feat: add intent parameter for query disambiguation

Add optional `intent` parameter that steers query expansion, reranking,
chunk selection, and snippet extraction without searching on its own.

When a query like "performance" is ambiguous (web-perf vs team health vs
fitness), intent provides background context that disambiguates results
across all pipeline stages:

- expandQuery: includes intent in LLM prompt ("Query intent: {intent}")
- rerank: prepends intent to rerank query for Qwen3-Reranker
- chunk selection: intent terms scored at 0.5x weight vs query terms
- snippet extraction: intent terms scored at 0.3x weight
- strong-signal bypass: disabled when intent provided

Available via CLI (--intent flag or intent: line in query documents),
MCP (intent field on query tool), and programmatic API.

Adapted from PR #180 (thanks @vyalamar).

docs/SYNTAX.md

@@ -8,7 +8,8 @@ QMD queries are structured documents with typed sub-queries. Each line specifies
 query          = expand_query | query_document ;
 expand_query   = text | explicit_expand ;
 explicit_expand= "expand:" text ;
-query_document = { typed_line } ;
+query_document = [ intent_line ] { typed_line } ;
+intent_line    = "intent:" text newline ;
 typed_line     = type ":" text newline ;
 type           = "lex" | "vec" | "hyde" ;
 text           = quoted_phrase | plain_text ;
@@ -101,11 +102,28 @@ error handling best practices
 
 Both forms call the local query expansion model, which generates lex, vec, and hyde variations automatically.
 
+## Intent
+
+An optional `intent:` line provides background context to disambiguate ambiguous queries. It steers query expansion, reranking, and snippet extraction but does not search on its own.
+
+- At most one `intent:` line per query document
+- `intent:` cannot appear alone — at least one `lex:`, `vec:`, or `hyde:` line is required
+- Intent is also available via the `--intent` CLI flag or MCP `intent` parameter
+
+```
+intent: web page load times and Core Web Vitals
+lex: performance
+vec: how to improve performance
+```
+
+Without intent, "performance" is ambiguous (web-perf? team health? fitness?). With intent, the search pipeline preferentially selects and ranks web-performance content.
+
 ## Constraints
 
 - Top-level query must be either a standalone expand query or a multi-line document
-- Query documents allow only `lex`, `vec`, and `hyde` typed lines (no `expand:` inside)
+- Query documents allow only `lex`, `vec`, `hyde`, and `intent` typed lines (no `expand:` inside)
 - `lex` syntax (`-term`, `"phrase"`) only works in lex queries
+- At most one `intent:` line per query document; cannot appear alone
 - Empty lines are ignored
 - Leading/trailing whitespace is trimmed
 
@@ -132,6 +150,17 @@ Or structured format:
 }
 ```
 
+With intent:
+
+```json
+{
+  "searches": [
+    { "type": "lex", "query": "performance" }
+  ],
+  "intent": "web page load times and Core Web Vitals"
+}
+```
+
 ## CLI
 
 ```bash
@@ -143,4 +172,10 @@ qmd query $'lex: auth token\nvec: how does authentication work'
 
 # Structured
 qmd query $'lex: keywords\nvec: question\nhyde: hypothetical answer...'
+
+# With intent (inline)
+qmd query $'intent: web performance and latency\nlex: performance\nvec: how to improve performance'
+
+# With intent (flag)
+qmd query --intent "web performance and latency" "performance"
 ```

skills/qmd/SKILL.md

@@ -60,6 +60,21 @@ Local search engine for markdown content.
 - Lets the local LLM generate lex/vec/hyde variations
 - Do not mix `expand:` with other typed lines — it's either a standalone expand query or a full query document
 
+### Intent (Disambiguation)
+
+When a query term is ambiguous, add `intent` to steer results:
+
+```json
+{
+  "searches": [
+    { "type": "lex", "query": "performance" }
+  ],
+  "intent": "web page load times and Core Web Vitals"
+}
+```
+
+Intent affects expansion, reranking, chunk selection, and snippet extraction. It does not search on its own — it's a steering signal that disambiguates queries like "performance" (web-perf vs team health vs fitness).
+
 ### Combining Types
 
 | Goal | Approach |
@@ -68,6 +83,7 @@ Local search engine for markdown content.
 | Don't know vocabulary | Use a single-line query (implicit `expand:`) or `vec` |
 | Best recall | `lex` + `vec` |
 | Complex topic | `lex` + `vec` + `hyde` |
+| Ambiguous query | Add `intent` to any combination above |
 
 First query gets 2x weight in fusion — put your best guess first.
 
@@ -104,6 +120,7 @@ Omit to search all collections.
 qmd query "question"              # Auto-expand + rerank
 qmd query $'lex: X\nvec: Y'       # Structured
 qmd query $'expand: question'     # Explicit expand
+qmd query --json --explain "q"    # Show score traces (RRF + rerank blend)
 qmd search "keywords"             # BM25 only (no LLM)
 qmd get "#abc123"                 # By docid
 qmd multi-get "journals/2026-*.md" -l 40  # Batch pull snippets by glob

src/formatter.ts

@@ -40,6 +40,7 @@ export type FormatOptions = {
   query?: string;       // Query for snippet extraction and highlighting
   useColor?: boolean;   // Enable terminal colors (default: false for non-CLI)
   lineNumbers?: boolean;// Add line numbers to output
+  intent?: string;      // Domain intent for snippet extraction disambiguation
 };
 
 // =============================================================================
@@ -101,7 +102,7 @@ export function searchResultsToJson(
   const output = results.map(row => {
     const bodyStr = row.body || "";
     let body = opts.full ? bodyStr : undefined;
-    let snippet = !opts.full ? extractSnippet(bodyStr, query, 300, row.chunkPos).snippet : undefined;
+    let snippet = !opts.full ? extractSnippet(bodyStr, query, 300, row.chunkPos, undefined, opts.intent).snippet : undefined;
 
     if (opts.lineNumbers) {
       if (body) body = addLineNumbers(body);
@@ -132,7 +133,7 @@ export function searchResultsToCsv(
   const header = "docid,score,file,title,context,line,snippet";
   const rows = results.map(row => {
     const bodyStr = row.body || "";
-    const { line, snippet } = extractSnippet(bodyStr, query, 500, row.chunkPos);
+    const { line, snippet } = extractSnippet(bodyStr, query, 500, row.chunkPos, undefined, opts.intent);
     let content = opts.full ? bodyStr : snippet;
     if (opts.lineNumbers && content) {
       content = addLineNumbers(content);
@@ -175,7 +176,7 @@ export function searchResultsToMarkdown(
     if (opts.full) {
       content = bodyStr;
     } else {
-      content = extractSnippet(bodyStr, query, 500, row.chunkPos).snippet;
+      content = extractSnippet(bodyStr, query, 500, row.chunkPos, undefined, opts.intent).snippet;
     }
     if (opts.lineNumbers) {
       content = addLineNumbers(content);
@@ -196,7 +197,7 @@ export function searchResultsToXml(
   const items = results.map(row => {
     const titleAttr = row.title ? ` title="${escapeXml(row.title)}"` : "";
     const bodyStr = row.body || "";
-    let content = opts.full ? bodyStr : extractSnippet(bodyStr, query, 500, row.chunkPos).snippet;
+    let content = opts.full ? bodyStr : extractSnippet(bodyStr, query, 500, row.chunkPos, undefined, opts.intent).snippet;
     if (opts.lineNumbers) {
       content = addLineNumbers(content);
     }

src/llm.ts

@@ -970,7 +970,7 @@ export class LlamaCpp implements LLM {
   // High-level abstractions
   // ==========================================================================
 
-  async expandQuery(query: string, options: { context?: string, includeLexical?: boolean } = {}): Promise<Queryable[]> {
+  async expandQuery(query: string, options: { context?: string, includeLexical?: boolean, intent?: string } = {}): Promise<Queryable[]> {
     // Ping activity at start to keep models alive during this operation
     this.touchActivity();
 
@@ -989,7 +989,10 @@ export class LlamaCpp implements LLM {
       `
     });
 
-    const prompt = `/no_think Expand this search query: ${query}`;
+    const intent = options.intent;
+    const prompt = intent
+      ? `/no_think Expand this search query: ${query}\nQuery intent: ${intent}`
+      : `/no_think Expand this search query: ${query}`;
 
     // Create a bounded context for expansion to prevent large default VRAM allocations.
