'self' }, // entity's own row\n      render: ([r]) => `# ${r.name as string}\\n\\n${(r.bio as string) ?? ''}`,\n    },\n    'TASKS.md': {\n      source: {\n        type: 'hasMany',\n        table: 'tasks',\n        foreignKey: 'agent_id',\n        orderBy: 'created_at',\n        orderDir: 'desc',\n        limit: 20,\n      },\n      render: (rows) => rows.map((r) => `- ${r.title as string}`).join('\\n'),\n      omitIfEmpty: true, // skip if no tasks\n      budget: 4000, // truncate at 4 000 chars\n    },\n    'SKILLS.md': {\n      source: {\n        type: 'manyToMany',\n        junctionTable: 'agent_skills',\n        localKey: 'agent_id',\n        remoteKey: 'skill_id',\n        remoteTable: 'skills',\n        orderBy: 'name', // softDelete inherited from sourceDefaults\n      },\n      render: (rows) => rows.map((r) => `- ${r.name as string}`).join('\\n'),\n      omitIfEmpty: true,\n    },\n  },\n\n  // Concatenate all files into one combined context file per entity\n  combined: { outputFile: 'CONTEXT.md', exclude: [] },\n\n  // Files agents may write — Lattice never deletes these during cleanup\n  protectedFiles: ['SESSION.md'],\n});\n```\n\n**On each `render()` / `reconcile()` call this produces:**\n\n```\ncontext/\n├── agents/\n│   └── AGENTS.md               ← global index\n├── agents/alpha/\n│   ├── AGENT.md\n│   ├── TASKS.md                ← omitted when empty\n│   ├── SKILLS.md               ← omitted when empty\n│   └── CONTEXT.md              ← AGENT.md + TASKS.md + SKILLS.md combined\n└── agents/beta/\n    ├── AGENT.md\n    └── CONTEXT.md\n```\n\n**Source types:**\n\n| Type                                                                           | What it queries                                                  |\n| ------------------------------------------------------------------------------ | ---------------------------------------------------------------- |\n| `{ type: 'self' }`                                                             | The entity row itself                                            |\n| `{ type: 'hasMany', table, foreignKey, ... }`                                  | Rows in `table` where `foreignKey = entityPk`                    |\n| `{ type: 'manyToMany', junctionTable, localKey, remoteKey, remoteTable, ... }` | Remote rows via a junction table                                 |\n| `{ type: 'belongsTo', table, foreignKey, ... }`                                | Single parent row via FK on this entity (`null` FK → empty)      |\n| `{ type: 'enriched', include: { ... } }`                                       | Entity row + related data attached as `_key` JSON fields (v0.7+) |\n| `{ type: 'custom', query: (row, adapter) => Row[] }`                           | Fully custom synchronous query                                   |\n\n#### Source query options (v0.6+)\n\n`hasMany`, `manyToMany`, and `belongsTo` sources accept optional query refinements:\n\n```typescript\n{\n  type: 'hasMany',\n  table: 'tasks',\n  foreignKey: 'agent_id',\n  // Query options (all optional):\n  softDelete: true,          // exclude rows where deleted_at IS NULL\n  filters: [                 // additional WHERE clauses (uses existing Filter type)\n    { col: 'status', op: 'eq', val: 'active' },\n  ],\n  orderBy: 'created_at',    // ORDER BY column\n  orderDir: 'desc',         // 'asc' (default) or 'desc'\n  limit: 20,                // LIMIT N\n}\n```\n\nThe `softDelete: true` shorthand is equivalent to `filters: [{ col: 'deleted_at', op: 'isNull' }]`.\n\n#### Junction column projection (v0.8+)\n\n`manyToMany` sources can include columns from the junction table in results:\n\n```typescript\n{\n  type: 'manyToMany',\n  junctionTable: 'agent_projects',\n  localKey: 'agent_id',\n  remoteKey: 'project_id',\n  remoteTable: 'projects',\n  junctionColumns: [\n    'source',                            // included as-is\n    { col: 'role', as: 'agent_role' },   // aliased\n  ],\n}\n// Each result row includes both remote table columns AND junction columns\n```\n\n#### Multi-column ORDER BY (v0.8+)\n\n`orderBy` accepts an array for multi-column sorting:\n\n```typescript\n{\n  type: 'hasMany',\n  table: 'events',\n  foreignKey: 'project_id',\n  orderBy: [\n    { col: 'severity' },                  // ASC by default\n    { col: 'timestamp', dir: 'desc' },    // DESC\n  ],\n  limit: 20,\n}\n```\n\nThe string form (`orderBy: 'name'`) still works for single-column sorting.\n\n#### sourceDefaults (v0.6+)\n\nSet default query options for all relationship sources in an entity context:\n\n```typescript\ndb.defineEntityContext('agents', {\n  slug: (row) => row.slug as string,\n  sourceDefaults: { softDelete: true }, // applied to all hasMany/manyToMany/belongsTo\n  files: {\n    'TASKS.md': {\n      // softDelete: true is inherited from sourceDefaults\n      source: { type: 'hasMany', table: 'tasks', foreignKey: 'agent_id', orderBy: 'created_at' },\n      render: (rows) => rows.map((r) => `- ${r.title as string}`).join('\\n'),\n    },\n  },\n});\n```\n\nPer-file source options override defaults. `custom`, `self`, and `enriched` sources are unaffected.