     const genContext = await this.generateModel!.createContext({

src/mcp.ts

@@ -126,10 +126,13 @@ function buildInstructions(store: Store): string {
   lines.push("  - type:'vec' — semantic vector search (meaning-based)");
   lines.push("  - type:'hyde' — hypothetical document (write what the answer looks like)");
   lines.push("");
+  lines.push("  Always provide `intent` on every search call to disambiguate and improve snippets.");
+  lines.push("");
   lines.push("Examples:");
   lines.push("  Quick keyword lookup: [{type:'lex', query:'error handling'}]");
   lines.push("  Semantic search: [{type:'vec', query:'how to handle errors gracefully'}]");
   lines.push("  Best results: [{type:'lex', query:'error'}, {type:'vec', query:'error handling best practices'}]");
+  lines.push("  With intent: searches=[{type:'lex', query:'performance'}], intent='web page load times'");
 
   // --- Retrieval workflow ---
   lines.push("");
@@ -312,9 +315,12 @@ Intent-aware lex (C++ performance, not sports):
           "Maximum candidates to rerank (default: 40, lower = faster but may miss results)"
         ),
         collections: z.array(z.string()).optional().describe("Filter to collections (OR match)"),
+        intent: z.string().optional().describe(
+          "Background context to disambiguate the query. Example: query='performance', intent='web page load times and Core Web Vitals'. Does not search on its own."
+        ),
       },
     },
-    async ({ searches, limit, minScore, candidateLimit, collections }) => {
+    async ({ searches, limit, minScore, candidateLimit, collections, intent }) => {
       // Map to internal format
       const subSearches: StructuredSubSearch[] = searches.map(s => ({
         type: s.type,
@@ -329,6 +335,7 @@ Intent-aware lex (C++ performance, not sports):
         limit,
         minScore,
         candidateLimit,
+        intent,
       });
 
       // Use first lex or vec query for snippet extraction
@@ -337,7 +344,7 @@ Intent-aware lex (C++ performance, not sports):
         || searches[0]?.query || "";
 
       const filtered: SearchResultItem[] = results.map(r => {
-        const { line, snippet } = extractSnippet(r.bestChunk, primaryQuery, 300);
+        const { line, snippet } = extractSnippet(r.bestChunk, primaryQuery, 300, undefined, undefined, intent);
         return {
           docid: `#${r.docid}`,
           file: r.displayPath,

src/qmd.ts

@@ -1771,6 +1771,7 @@ type OutputOptions = {
   explain?: boolean;     // Include retrieval score traces (query only)
   context?: string;      // Optional context for query expansion
   candidateLimit?: number;  // Max candidates to rerank (default: 40)
+  intent?: string;       // Domain intent for disambiguation
 };
 
 // Highlight query terms in text (skip short words < 3 chars)
@@ -1863,7 +1864,7 @@ function outputResults(results: OutputRow[], query: string, opts: OutputOptions)
     const output = filtered.map(row => {
       const docid = row.docid || (row.hash ? row.hash.slice(0, 6) : undefined);
       let body = opts.full ? row.body : undefined;
-      let snippet = !opts.full ? extractSnippet(row.body, query, 300, row.chunkPos).snippet : undefined;
+      let snippet = !opts.full ? extractSnippet(row.body, query, 300, row.chunkPos, undefined, opts.intent).snippet : undefined;
       if (opts.lineNumbers) {
         if (body) body = addLineNumbers(body);
         if (snippet) snippet = addLineNumbers(snippet);
@@ -1891,7 +1892,7 @@ function outputResults(results: OutputRow[], query: string, opts: OutputOptions)
     for (let i = 0; i < filtered.length; i++) {
       const row = filtered[i];
       if (!row) continue;
-      const { line, snippet } = extractSnippet(row.body, query, 500, row.chunkPos);
+      const { line, snippet } = extractSnippet(row.body, query, 500, row.chunkPos, undefined, opts.intent);
       const docid = row.docid || (row.hash ? row.hash.slice(0, 6) : undefined);
 
       // Line 1: filepath with docid
@@ -1954,7 +1955,7 @@ function outputResults(results: OutputRow[], query: string, opts: OutputOptions)
       if (!row) continue;
       const heading = row.title || row.displayPath;
       const docid = row.docid || (row.hash ? row.hash.slice(0, 6) : undefined);
-      let content = opts.full ? row.body : extractSnippet(row.body, query, 500, row.chunkPos).snippet;
+      let content = opts.full ? row.body : extractSnippet(row.body, query, 500, row.chunkPos, undefined, opts.intent).snippet;
       if (opts.lineNumbers) {
         content = addLineNumbers(content);
       }
@@ -1967,7 +1968,7 @@ function outputResults(results: OutputRow[], query: string, opts: OutputOptions)
       const titleAttr = row.title ? ` title="${row.title.replace(/"/g, '&quot;')}"` : "";
       const contextAttr = row.context ? ` context="${row.context.replace(/"/g, '&quot;')}"` : "";
       const docid = row.docid || (row.hash ? row.hash.slice(0, 6) : "");
-      let content = opts.full ? row.body : extractSnippet(row.body, query, 500, row.chunkPos).snippet;
+      let content = opts.full ? row.body : extractSnippet(row.body, query, 500, row.chunkPos, undefined, opts.intent).snippet;
       if (opts.lineNumbers) {
         content = addLineNumbers(content);
       }
@@ -1977,7 +1978,7 @@ function outputResults(results: OutputRow[], query: string, opts: OutputOptions)
     // CSV format
     console.log("docid,score,file,title,context,line,snippet");
     for (const row of filtered) {
-      const { line, snippet } = extractSnippet(row.body, query, 500, row.chunkPos);
+      const { line, snippet } = extractSnippet(row.body, query, 500, row.chunkPos, undefined, opts.intent);
       let content = opts.full ? row.body : snippet;
       if (opts.lineNumbers) {
         content = addLineNumbers(content, line);
@@ -2036,7 +2037,12 @@ function filterByCollections<T extends { filepath?: string; file?: string }>(res
  *   "lex: CAP\nvec: consistency"     -> [{ type: 'lex', ... }, { type: 'vec', ... }]
  *   "CAP\nconsistency"               -> throws (multiple plain lines)
  */
-function parseStructuredQuery(query: string): StructuredSubSearch[] | null {
+interface ParsedStructuredQuery {
+  searches: StructuredSubSearch[];
+  intent?: string;
+}
+
+function parseStructuredQuery(query: string): ParsedStructuredQuery | null {
   const rawLines = query.split('\n').map((line, idx) => ({
     raw: line,
     trimmed: line.trim(),
@@ -2047,7 +2053,9 @@ function parseStructuredQuery(query: string): StructuredSubSearch[] | null {
 
   const prefixRe = /^(lex|vec|hyde):\s*/i;
   const expandRe = /^expand:\s*/i;
+  const intentRe = /^intent:\s*/i;
   const typed: StructuredSubSearch[] = [];
+  let intent: string | undefined;
 
   for (const line of rawLines) {
     if (expandRe.test(line.trimmed)) {
@@ -2061,6 +2069,19 @@ function parseStructuredQuery(query: string): StructuredSubSearch[] | null {
       return null; // treat as standalone expand query
     }
 
+    // Parse intent: lines
+    if (intentRe.test(line.trimmed)) {
+      if (intent !== undefined) {
+        throw new Error(`Line ${line.number}: only one intent: line is allowed per query document.`);
+      }
+      const text = line.trimmed.replace(intentRe, '').trim();
+      if (!text) {
+        throw new Error(`Line ${line.number}: intent: must include text.`);
+      }
+      intent = text;
+      continue;
+    }
+
     const match = line.trimmed.match(prefixRe);
     if (match) {
       const type = match[1]!.toLowerCase() as 'lex' | 'vec' | 'hyde';
@@ -2080,10 +2101,15 @@ function parseStructuredQuery(query: string): StructuredSubSearch[] | null {
       return null;
     }
 
-    throw new Error(`Line ${line.number} is missing a lex:/vec:/hyde: prefix. Each line in a query document must start with one.`);
+    throw new Error(`Line ${line.number} is missing a lex:/vec:/hyde:/intent: prefix. Each line in a query document must start with one.`);
+  }
+
+  // intent: alone is not a valid query — must have at least one search
+  if (intent && typed.length === 0) {
+    throw new Error('intent: cannot appear alone. Add at least one lex:, vec:, or hyde: line.');
   }
 
-  return typed.length > 0 ? typed : null;
+  return typed.length > 0 ? { searches: typed, intent } : null;
 }
 
 function search(query: string, opts: OutputOptions): void {
@@ -2152,6 +2178,7 @@ async function vectorSearch(query: string, opts: OutputOptions, _model: string =
       collection: singleCollection,
       limit: opts.all ? 500 : (opts.limit || 10),
       minScore: opts.minScore || 0.3,
+      intent: opts.intent,
       hooks: {
         onExpand: (original, expanded) => {
           logExpansionTree(original, expanded);
@@ -2197,17 +2224,23 @@ async function querySearch(query: string, opts: OutputOptions, _embedModel: stri
 
   checkIndexHealth(store.db);
 
-  // Check for structured query syntax (lex:/vec:/hyde: prefixes)
-  const structuredQueries = parseStructuredQuery(query);
+  // Check for structured query syntax (lex:/vec:/hyde:/intent: prefixes)
+  const parsed = parseStructuredQuery(query);
+  // Intent can come from --intent flag or from intent: line in query document
+  const intent = opts.intent || parsed?.intent;
 
   await withLLMSession(async () => {
     let results;
 
-    if (structuredQueries) {
+    if (parsed) {
+      const structuredQueries = parsed.searches;
       // Structured search — user provided their own query expansions
       const typeLabels = structuredQueries.map(s => s.type).join('+');
       process.stderr.write(`${c.dim}Structured search: ${structuredQueries.length} queries (${typeLabels})${c.reset}\n`);
-      
+      if (intent) {
+        process.stderr.write(`${c.dim}├─ intent: ${intent}${c.reset}\n`);
+      }
+
       // Log each sub-query
       for (const s of structuredQueries) {
         let preview = s.query.replace(/\n/g, ' ');
@@ -2222,6 +2255,7 @@ async function querySearch(query: string, opts: OutputOptions, _embedModel: stri
         minScore: opts.minScore || 0,
         candidateLimit: opts.candidateLimit,
         explain: !!opts.explain,
+        intent,
         hooks: {
           onEmbedStart: (count) => {
             process.stderr.write(`${c.dim}Embedding ${count} ${count === 1 ? 'query' : 'queries'}...${c.reset}`);
@@ -2247,6 +2281,7 @@ async function querySearch(query: string, opts: OutputOptions, _embedModel: stri
         minScore: opts.minScore || 0,
         candidateLimit: opts.candidateLimit,
         explain: !!opts.explain,
+        intent,
         hooks: {
           onStrongSignal: (score) => {
             process.stderr.write(`${c.dim}Strong BM25 signal (${score.toFixed(2)}) — skipping expansion${c.reset}\n`);
@@ -2293,6 +2328,7 @@ async function querySearch(query: string, opts: OutputOptions, _embedModel: stri
     }
 
     // Use first lex/vec query for output context, or original query
+    const structuredQueries = parsed?.searches;
     const displayQuery = structuredQueries
       ? (structuredQueries.find(s => s.type === 'lex')?.query || structuredQueries.find(s => s.type === 'vec')?.query || query)
       : query;
@@ -2354,6 +2390,7 @@ function parseCLI() {
       "line-numbers": { type: "boolean" },  // add line numbers to output
       // Query options
       "candidate-limit": { type: "string", short: "C" },
+      intent: { type: "string" },
       // MCP HTTP transport options
       http: { type: "boolean" },
       daemon: { type: "boolean" },
@@ -2393,6 +2430,7 @@ function parseCLI() {
     lineNumbers: !!values["line-numbers"],
     candidateLimit: values["candidate-limit"] ? parseInt(String(values["candidate-limit"]), 10) : undefined,
     explain: !!values.explain,
+    intent: values.intent as string | undefined,
   };
 
   return {
@@ -2457,7 +2495,8 @@ function showHelp(): void {
     `query          = expand_query | query_document ;`,
     `expand_query   = text | explicit_expand ;`,
     `explicit_expand= "expand:" text ;`,
-    `query_document = { typed_line } ;`,
+    `query_document = [ intent_line ] { typed_line } ;`,
+    `intent_line    = "intent:" text newline ;`,
     `typed_line     = type ":" text newline ;`,
     `type           = "lex" | "vec" | "hyde" ;`,
     `text           = quoted_phrase | plain_text ;`,

src/store.ts

@@ -892,8 +892,8 @@ export function createStore(dbPath?: string): Store {