\n\n#### Enriched source (v0.7+)\n\nStarts with the entity's own row and attaches related data as JSON string fields. Each key in `include` becomes a `_key` field containing `JSON.stringify(resolvedRows)`.\n\n```typescript\n'PROFILE.md': {\n  source: {\n    type: 'enriched',\n    include: {\n      // Declarative sub-lookups (support all query options)\n      skills:   { type: 'manyToMany', junctionTable: 'agent_skills',\n                  localKey: 'agent_id', remoteKey: 'skill_id',\n                  remoteTable: 'skills', softDelete: true },\n      projects: { type: 'hasMany', table: 'projects', foreignKey: 'org_id',\n                  softDelete: true, orderBy: 'name' },\n      // Custom sub-lookup for complex queries\n      stats:    { type: 'custom', query: (row, adapter) =>\n                    adapter.all('SELECT COUNT(*) as cnt FROM events WHERE actor_id = ?', [row.id]) },\n    },\n  },\n  render: ([row]) => {\n    const skills = JSON.parse(row._skills as string);\n    const projects = JSON.parse(row._projects as string);\n    return `# ${row.name}\\n\\nSkills: ${skills.length}\\nProjects: ${projects.length}`;\n  },\n}\n```\n\n#### Entity render templates (v0.9+)\n\n`EntityFileSpec.render` accepts declarative template objects in addition to functions. Three built-in templates:\n\n**entity-table** — heading + GFM table:\n\n```typescript\nrender: {\n  template: 'entity-table',\n  heading: 'Skills',\n  columns: [\n    { key: 'name', header: 'Name' },\n    { key: 'level', header: 'Level', format: (v) => String(v || '—') },\n  ],\n  emptyMessage: '*No skills assigned.*',\n  beforeRender: (rows) => rows.filter(r => r.active),  // optional\n}\n```\n\n**entity-profile** — heading + field-value pairs + enriched JSON sections:\n\n```typescript\nrender: {\n  template: 'entity-profile',\n  heading: (r) => r.name as string,\n  fields: [\n    { key: 'status', label: 'Status' },\n    { key: 'role', label: 'Role' },\n  ],\n  sections: [\n    { key: 'skills', heading: 'Skills', render: 'table',\n      columns: [{ key: 'name', header: 'Name' }] },\n    { key: 'projects', heading: 'Projects', render: 'list',\n      formatItem: (p) => `${p.name} (${p.status})` },\n  ],\n  frontmatter: (r) => ({ agent: r.name as string }),\n}\n```\n\n**entity-sections** — per-row sections with metadata + body:\n\n```typescript\nrender: {\n  template: 'entity-sections',\n  heading: 'Rules',\n  perRow: {\n    heading: (r) => r.title as string,\n    metadata: [\n      { key: 'scope', label: 'Scope' },\n      { key: 'category', label: 'Category' },\n    ],\n    body: (r) => r.rule_text as string,\n  },\n  emptyMessage: '*No rules defined.*',\n}\n```\n\nAll templates auto-prepend a read-only header and YAML frontmatter. Functions still work — the union type is backward compatible.\n\nSee [docs/entity-context.md](./docs/entity-context.md) for the complete guide.\n\n---\n\n### `defineWriteHook()` (v0.10+)\n\n```typescript\ndb.defineWriteHook(hook: WriteHook): this\n```\n\nRegister a post-write lifecycle hook that fires after `insert()`, `update()`, or `delete()` operations. Useful for denormalization, fan-out, computed fields, and audit logging.\n\n```typescript\ndb.defineWriteHook({\n  table: 'agents',\n  on: ['insert', 'update'],\n  watchColumns: ['team_id', 'division'], // only fire when these change\n  handler: (ctx) => {\n    // ctx.table, ctx.op, ctx.row, ctx.pk, ctx.changedColumns\n    console.log(`${ctx.op} on ${ctx.table}: ${ctx.pk}`);\n    denormalizeRelatedData(ctx.pk, ctx.row);\n  },\n});\n```\n\n**Options:**\n\n| Field          | Type                                      | Description                                    |\n| -------------- | ----------------------------------------- | ---------------------------------------------- |\n| `table`        | `string`                                  | Table to watch                                 |\n| `on`           | `Array<'insert' \\| 'update' \\| 'delete'>` | Operations that trigger the hook               |\n| `watchColumns` | `string[]` (optional)                     | Only fire on update when these columns changed |\n| `handler`      | `(ctx: WriteHookContext) => void`         | Synchronous handler                            |\n\nHook errors are caught and routed to error handlers — they never crash the caller. Multiple hooks per table are supported.\n\n---\n\n### `defineWriteback()`\n\n```typescript\ndb.defineWriteback(definition: WritebackDefinition): this\n```\n\nRegister an agent-output file for parsing and DB ingestion. Lattice tracks file offsets and handles rotation (truncation) automatically.