     searchVec: (query: string, model: string, limit?: number, collectionName?: string, session?: ILLMSession, precomputedEmbedding?: number[]) => searchVec(db, query, model, limit, collectionName, session, precomputedEmbedding),
 
     // Query expansion & reranking
-    expandQuery: (query: string, model?: string) => expandQuery(query, model, db),
-    rerank: (query: string, documents: { file: string; text: string }[], model?: string) => rerank(query, documents, model, db),
+    expandQuery: (query: string, model?: string, intent?: string) => expandQuery(query, model, db, intent),
+    rerank: (query: string, documents: { file: string; text: string }[], model?: string, intent?: string) => rerank(query, documents, model, db, intent),
 
     // Document retrieval
     findDocument: (filename: string, options?: { includeBody?: boolean }) => findDocument(db, filename, options),
@@ -2346,9 +2346,9 @@ export function insertEmbedding(
 // Query expansion
 // =============================================================================
 
-export async function expandQuery(query: string, model: string = DEFAULT_QUERY_MODEL, db: Database): Promise<ExpandedQuery[]> {
+export async function expandQuery(query: string, model: string = DEFAULT_QUERY_MODEL, db: Database, intent?: string): Promise<ExpandedQuery[]> {
   // Check cache first — stored as JSON preserving types
-  const cacheKey = getCacheKey("expandQuery", { query, model });
+  const cacheKey = getCacheKey("expandQuery", { query, model, ...(intent && { intent }) });
   const cached = getCachedResult(db, cacheKey);
   if (cached) {
     try {
@@ -2360,7 +2360,7 @@ export async function expandQuery(query: string, model: string = DEFAULT_QUERY_M
 
   const llm = getDefaultLlamaCpp();
   // Note: LlamaCpp uses hardcoded model, model parameter is ignored
-  const results = await llm.expandQuery(query);
+  const results = await llm.expandQuery(query, { intent });
 
   // Map Queryable[] → ExpandedQuery[] (same shape, decoupled from llm.ts internals).
   // Filter out entries that duplicate the original query text.
@@ -2379,7 +2379,10 @@ export async function expandQuery(query: string, model: string = DEFAULT_QUERY_M
 // Reranking
 // =============================================================================
 
-export async function rerank(query: string, documents: { file: string; text: string }[], model: string = DEFAULT_RERANK_MODEL, db: Database): Promise<{ file: string; score: number }[]> {
+export async function rerank(query: string, documents: { file: string; text: string }[], model: string = DEFAULT_RERANK_MODEL, db: Database, intent?: string): Promise<{ file: string; score: number }[]> {
+  // Prepend intent to rerank query so the reranker scores with domain context
+  const rerankQuery = intent ? `${intent}\n\n${query}` : query;
+
   const cachedResults: Map<string, number> = new Map();
   const uncachedDocsByChunk: Map<string, RerankDocument> = new Map();
 
@@ -2389,7 +2392,7 @@ export async function rerank(query: string, documents: { file: string; text: str
   // File path is excluded from the new cache key because the reranker score
   // depends on the chunk content, not where it came from.
   for (const doc of documents) {
-    const cacheKey = getCacheKey("rerank", { query, model, chunk: doc.text });
+    const cacheKey = getCacheKey("rerank", { query: rerankQuery, model, chunk: doc.text });
     const legacyCacheKey = getCacheKey("rerank", { query, file: doc.file, model, chunk: doc.text });
     const cached = getCachedResult(db, cacheKey) ?? getCachedResult(db, legacyCacheKey);
     if (cached !== null) {
@@ -2403,13 +2406,13 @@ export async function rerank(query: string, documents: { file: string; text: str
   if (uncachedDocsByChunk.size > 0) {
     const llm = getDefaultLlamaCpp();
     const uncachedDocs = [...uncachedDocsByChunk.values()];
-    const rerankResult = await llm.rerank(query, uncachedDocs, { model });
+    const rerankResult = await llm.rerank(rerankQuery, uncachedDocs, { model });
 
     // Cache results by chunk text so identical chunks across files are scored once.
     const textByFile = new Map(uncachedDocs.map(d => [d.file, d.text]));
     for (const result of rerankResult.results) {
       const chunk = textByFile.get(result.file) || "";
-      const cacheKey = getCacheKey("rerank", { query, model, chunk });
+      const cacheKey = getCacheKey("rerank", { query: rerankQuery, model, chunk });
       setCachedResult(db, cacheKey, result.score.toString());
       cachedResults.set(chunk, result.score);
     }
@@ -2885,7 +2888,45 @@ export type SnippetResult = {
   snippetLines: number;   // Number of lines in snippet
 };
 
-export function extractSnippet(body: string, query: string, maxLen = 500, chunkPos?: number, chunkLen?: number): SnippetResult {
+/** Weight for intent terms relative to query terms (1.0) in snippet scoring */
+export const INTENT_WEIGHT_SNIPPET = 0.3;
+
+/** Weight for intent terms relative to query terms (1.0) in chunk selection */
+export const INTENT_WEIGHT_CHUNK = 0.5;
+
+// Common stop words filtered from intent strings before tokenization.
+// Seeded from finetune/reward.py KEY_TERM_STOPWORDS, extended with common
+// 2-3 char function words so the length threshold can drop to >1 and let
+// short domain terms (API, SQL, LLM, CPU, CDN, …) survive.
+const INTENT_STOP_WORDS = new Set([
+  // 2-char function words
+  "am", "an", "as", "at", "be", "by", "do", "he", "if",
+  "in", "is", "it", "me", "my", "no", "of", "on", "or", "so",
+  "to", "up", "us", "we",
+  // 3-char function words
+  "all", "and", "any", "are", "but", "can", "did", "for", "get",
+  "has", "her", "him", "his", "how", "its", "let", "may", "not",
+  "our", "out", "the", "too", "was", "who", "why", "you",
+  // 4+ char common words
+  "also", "does", "find", "from", "have", "into", "more", "need",
+  "show", "some", "tell", "that", "them", "this", "want", "what",
+  "when", "will", "with", "your",
+  // Search-context noise
+  "about", "looking", "notes", "search", "where", "which",
+]);
+
+/**
+ * Extract meaningful terms from an intent string, filtering stop words and punctuation.
+ * Uses Unicode-aware punctuation stripping so domain terms like "API" survive.
+ * Returns lowercase terms suitable for text matching.