\n\n```typescript\ndb.defineWriteback({\n  // Path or glob to agent-written output files\n  file: './context/agents/*/SESSION.md',\n\n  parse(content, fromOffset) {\n    // Parse new content since last read\n    const newContent = content.slice(fromOffset);\n    const entries = parseMarkdownItems(newContent);\n    return { entries, nextOffset: content.length };\n  },\n\n  async persist(entry, filePath) {\n    await db.insert('events', {\n      source_file: filePath,\n      ...(entry as Row),\n    });\n  },\n\n  // Optional: skip entries with the same dedupeKey seen before\n  dedupeKey: (entry) => (entry as { id: string }).id,\n});\n```\n\n---\n\n### Generic CRUD (v0.11+)\n\nMethods that work on **any table** — including tables created via raw DDL (not `define()`). Uses PRAGMA introspection to discover columns at runtime.\n\n```typescript\n// Upsert by natural key (not just UUID). Auto-handles org_id, updated_at, deleted_at.\nconst id = await db.upsertByNaturalKey(\n  'agents',\n  'name',\n  'Alice',\n  {\n    role: 'engineer',\n    status: 'active',\n  },\n  { sourceFile: 'agents.md', orgId: 'org-1' },\n);\n\n// Sparse update — only writes non-null fields.\nawait db.enrichByNaturalKey('agents', 'name', 'Alice', { title: 'Senior Engineer' });\n\n// Soft-delete records NOT in a set (reconciliation).\nconst deleted = await db.softDeleteMissing('agents', 'name', 'agents.md', ['Alice', 'Bob']);\n\n// Query helpers\nconst agents = await db.getActive('agents', 'name');\nconst count = await db.countActive('agents');\nconst alice = await db.getByNaturalKey('agents', 'name', 'Alice');\n```\n\n### Junction table helpers (v0.11+)\n\n```typescript\n// Link (INSERT OR IGNORE — idempotent)\nawait db.link('agent_skills', { agent_id: 'a1', skill_id: 's1', proficiency: 'expert' });\n\n// Link with upsert (INSERT OR REPLACE — updates existing)\nawait db.link(\n  'agent_projects',\n  { agent_id: 'a1', project_id: 'p1', role: 'lead' },\n  { upsert: true },\n);\n\n// Unlink (DELETE matching rows)\nawait db.unlink('agent_projects', { agent_id: 'a1', project_id: 'p1' });\n```\n\n### `seed()` (v0.13+)\n\n```typescript\ndb.seed(config: SeedConfig): Promise<SeedResult>\n```\n\nBulk seed records from structured data (YAML, JSON, etc.). Upserts by natural key, links to related entities via junction tables, and optionally soft-deletes removed entries.\n\n```typescript\nimport { parse } from 'yaml';\nimport { readFileSync } from 'fs';\n\nconst rules = parse(readFileSync('rules.yaml', 'utf8'));\n\nawait db.seed({\n  data: rules,\n  table: 'rules',\n  naturalKey: 'title',\n  sourceFile: 'rules.yaml',\n  orgId: 'org-1',\n  linkTo: {\n    targetAgents: {\n      junction: 'rule_agents',\n      foreignKey: 'agent_id',\n      resolveBy: 'name',\n      resolveTable: 'agents',\n    },\n  },\n  softDeleteMissing: true,\n});\n```\n\nA junction link whose target row doesn't resolve is **never silently dropped**. `SeedResult.unresolvedLinks` lists every such link (source record, field, target name, junction). Pass `onUnresolvedLink: 'throw'` to abort with a `SeedReconciliationError` instead — for pipelines that must never leave a record citing a relationship that has no link in the graph:\n\n```typescript\nconst result = await db.seed({ ...config, onUnresolvedLink: 'collect' });\nif (result.unresolvedLinks.length) {\n  // create the missing targets, then re-seed\n  console.warn('unresolved links:', result.unresolvedLinks);\n}\n```\n\n### `buildReport()` (v0.14+)\n\n```typescript\ndb.buildReport(config: ReportConfig): Promise<ReportResult>\n```\n\nDeclarative report builder — queries data within a time window, groups into sections, formats for output.\n\n```typescript\nconst report = await db.buildReport({\n  since: '8h', // or '24h', '7d', or ISO timestamp\n  sections: [\n    {\n      name: 'tasks',\n      query: { table: 'tasks', orderBy: 'created_at', orderDir: 'desc' },\n      format: 'count_and_list',\n    },\n    { name: 'events', query: { table: 'activity', groupBy: 'type' }, format: 'counts' },\n    {\n      name: 'alerts',\n      query: { table: 'activity', filters: [{ col: 'severity', op: 'lte', val: 2 }] },\n      format: 'list',\n    },\n  ],\n});\n\nfor (const section of report.sections) {\n  console.log(`${section.name}: ${section.count} items`);\n  console.log(section.formatted);\n}\n```\n\n### Writeback persistence (v0.12+)\n\n`WritebackDefinition` now accepts an optional `stateStore` for persistent offset/dedup tracking across restarts:\n\n```typescript\nimport { createSQLiteStateStore } from 'latticesql';\n\ndb.defineWriteback({\n  file: './agents/*/SESSION.md',\n  stateStore: createSQLiteStateStore(db.db), // persists offsets in SQLite\n  parse: (content, offset) => myParser(content, offset),\n  persist: async (entry, filePath) => {\n    /* ... */\n  },\n  dedupeKey: (entry) => entry.id,\n  onArchive: (filePath) => archiveFile(filePath), // lifecycle hook\n});\n```\n\nBuilt-in implementations: `InMemoryStateStore` (default), `SQLiteStateStore` (persistent).\n\n---\n\n### `init()` / `close()`\n\n```typescript\nawait db.init(options?: InitOptions): Promise<void>\ndb.close(): void\n```\n\n`init()` opens the SQLite file, runs `CREATE TABLE IF NOT EXISTS` for all defined tables, and applies any migrations. Must be called once before any CRUD or render operations.\n\n```typescript\nawait db.init({\n  migrations: [\n    { version: 1, sql: 'ALTER TABLE tasks ADD COLUMN due_date TEXT' },\n    { version: 2, sql: 'ALTER TABLE tasks ADD COLUMN priority INTEGER DEFAULT 0' },\n  ],\n});\n```\n\nMigrations are idempotent — each `version` number is applied exactly once, tracked in a `__lattice_migrations` internal table.\n\n`close()` closes the SQLite connection. Call it when the process shuts down.\n\n### `migrate()` (v0.17+)\n\n```typescript\nawait db.migrate(migrations: Migration[]): Promise<void>\n```\n\nRun migrations after `init()`. Works exactly like `init({ migrations })` but callable any time — useful when migrations are loaded dynamically or added by plugins after startup.\n\n```typescript\nawait db.init();\n\n// Later — e.g., after loading a plugin that needs new columns\nawait db.migrate([\n  { version: 'plugin-v1', sql: 'ALTER TABLE tasks ADD COLUMN tags TEXT' },\n  { version: 'plugin-v2', sql: 'CREATE INDEX IF NOT EXISTS idx_tasks_tags ON tasks (tags)' },\n]);\n```\n\n`Migration.version` accepts `number | string` — use numbers for sequential migrations, or strings for named/namespaced versions (e.g., `'plugin-v1'`). Each version is applied at most once, tracked in the same `__lattice_migrations` table used by `init()`.\n\n---\n\n### CRUD operations\n\nAll CRUD methods return Promises and are safe to `await`.\n\n#### `insert()`\n\n```typescript\nawait db.insert(table: string, row: Row): Promise<string>\n```\n\nInsert a row. Returns the primary key value (as a string). For the default `id` column, a UUID is auto-generated when absent.\n\n```typescript\nconst id = await db.insert('tasks', { title: 'Write docs', status: 'open' });\n// id → 'f47ac10b-58cc-4372-a567-0e02b2c3d479'\n\n// With a custom PK — caller must supply the value\nawait db.insert('pages', { slug: 'about', title: 'About Us' });\n\n// With explicit id\nawait db.insert('tasks', { id: 'task-001', title: 'Specific task' });\n```\n\n#### `insertReturning()` (v0.17+)\n\n```typescript\nawait db.insertReturning(table: string, row: Row): Promise<Row>\n```\n\nInsert a row and get the full row back — including the auto-generated `id`, defaults, and any other columns. Equivalent to `insert()` + `get()` in a single call.\n\n```typescript\nconst task = await db.insertReturning('tasks', { title: 'Write docs', status: 'open' });\n// task → { id: 'f47ac10b-...', title: 'Write docs', status: 'open', priority: 0, ... }\n\n// Useful when you need the generated id or default values immediately\nconst agent = await db.insertReturning('agents', { name: 'Gamma' });\nconsole.log(agent.id); // auto-generated UUID\nconsole.log(agent.active); // default value from schema\n```\n\n#### `upsert()`\n\n```typescript\nawait db.upsert(table: string, row: Row): Promise<string>\n```\n\nInsert or update a row by primary key (`ON CONFLICT DO UPDATE`). All PK columns must be present in `row`.\n\n```typescript\nawait db.upsert('tasks', { id: 'task-001', title: 'Updated title', status: 'done' });\n```\n\n#### `upsertBy()`\n\n```typescript\nawait db.upsertBy(table: string, col: string, val: unknown, row: Row): Promise<string>\n```\n\nUpsert by an arbitrary column — looks up the row by `col = val`, updates if found, inserts if not. Useful for `email`-keyed users, `slug`-keyed posts, etc.\n\n```typescript\nawait db.upsertBy('users', 'email', 'alice@example.com', { name: 'Alice' });\n```\n\n#### `update()`\n\n```typescript\nawait db.update(table: string, id: PkLookup, row: Partial<Row>): Promise<void>\n```\n\nUpdate specific columns on an existing row.\n\n```typescript\nawait db.update('tasks', 'task-001', { status: 'done' });\n\n// Composite PK\nawait db.update('event_seats', { event_id: 'e-1', seat_no: 3 }, { holder: 'Bob' });\n```\n\n#### `updateReturning()` (v0.17+)\n\n```typescript\nawait db.updateReturning(table: string, id: PkLookup, row: Partial<Row>): Promise<Row>\n```\n\nUpdate specific columns and get the full updated row back. Equivalent to `update()` + `get()` in a single call.