+ */
+export function extractIntentTerms(intent: string): string[] {
+  return intent.toLowerCase().split(/\s+/)
+    .map(t => t.replace(/^[^\p{L}\p{N}]+|[^\p{L}\p{N}]+$/gu, ""))
+    .filter(t => t.length > 1 && !INTENT_STOP_WORDS.has(t));
+}
+
+export function extractSnippet(body: string, query: string, maxLen = 500, chunkPos?: number, chunkLen?: number, intent?: string): SnippetResult {
   const totalLines = body.split('\n').length;
   let searchBody = body;
   let lineOffset = 0;
@@ -2904,13 +2945,17 @@ export function extractSnippet(body: string, query: string, maxLen = 500, chunkP
 
   const lines = searchBody.split('\n');
   const queryTerms = query.toLowerCase().split(/\s+/).filter(t => t.length > 0);
+  const intentTerms = intent ? extractIntentTerms(intent) : [];
   let bestLine = 0, bestScore = -1;
 
   for (let i = 0; i < lines.length; i++) {
     const lineLower = (lines[i] ?? "").toLowerCase();
     let score = 0;
     for (const term of queryTerms) {
-      if (lineLower.includes(term)) score++;
+      if (lineLower.includes(term)) score += 1.0;
+    }
+    for (const term of intentTerms) {
+      if (lineLower.includes(term)) score += INTENT_WEIGHT_SNIPPET;
     }
     if (score > bestScore) {
       bestScore = score;
@@ -2926,7 +2971,7 @@ export function extractSnippet(body: string, query: string, maxLen = 500, chunkP
   // If we focused on a chunk window and it produced an empty/whitespace-only snippet,
   // fall back to a full-document snippet so we always show something useful.
   if (chunkPos && chunkPos > 0 && snippetText.trim().length === 0) {
-    return extractSnippet(body, query, maxLen, undefined);
+    return extractSnippet(body, query, maxLen, undefined, undefined, intent);
   }
 
   if (snippetText.length > maxLen) snippetText = snippetText.substring(0, maxLen - 3) + "...";
@@ -2998,6 +3043,7 @@ export interface HybridQueryOptions {
   minScore?: number;        // default 0
   candidateLimit?: number;  // default RERANK_CANDIDATE_LIMIT
   explain?: boolean;        // include backend/RRF/rerank score traces
+  intent?: string;          // domain intent hint for disambiguation
   hooks?: SearchHooks;
 }
 
@@ -3043,6 +3089,7 @@ export async function hybridQuery(
   const candidateLimit = options?.candidateLimit ?? RERANK_CANDIDATE_LIMIT;
   const collection = options?.collection;
   const explain = options?.explain ?? false;
+  const intent = options?.intent;
   const hooks = options?.hooks;
 
   const rankedLists: RankedResult[][] = [];
@@ -3053,11 +3100,14 @@ export async function hybridQuery(
   ).get();
 
   // Step 1: BM25 probe — strong signal skips expensive LLM expansion
+  // When intent is provided, disable strong-signal bypass — the obvious BM25
+  // match may not be what the caller wants (e.g. "performance" with intent
+  // "web page load times" should NOT shortcut to a sports-performance doc).
   // Pass collection directly into FTS query (filter at SQL level, not post-hoc)
   const initialFts = store.searchFTS(query, 20, collection);
   const topScore = initialFts[0]?.score ?? 0;
   const secondScore = initialFts[1]?.score ?? 0;
-  const hasStrongSignal = initialFts.length > 0
+  const hasStrongSignal = !intent && initialFts.length > 0
     && topScore >= STRONG_SIGNAL_MIN_SCORE
     && (topScore - secondScore) >= STRONG_SIGNAL_MIN_GAP;
 
@@ -3068,7 +3118,7 @@ export async function hybridQuery(
   const expandStart = Date.now();
   const expanded = hasStrongSignal
     ? []
-    : await store.expandQuery(query);
+    : await store.expandQuery(query, undefined, intent);
 
   hooks?.onExpand?.(query, expanded, Date.now() - expandStart);
 
@@ -3157,6 +3207,7 @@ export async function hybridQuery(
   // Step 5: Chunk documents, pick best chunk per doc for reranking.
   // Reranking full bodies is O(tokens) — the critical perf lesson that motivated this refactor.
   const queryTerms = query.toLowerCase().split(/\s+/).filter(t => t.length > 2);
+  const intentTerms = intent ? extractIntentTerms(intent) : [];
   const chunksToRerank: { file: string; text: string }[] = [];
   const docChunkMap = new Map<string, { chunks: { text: string; pos: number }[]; bestIdx: number }>();
 
@@ -3165,11 +3216,15 @@ export async function hybridQuery(
     if (chunks.length === 0) continue;
 
     // Pick chunk with most keyword overlap (fallback: first chunk)
+    // Intent terms contribute at INTENT_WEIGHT_CHUNK (0.5) relative to query terms (1.0)
     let bestIdx = 0;
     let bestScore = -1;
     for (let i = 0; i < chunks.length; i++) {
       const chunkLower = chunks[i]!.text.toLowerCase();
-      const score = queryTerms.reduce((acc, term) => acc + (chunkLower.includes(term) ? 1 : 0), 0);
+      let score = queryTerms.reduce((acc, term) => acc + (chunkLower.includes(term) ? 1 : 0), 0);
+      for (const term of intentTerms) {
+        if (chunkLower.includes(term)) score += INTENT_WEIGHT_CHUNK;
+      }
       if (score > bestScore) { bestScore = score; bestIdx = i; }
     }
 
@@ -3180,7 +3235,7 @@ export async function hybridQuery(
   // Step 6: Rerank chunks (NOT full bodies)
   hooks?.onRerankStart?.(chunksToRerank.length);
   const rerankStart = Date.now();
-  const reranked = await store.rerank(query, chunksToRerank);
+  const reranked = await store.rerank(query, chunksToRerank, undefined, intent);
   hooks?.onRerankDone?.(Date.now() - rerankStart);
 
   // Step 7: Blend RRF position score with reranker score
@@ -3251,6 +3306,7 @@ export interface VectorSearchOptions {
   collection?: string;
   limit?: number;           // default 10
   minScore?: number;        // default 0.3
+  intent?: string;          // domain intent hint for disambiguation
   hooks?: Pick<SearchHooks, 'onExpand'>;
 }
 
@@ -3281,6 +3337,7 @@ export async function vectorSearchQuery(
   const limit = options?.limit ?? 10;
   const minScore = options?.minScore ?? 0.3;
   const collection = options?.collection;
+  const intent = options?.intent;
 
   const hasVectors = !!store.db.prepare(
     `SELECT name FROM sqlite_master WHERE type='table' AND name='vectors_vec'`
@@ -3289,7 +3346,7 @@ export async function vectorSearchQuery(
 
   // Expand query — filter to vec/hyde only (lex queries target FTS, not vector)
   const expandStart = Date.now();
-  const allExpanded = await store.expandQuery(query);
+  const allExpanded = await store.expandQuery(query, undefined, intent);
   const vecExpanded = allExpanded.filter(q => q.type !== 'lex');
   options?.hooks?.onExpand?.(query, vecExpanded, Date.now() - expandStart);
 
@@ -3343,7 +3400,7 @@ export interface StructuredSearchOptions {
   minScore?: number;        // default 0
   candidateLimit?: number;  // default RERANK_CANDIDATE_LIMIT
   explain?: boolean;        // include backend/RRF/rerank score traces
-  /** Future: domain intent hint for routing/boosting */