\n\n```typescript\nconst task = await db.updateReturning('tasks', 'task-001', { status: 'done' });\n// task → { id: 'task-001', title: 'Write docs', status: 'done', priority: 3, ... }\n\n// Composite PK\nconst seat = await db.updateReturning(\n  'event_seats',\n  { event_id: 'e-1', seat_no: 3 },\n  { holder: 'Bob' },\n);\n// seat → { event_id: 'e-1', seat_no: 3, holder: 'Bob' }\n```\n\n#### `delete()`\n\n```typescript\nawait db.delete(table: string, id: PkLookup): Promise<void>\n```\n\n```typescript\nawait db.delete('tasks', 'task-001');\nawait db.delete('event_seats', { event_id: 'e-1', seat_no: 3 });\n```\n\n#### `transaction()` (v5.0+)\n\n```typescript\nawait db.transaction<T>(fn: () => Promise<T>): Promise<T>\n```\n\nRun `fn` inside a single database transaction. Every write `fn` performs through this Lattice (`insert` / `update` / `delete` and their audit + changelog writes) commits together, or rolls back together if `fn` throws. Reads inside `fn` see its own uncommitted writes (read-your-writes). The transaction is scoped to the async context of `fn`, so two concurrent callers never accidentally share one; a nested `transaction()` reuses the outer transaction. When the adapter cannot open a transaction, `fn` runs without one.\n\n```typescript\n// Move every row from one table to another as one atomic unit — either all\n// rows move, or (on any error) nothing does.\nawait db.transaction(async () => {\n  for (const row of rows) {\n    await db.insert('archive', row);\n    await db.delete('inbox', row.id);\n  }\n});\n```\n\n#### `get()`\n\n```typescript\nawait db.get(table: string, id: PkLookup): Promise<Row | null>\n```\n\nFetch a single row by PK. Returns `null` if not found.\n\n```typescript\nconst task = await db.get('tasks', 'task-001');\n// { id: 'task-001', title: 'Write docs', status: 'open' } | null\n```\n\n#### `query()`\n\n```typescript\nawait db.query(table: string, opts?: QueryOptions): Promise<Row[]>\n```\n\n```typescript\ninterface QueryOptions {\n  where?: Record<string, unknown>; // Equality shorthand\n  filters?: Filter[]; // Advanced operators (see below)\n  orderBy?: string;\n  orderDir?: 'asc' | 'desc';\n  limit?: number;\n  offset?: number;\n}\n```\n\n```typescript\n// Simple equality filter\nconst open = await db.query('tasks', { where: { status: 'open' } });\n\n// Sorted + paginated\nconst page1 = await db.query('tasks', {\n  where: { status: 'open' },\n  orderBy: 'created_at',\n  orderDir: 'desc',\n  limit: 20,\n  offset: 0,\n});\n\n// All rows\nconst all = await db.query('tasks');\n```\n\n#### `count()`\n\n```typescript\nawait db.count(table: string, opts?: CountOptions): Promise<number>\n```\n\n```typescript\nconst n = await db.count('tasks', { where: { status: 'open' } });\n```\n\n---\n\n### Query operators\n\nThe `filters` array supports operators beyond equality. `where` and `filters` are combined with `AND`.\n\n```typescript\ninterface Filter {\n  col: string;\n  op: 'eq' | 'ne' | 'gt' | 'gte' | 'lt' | 'lte' | 'like' | 'in' | 'isNull' | 'isNotNull';\n  val?: unknown; // not needed for isNull / isNotNull\n}\n```\n\n**Examples:**\n\n```typescript\n// Comparison\nconst highPriority = await db.query('tasks', {\n  filters: [{ col: 'priority', op: 'gte', val: 4 }],\n});\n\n// Pattern match\nconst search = await db.query('tasks', {\n  filters: [{ col: 'title', op: 'like', val: '%refactor%' }],\n});\n\n// IN list\nconst active = await db.query('tasks', {\n  filters: [{ col: 'status', op: 'in', val: ['open', 'in-progress'] }],\n});\n\n// NULL checks\nconst unassigned = await db.query('tasks', {\n  filters: [{ col: 'assignee_id', op: 'isNull' }],\n});\n\n// Combine where + filters (ANDed)\nconst results = await db.query('tasks', {\n  where: { project_id: 'proj-1' },\n  filters: [\n    { col: 'priority', op: 'gte', val: 3 },\n    { col: 'deleted_at', op: 'isNull' },\n  ],\n  orderBy: 'priority',\n  orderDir: 'desc',\n});\n\n// count() supports filters too\nconst n = await db.count('tasks', {\n  filters: [{ col: 'status', op: 'ne', val: 'done' }],\n});\n```\n\n---\n\n### Render, sync, watch, and reconcile\n\n#### `render()`\n\n```typescript\nawait db.render(outputDir: string): Promise<RenderResult>\n```\n\nRender all tables to text files in `outputDir`. Files are written atomically (write to temp, rename). Files whose content hasn't changed are skipped.\n\n```typescript\nconst result = await db.render('./context');\n// { filesWritten: ['context/TASKS.md'], filesSkipped: 2, durationMs: 12 }\n```\n\n#### `sync()`\n\n```typescript\nawait db.sync(outputDir: string): Promise<SyncResult>\n```\n\n`render()` + writeback pipeline in one call.\n\n```typescript\nconst result = await db.sync('./context');\n// { filesWritten: [...], filesSkipped: 0, durationMs: 18, writebackProcessed: 3 }\n```\n\n#### `watch()`\n\n```typescript\nawait db.watch(outputDir: string, opts?: WatchOptions): Promise<StopFn>\n```\n\nPoll the DB every `interval` ms and re-render when content changes.\n\n```typescript\nconst stop = await db.watch('./context', {\n  interval: 5_000, // default: 5000 ms\n  onRender: (r) => console.log('rendered', r.filesWritten.length, 'files'),\n  onError: (e) => console.error('render error:', e.message),\n});\n\n// Stop the loop later\nstop();\n```\n\n**With automatic orphan cleanup (v0.5+):**\n\n```typescript\nconst stop = await db.watch('./context', {\n  interval: 10_000,\n  cleanup: {\n    removeOrphanedDirectories: true, // delete dirs for deleted entities\n    removeOrphanedFiles: true, // delete stale relationship files\n    protectedFiles: ['SESSION.md'], // never delete these\n    dryRun: false,\n  },\n  onCleanup: (r) => {\n    if (r.directoriesRemoved.length > 0) {\n      console.log('removed orphaned dirs:', r.directoriesRemoved);\n    }\n  },\n});\n```\n\n#### `reconcile()` (v0.5+)\n\n```typescript\nawait db.reconcile(outputDir: string, options?: ReconcileOptions): Promise<ReconcileResult>\n```\n\nOne-shot reverse-sync + render + orphan cleanup. Reads the previous manifest, detects external file edits (reverse-sync), renders all tables and entity contexts (writing a new manifest), then removes orphaned directories and files.\n\n**Reverse-sync (v0.16+):** If any `EntityFileSpec` defines a `reverseSync` function, Lattice detects files modified since the last render (via SHA-256 hashes in the manifest) and sweeps those changes back into the database before re-rendering. See [docs/entity-context.md](./docs/entity-context.md#reverse-sync-v016).\n\n```typescript\nconst result = await db.reconcile('./context', {\n  removeOrphanedDirectories: true,\n  removeOrphanedFiles: true,\n  protectedFiles: ['SESSION.md'],\n  reverseSync: true, // default; set false to skip, 'dry-run' to preview\n  dryRun: false, // set true to preview without deleting\n  onOrphan: (path, kind) => console.log(`would remove ${kind}: ${path}`),\n});\n\nconsole.log(result.filesWritten); // files written this cycle\nconsole.log(result.cleanup.directoriesRemoved); // orphaned dirs removed\nconsole.log(result.cleanup.warnings); // dirs left in place (user files)\nconsole.log(result.reverseSync); // { filesScanned, filesChanged, updatesApplied, errors }\n```\n\n`ReconcileResult` extends `RenderResult` with `cleanup` and `reverseSync` fields:\n\n```typescript\ninterface ReconcileResult {\n  filesWritten: string[];\n  filesSkipped: number;\n  durationMs: number;\n  cleanup: {\n    directoriesRemoved: string[];\n    filesRemoved: string[];\n    directoriesSkipped: string[];\n    warnings: string[];\n  };\n  reverseSync: {\n    filesScanned: number;\n    filesChanged: number;\n    updatesApplied: number;\n    errors: Array<{ file: string; error: string }>;\n  } | null;\n}\n```\n\n---\n\n#### `reverseSyncFromFiles()` (v3.4+)\n\n```typescript\nawait db.reverseSyncFromFiles(outputDir: string, opts?: ReverseSyncProcessOptions): Promise<ReverseSyncResult>\n```\n\nChangelog-aware reverse-sync of on-disk rendered-file edits back into the database — the entry point the GUI file-loopback uses. Unlike `reconcile()` (raw SQL pre-render step), pass `apply` to route each update through a versioned write so a file edit is recorded exactly like a GUI edit, and `useDefault` to round-trip frontmatter + body `key: value` fields for files without a hand-written `reverseSync`. File hashes are compared against the current manifest, so a render-written file is recognized as an echo and skipped; an unparseable (free-form/custom) file is reported via `onSkip` rather than guessed at. See [docs/api-reference.md](docs/api-reference.md) and [docs/workspaces.md](docs/workspaces.md#file-loopback-34).\n\n```typescript\nconst result = await db.reverseSyncFromFiles('./context', { useDefault: true });\nconsole.log(result.filesChanged, result.updatesApplied);\n```\n\n#### `rebuildFtsIndexes()` (v3.4+)\n\n```typescript\nawait db.rebuildFtsIndexes(): Promise<void>\n```\n\n(Re)build the full-text search indexes for all `fts`-configured tables, backfilling existing rows. Called automatically by `migrate-to-cloud` so search works on a migrated cloud; use it manually to recover search if an index was omitted. Idempotent.\n\n---\n\n### Events\n\n```typescript\ndb.on('audit',     ({ table, operation, id, timestamp }) => void)\ndb.on('render',    ({ filesWritten, filesSkipped, durationMs }) => void)\ndb.on('writeback', ({ filePath, entriesProcessed }) => void)\ndb.on('error',     (err: Error) => void)\n```\n\n`audit` events fire on every insert/update/delete for tables listed in `security.auditTables`. Use them to build an audit log.\n\n```typescript\ndb.on('audit', ({ table, operation, id, timestamp }) => {\n  console.log(`[AUDIT] ${operation} on ${table}#${id} at ${timestamp}`);\n});\n```\n\n---\n\n### Raw DB access\n\n```typescript\ndb.db: Database.Database  // better-sqlite3 instance\n```\n\nEscape hatch for queries Lattice doesn't cover (JOINs, aggregates, etc.):\n\n```typescript\nconst rows = db.db\n  .prepare(\n    `\n  SELECT t.*, u.name AS assignee_name\n  FROM tasks t\n  LEFT JOIN users u ON u.id = t.assignee_id\n  WHERE t.status = ?\n`,\n  )\n  .all('open');\n```\n\n---\n\n### Context optimization (v1.3+)\n\nLattice provides several options on `TableDefinition` to optimize what gets rendered into context files.