+  /** Domain intent hint for disambiguation — steers reranking and chunk selection */
   intent?: string;
   hooks?: SearchHooks;
 }
@@ -3375,6 +3432,7 @@ export async function structuredSearch(
   const minScore = options?.minScore ?? 0;
   const candidateLimit = options?.candidateLimit ?? RERANK_CANDIDATE_LIMIT;
   const explain = options?.explain ?? false;
+  const intent = options?.intent;
   const hooks = options?.hooks;
 
   const collections = options?.collections;
@@ -3489,6 +3547,7 @@ export async function structuredSearch(
     || searches.find(s => s.type === 'vec')?.query
     || searches[0]?.query || "";
   const queryTerms = primaryQuery.toLowerCase().split(/\s+/).filter(t => t.length > 2);
+  const intentTerms = intent ? extractIntentTerms(intent) : [];
   const chunksToRerank: { file: string; text: string }[] = [];
   const docChunkMap = new Map<string, { chunks: { text: string; pos: number }[]; bestIdx: number }>();
 
@@ -3497,11 +3556,15 @@ export async function structuredSearch(
     if (chunks.length === 0) continue;
 
     // Pick chunk with most keyword overlap
+    // Intent terms contribute at INTENT_WEIGHT_CHUNK (0.5) relative to query terms (1.0)
     let bestIdx = 0;
     let bestScore = -1;
     for (let i = 0; i < chunks.length; i++) {
       const chunkLower = chunks[i]!.text.toLowerCase();
-      const score = queryTerms.reduce((acc, term) => acc + (chunkLower.includes(term) ? 1 : 0), 0);
+      let score = queryTerms.reduce((acc, term) => acc + (chunkLower.includes(term) ? 1 : 0), 0);
+      for (const term of intentTerms) {
+        if (chunkLower.includes(term)) score += INTENT_WEIGHT_CHUNK;
+      }
       if (score > bestScore) { bestScore = score; bestIdx = i; }
     }
 
@@ -3512,7 +3575,7 @@ export async function structuredSearch(
   // Step 5: Rerank chunks
   hooks?.onRerankStart?.(chunksToRerank.length);
   const rerankStart2 = Date.now();
-  const reranked = await store.rerank(primaryQuery, chunksToRerank);
+  const reranked = await store.rerank(primaryQuery, chunksToRerank, undefined, intent);
   hooks?.onRerankDone?.(Date.now() - rerankStart2);
 
   // Step 6: Blend RRF position score with reranker score

test/intent.test.ts

@@ -0,0 +1,513 @@
+/**
+ * intent.test.ts - Tests for the intent feature
+ *
+ * Tests cover:
+ * - extractIntentTerms: stop word filtering, punctuation, acronyms, edge cases
+ * - extractSnippet with intent: disambiguation across multiple document sections
+ * - parseStructuredQuery with intent: lines (parsing, validation, error cases)
+ * - Chunk selection scoring with intent
+ * - Strong-signal bypass when intent is present
+ * - Intent constants
+ *
+ * Run with: npx vitest run test/intent.test.ts
+ */
+
+import { describe, test, expect } from "vitest";
+import {
+  extractSnippet,
+  extractIntentTerms,
+  INTENT_WEIGHT_SNIPPET,
+  INTENT_WEIGHT_CHUNK,
+  type StructuredSubSearch,
+} from "../src/store.js";
+
+// =============================================================================
+// parseStructuredQuery — duplicated from src/qmd.ts for unit testing
+// (qmd.ts doesn't export it since it's a CLI internal)
+// =============================================================================
+
+interface ParsedStructuredQuery {
+  searches: StructuredSubSearch[];
+  intent?: string;
+}
+
+function parseStructuredQuery(query: string): ParsedStructuredQuery | null {
+  const rawLines = query.split('\n').map((line, idx) => ({
+    raw: line,
+    trimmed: line.trim(),
+    number: idx + 1,
+  })).filter(line => line.trimmed.length > 0);
+
+  if (rawLines.length === 0) return null;
+
+  const prefixRe = /^(lex|vec|hyde):\s*/i;
+  const expandRe = /^expand:\s*/i;
+  const intentRe = /^intent:\s*/i;
+  const typed: StructuredSubSearch[] = [];
+  let intent: string | undefined;
+
+  for (const line of rawLines) {
+    if (expandRe.test(line.trimmed)) {
+      if (rawLines.length > 1) {
+        throw new Error(`Line ${line.number} starts with expand:, but query documents cannot mix expand with typed lines. Submit a single expand query instead.`);
+      }
+      const text = line.trimmed.replace(expandRe, '').trim();
+      if (!text) {
+        throw new Error('expand: query must include text.');
+      }
+      return null;
+    }
+
+    if (intentRe.test(line.trimmed)) {
+      if (intent !== undefined) {
+        throw new Error(`Line ${line.number}: only one intent: line is allowed per query document.`);
+      }
+      const text = line.trimmed.replace(intentRe, '').trim();
+      if (!text) {
+        throw new Error(`Line ${line.number}: intent: must include text.`);
+      }
+      intent = text;
+      continue;
+    }
+
+    const match = line.trimmed.match(prefixRe);
+    if (match) {
+      const type = match[1]!.toLowerCase() as 'lex' | 'vec' | 'hyde';
+      const text = line.trimmed.slice(match[0].length).trim();
+      if (!text) {
+        throw new Error(`Line ${line.number} (${type}:) must include text.`);
+      }
+      if (/\r|\n/.test(text)) {
+        throw new Error(`Line ${line.number} (${type}:) contains a newline. Keep each query on a single line.`);
+      }
+      typed.push({ type, query: text, line: line.number });
+      continue;
+    }
+
+    if (rawLines.length === 1) {
+      return null;
+    }
+
+    throw new Error(`Line ${line.number} is missing a lex:/vec:/hyde:/intent: prefix. Each line in a query document must start with one.`);
+  }
+
+  if (intent && typed.length === 0) {
+    throw new Error('intent: cannot appear alone. Add at least one lex:, vec:, or hyde: line.');
+  }
+
+  return typed.length > 0 ? { searches: typed, intent } : null;
+}
+
+// =============================================================================
+// extractIntentTerms
+// =============================================================================
+
+describe("extractIntentTerms", () => {
+  test("filters stop words", () => {
+    // "looking", "for", "notes", "about" are stop words
+    expect(extractIntentTerms("looking for notes about latency optimization"))
+      .toEqual(["latency", "optimization"]);
+  });
+
+  test("filters common function words", () => {
+    // "what", "is", "the", "to", "find" are stop words; "best", "way" survive
+    expect(extractIntentTerms("what is the best way to find"))
+      .toEqual(["best", "way"]);
+  });
+
+  test("preserves domain terms", () => {
+    expect(extractIntentTerms("web performance latency page load times"))
+      .toEqual(["web", "performance", "latency", "page", "load", "times"]);
+  });
+
+  test("handles surrounding punctuation with Unicode awareness", () => {
+    expect(extractIntentTerms("personal health, fitness, and endurance"))
+      .toEqual(["personal", "health", "fitness", "endurance"]);
+  });
+