\n\n#### Token budget\n\nLimit the token count of rendered output. When content exceeds the budget, rows are pruned by priority:\n\n```typescript\ndb.define('tickets', {\n  columns: { id: 'TEXT PRIMARY KEY', title: 'TEXT', updated_at: 'TEXT' },\n  render: (rows) => rows.map((r) => `- ${r.title}`).join('\\n'),\n  outputFile: 'TICKETS.md',\n  tokenBudget: 4000, // max estimated tokens (~4 chars/token)\n  prioritizeBy: 'updated_at', // keep most recent rows when pruning\n});\n```\n\nA truncation footer is appended: `[truncated: 47 of 123 rows rendered, ~3800 tokens]`\n\n#### Relevance filtering\n\nDynamically filter rows based on a task context string:\n\n```typescript\ndb.define('knowledge', {\n  columns: { id: 'TEXT PRIMARY KEY', topic: 'TEXT', body: 'TEXT' },\n  render: (rows) => rows.map((r) => `## ${r.topic}\\n${r.body}`).join('\\n\\n'),\n  outputFile: 'KNOWLEDGE.md',\n  relevanceFilter: (row, ctx) =>\n    ctx ? String(row.body).toLowerCase().includes(ctx.toLowerCase()) : true,\n});\n\n// Set the current task context — only matching rows are rendered\ndb.setTaskContext('deployment');\nawait db.render('./context');\n```\n\n#### Enrichment pipeline\n\nTransform rows between filtering and rendering — add computed fields, cluster, summarize:\n\n```typescript\ndb.define('incidents', {\n  columns: { id: 'TEXT PRIMARY KEY', severity: 'TEXT', title: 'TEXT', created_at: 'TEXT' },\n  render: (rows) => JSON.stringify(rows, null, 2),\n  outputFile: 'incidents.json',\n  enrich: [\n    (rows) =>\n      rows.map((r) => ({\n        ...r,\n        _age_hours: Math.round((Date.now() - new Date(r.created_at as string).getTime()) / 3600000),\n      })),\n    (rows) => (rows.length > 100 ? [{ _summary: `${rows.length} incidents` }] : rows),\n  ],\n});\n```\n\n#### Reward-scored memory\n\nTrack which data is useful. High-reward rows are prioritized in rendering; low-scoring rows can be auto-pruned:\n\n```typescript\ndb.define('tips', {\n  columns: { id: 'TEXT PRIMARY KEY', tip: 'TEXT', deleted_at: 'TEXT' },\n  render: (rows) => rows.map((r) => `- ${r.tip}`).join('\\n'),\n  outputFile: 'TIPS.md',\n  rewardTracking: true, // auto-adds _reward_total, _reward_count columns\n  pruneBelow: 0.3, // soft-delete rows with reward < 0.3 (requires deleted_at column)\n});\n\nawait db.init();\nconst id = await db.insert('tips', { tip: 'Use batch inserts for bulk data' });\n\n// After the agent confirms this tip was useful:\nawait db.reward('tips', id, { relevance: 0.9, accuracy: 1.0 });\n```\n\n### Semantic search (v1.3+)\n\nEnable embedding-based search on any table. Bring your own embedding function:\n\n```typescript\ndb.define('docs', {\n  columns: { id: 'TEXT PRIMARY KEY', title: 'TEXT', body: 'TEXT' },\n  render: (rows) => rows.map((r) => `## ${r.title}\\n${r.body}`).join('\\n\\n---\\n\\n'),\n  outputFile: 'DOCS.md',\n  embeddings: {\n    fields: ['title', 'body'],\n    embed: async (text) => {\n      const res = await openai.embeddings.create({ input: text, model: 'text-embedding-3-small' });\n      return res.data[0].embedding;\n    },\n  },\n});\n\nawait db.init();\nawait db.insert('docs', { title: 'Deploy guide', body: 'How to deploy to production...' });\n\n// Search by meaning, not keywords\nconst results = await db.search('docs', 'ship to prod', { topK: 5, minScore: 0.7 });\nfor (const { row, score } of results) {\n  console.log(`${score.toFixed(2)} — ${row.title}`);\n}\n```\n\nEmbeddings are stored in a companion SQLite table and cosine similarity is computed in JS — no external vector database required.\n\n### Writeback validation (v1.3+)\n\nValidate agent-written data before persisting. Reject low-quality or hallucinated writes:\n\n```typescript\ndb.defineWriteback({\n  file: './agent-output/*.md',\n  parse: (content, offset) => ({ entries: [content.slice(offset)], nextOffset: content.length }),\n  persist: async (entry) => {\n    /* save to DB */\n  },\n  validate: async (entry) => {\n    const text = entry as string;\n    const hasRequiredFields = text.includes('## Title') && text.includes('## Body');\n    return {\n      pass: hasRequiredFields,\n      score: hasRequiredFields ? 0.9 : 0.1,\n      reason: hasRequiredFields ? undefined : 'Missing required sections',\n    };\n  },\n  rejectBelow: 0.5,\n  onReject: (entry, result) => {\n    console.warn(`Rejected write: ${result.reason} (score: ${result.score})`);\n  },\n});\n```\n\n---\n\n## Template rendering\n\n### Built-in templates\n\nPass a `BuiltinTemplateName` string as `render` to use a built-in template without writing a render function:\n\n```typescript\ndb.define('users', {\n  columns: { id: 'TEXT PRIMARY KEY', name: 'TEXT', email: 'TEXT', role: 'TEXT' },\n  render: 'default-table', // or 'default-list' | 'default-detail' | 'default-json'\n  outputFile: 'USERS.md',\n});\n```\n\n| Template         | Output                                              |\n| ---------------- | --------------------------------------------------- |\n| `default-list`   | One bullet per row: `- key: value, key: value, ...