+  test("preserves internal hyphens", () => {
+    expect(extractIntentTerms("self-hosted real-time (decision-making)"))
+      .toEqual(["self-hosted", "real-time", "decision-making"]);
+  });
+
+  test("short domain terms survive (API, SQL, LLM)", () => {
+    expect(extractIntentTerms("API design for LLM agents"))
+      .toEqual(["api", "design", "llm", "agents"]);
+  });
+
+  test("returns empty for empty input", () => {
+    expect(extractIntentTerms("")).toEqual([]);
+    expect(extractIntentTerms("  ")).toEqual([]);
+  });
+
+  test("filters single-char terms", () => {
+    const terms = extractIntentTerms("a b c web");
+    expect(terms).toEqual(["web"]);
+  });
+
+  test("all stop words returns empty", () => {
+    const terms = extractIntentTerms("the and or but in on at to for of with by");
+    expect(terms).toEqual([]);
+  });
+
+  test("preserves 2-char domain terms (CI, CD, DB)", () => {
+    const terms = extractIntentTerms("SQL CI CD DB");
+    expect(terms).toContain("sql");
+    expect(terms).toContain("ci");
+    expect(terms).toContain("cd");
+    expect(terms).toContain("db");
+  });
+
+  test("lowercases all terms", () => {
+    const terms = extractIntentTerms("WebSocket HTTP REST");
+    expect(terms).toContain("websocket");
+    expect(terms).toContain("http");
+    expect(terms).toContain("rest");
+  });
+
+  test("handles C++ style punctuation", () => {
+    const terms = extractIntentTerms("C++, performance! optimization.");
+    expect(terms).toContain("performance");
+    expect(terms).toContain("optimization");
+  });
+});
+
+// =============================================================================
+// extractSnippet with intent — disambiguation
+// =============================================================================
+
+describe("extractSnippet with intent", () => {
+  // Each section contains "performance" so the query score is tied (1.0 each).
+  // Intent terms (INTENT_WEIGHT_SNIPPET) then break the tie toward the relevant section.
+  const body = [
+    "# Notes on Various Topics",
+    "",
+    "## Web Performance Section",
+    "Web performance means optimizing page load times and Core Web Vitals.",
+    "Reduce latency, improve rendering speed, and measure performance budgets.",
+    "",
+    "## Team Performance Section",
+    "Team performance depends on trust, psychological safety, and feedback.",
+    "Build culture where performance reviews drive growth not fear.",
+    "",
+    "## Health Performance Section",
+    "Health performance comes from consistent exercise, sleep, and endurance.",
+    "Track fitness metrics, optimize recovery, and monitor healthspan.",
+  ].join("\n");
+
+  test("without intent, anchors on query terms only", () => {
+    const result = extractSnippet(body, "performance", 500);
+    // "performance" appears in title and multiple sections — should anchor on first match
+    expect(result.snippet).toContain("Performance");
+  });
+
+  test("with web-perf intent, prefers web performance section", () => {
+    const result = extractSnippet(
+      body, "performance", 500,
+      undefined, undefined,
+      "Looking for notes about web performance, latency, and page load times"
+    );
+    expect(result.snippet).toMatch(/latency|page.*load|Core Web Vitals/i);
+  });
+
+  test("with health intent, prefers health section", () => {
+    const result = extractSnippet(
+      body, "performance", 500,
+      undefined, undefined,
+      "Looking for notes about personal health, fitness, and endurance"
+    );
+    expect(result.snippet).toMatch(/health|fitness|endurance|exercise/i);
+  });
+
+  test("with team intent, prefers team section", () => {
+    const result = extractSnippet(
+      body, "performance", 500,
+      undefined, undefined,
+      "Looking for notes about building high-performing teams and culture"
+    );
+    expect(result.snippet).toMatch(/team|culture|trust|feedback/i);
+  });
+
+  test("intent does not override strong query match", () => {
+    // Query "Core Web Vitals" is very specific — intent shouldn't pull away from it
+    const result = extractSnippet(
+      body, "Core Web Vitals", 500,
+      undefined, undefined,
+      "Looking for notes about health and fitness"
+    );
+    expect(result.snippet).toContain("Core Web Vitals");
+  });
+
+  test("absent intent produces same result as undefined", () => {
+    const withoutIntent = extractSnippet(body, "performance", 500);
+    const withUndefined = extractSnippet(body, "performance", 500, undefined, undefined, undefined);
+    expect(withoutIntent.line).toBe(withUndefined.line);
+    expect(withoutIntent.snippet).toBe(withUndefined.snippet);
+  });
+
+  test("intent with no matching terms falls back to query-only scoring", () => {
+    const result = extractSnippet(
+      body, "performance", 500,
+      undefined, undefined,
+      "quantum computing and entanglement"
+    );
+    expect(result.snippet).toContain("Performance");
+    expect(result.snippet.length).toBeGreaterThan(0);
+  });
+
+  test("intent works with chunk position", () => {
+    const webPerfStart = body.indexOf("## Web Performance");
+    const result = extractSnippet(
+      body, "performance", 500,
+      webPerfStart, 200,
+      "web page load times"
+    );
+    expect(result.snippet).toMatch(/Web Performance|Core Web Vitals|Page load/i);
+  });
+});
+
+// =============================================================================
+// extractSnippet — intent weight verification
+// =============================================================================
+
+describe("extractSnippet intent weight behavior", () => {
+  // Document where query term appears on every line but intent terms differ
+  const body = [
+    "performance metrics for team velocity",
+    "performance metrics for web latency",
+    "performance metrics for athletic endurance",
+  ].join("\n");
+
+  test("intent breaks tie when query matches all lines equally", () => {
+    const noIntent = extractSnippet(body, "performance metrics", 500);
+    // Without intent, first line wins (all equal score)
+    expect(noIntent.line).toBe(1);
+
+    const withIntent = extractSnippet(
+      body, "performance metrics", 500,
+      undefined, undefined,
+      "web latency and page speed"
+    );
+    // Intent terms "web", "latency" match line 2
+    expect(withIntent.snippet).toContain("web latency");
+  });
+});
+
+// =============================================================================
+// Chunk selection scoring with intent
+// =============================================================================
+
+describe("intent keyword extraction logic", () => {
+  // Mirrors the chunk selection scoring in hybridQuery, using the shared
+  // extractIntentTerms helper and INTENT_WEIGHT_CHUNK constant.