` |\n| `default-table`  | GitHub-flavoured Markdown table with a header row   |\n| `default-detail` | `## <pk>` section per row with `key: value` body    |\n| `default-json`   | `JSON.stringify(rows, null, 2)`                     |\n\nAll templates return empty string for zero rows.\n\n---\n\n### Lifecycle hooks\n\nAdd a `hooks` object to customise any built-in template:\n\n```typescript\ndb.define('tasks', {\n  columns: { id: 'TEXT PRIMARY KEY', title: 'TEXT', status: 'TEXT', priority: 'INTEGER' },\n  render: {\n    template: 'default-list',\n    hooks: {\n      // Transform or filter rows before rendering\n      beforeRender: (rows) =>\n        rows\n          .filter((r) => r.status !== 'done')\n          .sort((a, b) => (b.priority as number) - (a.priority as number)),\n\n      // Customise how each row becomes a line\n      formatRow: '{{title}} [priority {{priority}}]',\n    },\n  },\n  outputFile: 'TASKS.md',\n});\n```\n\n| Hook                 | Applies to                       | Type                               |\n| -------------------- | -------------------------------- | ---------------------------------- |\n| `beforeRender(rows)` | All templates                    | `(rows: Row[]) => Row[]`           |\n| `formatRow`          | `default-list`, `default-detail` | `((row: Row) => string) \\| string` |\n\n`formatRow` can be a function or a `{{field}}` template string. When it's a string, `belongsTo` relation fields are resolved and available as `{{relationName.field}}`.\n\n---\n\n### Field interpolation\n\nAny `formatRow` string supports `{{field}}` tokens with dot-notation for related rows:\n\n```typescript\ndb.define('users', {\n  columns: { id: 'TEXT PRIMARY KEY', name: 'TEXT', team: 'TEXT' },\n  render: 'default-list',\n  outputFile: 'USERS.md',\n});\n\ndb.define('tickets', {\n  columns: {\n    id: 'TEXT PRIMARY KEY',\n    title: 'TEXT',\n    assignee_id: 'TEXT',\n    status: 'TEXT',\n  },\n  relations: {\n    assignee: { type: 'belongsTo', table: 'users', foreignKey: 'assignee_id' },\n  },\n  render: {\n    template: 'default-list',\n    hooks: {\n      formatRow: '{{title}} → {{assignee.name}} ({{status}})',\n    },\n  },\n  outputFile: 'TICKETS.md',\n});\n// Output line: \"- Fix login → Alice (open)\"\n```\n\n**Rules:**\n\n- `{{field}}` — value of `field` in the current row\n- `{{relation.field}}` — value of `field` in the related row (resolved via `belongsTo`)\n- Unknown paths, `null`, and `undefined` all render as empty string\n- Non-string values are coerced with `String()`\n- Leading/trailing whitespace in token names is trimmed: `{{ name }}` works\n\n---\n\n## Markdown utilities (v0.6+)\n\nComposable helper functions for building render functions. Use inside `render: (rows) => ...` callbacks to reduce boilerplate.\n\n### `frontmatter(fields)`\n\nGenerate a YAML-style frontmatter block. Automatically includes `generated_at` with the current ISO timestamp.\n\n```typescript\nimport { frontmatter } from 'latticesql';\n\nconst header = frontmatter({ agent: 'Alice', skill_count: 5 });\n// ---\n// generated_at: \"2026-03-27T...\"\n// agent: \"Alice\"\n// skill_count: 5\n// ---\n```\n\n### `markdownTable(rows, columns)`\n\nGenerate a GitHub-Flavoured Markdown table from rows with explicit column configuration and optional per-cell formatters.\n\n```typescript\nimport { markdownTable } from 'latticesql';\n\nconst md = markdownTable(rows, [\n  { key: 'name', header: 'Name' },\n  { key: 'status', header: 'Status', format: (v) => String(v || '—') },\n  { key: 'name', header: 'Detail', format: (v, row) => `[view](${row.slug}/DETAIL.md)` },\n]);\n// | Name | Status | Detail |\n// | --- | --- | --- |\n// | Alice | active | [view](alice/DETAIL.md) |\n```\n\nReturns empty string for zero rows. The `format` callback receives `(cellValue, fullRow)`.\n\n### `slugify(name)`\n\nGenerate a URL-safe slug from a display name — lowercases, strips diacritics, replaces non-alphanumeric runs with hyphens.\n\n```typescript\nimport { slugify } from 'latticesql';\n\nslugify('My Agent Name'); // 'my-agent-name'\nslugify('Jose Garcia'); // 'jose-garcia'\n```\n\n### `truncate(content, maxChars, notice?)`\n\nTruncate content at a character budget. Appends a notice when truncation occurs.\n\n```typescript\nimport { truncate } from 'latticesql';\n\nconst md = truncate(longContent, 4000);\n// Appends: \"\\n\\n*[truncated — context budget exceeded]*\"\n\nconst md2 = truncate(longContent, 4000, '\\n\\n[...truncated]');\n// Custom notice\n```\n\n---\n\n## Entity context directories (v0.5+)\n\n`defineEntityContext()` is the high-level API for per-entity file generation — the pattern where each entity type gets its own directory tree, with a separate file for each relationship type.\n\n### Why use it instead of `defineMulti()`?\n\n`defineMulti()` produces one file per anchor entity but you manage queries yourself. `defineEntityContext()` declares the _structure_ — which tables to pull, how to render them, what budget to enforce — and Lattice handl","readmeFilename":"README.md"}