+  function scoreChunk(text: string, query: string, intent?: string): number {
+    const queryTerms = query.toLowerCase().split(/\s+/).filter(t => t.length > 2);
+    const intentTerms = intent ? extractIntentTerms(intent) : [];
+    const lower = text.toLowerCase();
+    const qScore = queryTerms.reduce((acc, term) => acc + (lower.includes(term) ? 1 : 0), 0);
+    const iScore = intentTerms.reduce((acc, term) => acc + (lower.includes(term) ? INTENT_WEIGHT_CHUNK : 0), 0);
+    return qScore + iScore;
+  }
+
+  const chunks = [
+    "Web performance: optimize page load times, reduce latency, improve rendering pipeline.",
+    "Team performance: build trust, give feedback, set clear expectations for the group.",
+    "Health performance: exercise regularly, sleep 8 hours, manage stress for endurance.",
+  ];
+
+  test("without intent, all chunks score equally on 'performance'", () => {
+    const scores = chunks.map(c => scoreChunk(c, "performance"));
+    // All contain "performance", so all score 1
+    expect(scores[0]).toBe(scores[1]);
+    expect(scores[1]).toBe(scores[2]);
+  });
+
+  test("with web intent, web chunk scores highest", () => {
+    const intent = "looking for notes about page load times and latency optimization";
+    const scores = chunks.map(c => scoreChunk(c, "performance", intent));
+    expect(scores[0]).toBeGreaterThan(scores[1]!);
+    expect(scores[0]).toBeGreaterThan(scores[2]!);
+  });
+
+  test("with health intent, health chunk scores highest", () => {
+    const intent = "looking for notes about exercise, sleep, and endurance";
+    const scores = chunks.map(c => scoreChunk(c, "performance", intent));
+    expect(scores[2]).toBeGreaterThan(scores[0]!);
+    expect(scores[2]).toBeGreaterThan(scores[1]!);
+  });
+
+  test("intent terms have lower weight than query terms (1.0)", () => {
+    const intent = "looking for latency";
+    // Chunk 0 has "performance" (query: 1.0) + "latency" (intent: INTENT_WEIGHT_CHUNK) = 1.5
+    const withBoth = scoreChunk(chunks[0]!, "performance", intent);
+    const queryOnly = scoreChunk(chunks[0]!, "performance");
+    expect(withBoth).toBe(queryOnly + INTENT_WEIGHT_CHUNK);
+  });
+
+  test("stop words are filtered, short domain terms survive", () => {
+    const intent = "the art of web performance";
+    // "the" (stop word), "art" (survives), "of" (stop word),
+    // "web" (survives), "performance" (survives)
+    // intent terms after filtering: ["art", "web", "performance"]
+    // Chunk 0 has "web" + "performance" → 2 intent hits (no "art")
+    // Chunks 1,2 have "performance" only → 1 intent hit
+    const scores = chunks.map(c => scoreChunk(c, "test", intent));
+    expect(scores[0]).toBe(INTENT_WEIGHT_CHUNK * 2); // "web" + "performance"
+    expect(scores[1]).toBe(INTENT_WEIGHT_CHUNK);      // "performance" only
+    expect(scores[2]).toBe(INTENT_WEIGHT_CHUNK);      // "performance" only
+  });
+});
+
+// =============================================================================
+// Strong-signal bypass with intent
+// =============================================================================
+
+describe("strong-signal bypass logic", () => {
+  // Mirrors the logic in hybridQuery:
+  // const hasStrongSignal = !intent && topScore >= STRONG_SIGNAL_MIN_SCORE && gap >= STRONG_SIGNAL_MIN_GAP
+  function hasStrongSignal(topScore: number, secondScore: number, intent?: string): boolean {
+    return !intent
+      && topScore >= 0.85
+      && (topScore - secondScore) >= 0.15;
+  }
+
+  test("strong signal detected without intent", () => {
+    expect(hasStrongSignal(0.90, 0.70)).toBe(true);
+  });
+
+  test("strong signal bypassed when intent provided", () => {
+    expect(hasStrongSignal(0.90, 0.70, "looking for health performance")).toBe(false);
+  });
+
+  test("weak signal not affected by intent", () => {
+    expect(hasStrongSignal(0.50, 0.45)).toBe(false);
+    expect(hasStrongSignal(0.50, 0.45, "some intent")).toBe(false);
+  });
+
+  test("close scores not strong even without intent", () => {
+    expect(hasStrongSignal(0.90, 0.80)).toBe(false); // gap < 0.15
+  });
+});
+
+// =============================================================================
+// parseStructuredQuery with intent
+// =============================================================================
+
+describe("parseStructuredQuery with intent", () => {
+  test("parses intent + lex query", () => {
+    const result = parseStructuredQuery("intent: web performance\nlex: performance");
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBe("web performance");
+    expect(result!.searches).toHaveLength(1);
+    expect(result!.searches[0]!.type).toBe("lex");
+    expect(result!.searches[0]!.query).toBe("performance");
+  });
+
+  test("parses intent + multiple typed lines", () => {
+    const result = parseStructuredQuery(
+      "intent: web page load times\nlex: performance\nvec: how to improve performance"
+    );
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBe("web page load times");
+    expect(result!.searches).toHaveLength(2);
+    expect(result!.searches[0]!.type).toBe("lex");
+    expect(result!.searches[1]!.type).toBe("vec");
+  });
+
+  test("intent can appear after typed lines", () => {
+    const result = parseStructuredQuery(
+      "lex: performance\nintent: web page load times\nvec: latency"
+    );
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBe("web page load times");
+    expect(result!.searches).toHaveLength(2);
+  });
+
+  test("intent is case-insensitive prefix", () => {
+    const result = parseStructuredQuery("Intent: web perf\nlex: performance");
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBe("web perf");
+  });
+
+  test("no intent returns undefined", () => {
+    const result = parseStructuredQuery("lex: performance\nvec: speed");
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBeUndefined();
+  });
+
+  test("intent alone throws error", () => {
+    expect(() => parseStructuredQuery("intent: web performance")).toThrow(
+      /intent: cannot appear alone/
+    );
+  });
+
+  test("multiple intent lines throw error", () => {
+    expect(() =>
+      parseStructuredQuery("intent: web perf\nintent: team health\nlex: performance")
+    ).toThrow(/only one intent: line is allowed/);
+  });
+
+  test("empty intent text throws error", () => {
+    expect(() =>
+      parseStructuredQuery("intent:\nlex: performance")
+    ).toThrow(/intent: must include text/);
+  });
+
+  test("intent with whitespace-only text throws error", () => {
+    expect(() =>
+      parseStructuredQuery("intent:   \nlex: performance")
+    ).toThrow(/intent: must include text/);
+  });
+
+  test("single plain line still returns null (expand mode)", () => {
+    const result = parseStructuredQuery("how does auth work");
+    expect(result).toBeNull();
+  });
+
+  test("expand: line still returns null", () => {
+    const result = parseStructuredQuery("expand: auth stuff");
+    expect(result).toBeNull();
+  });
+
+  test("intent with expand throws error (expand can't mix)", () => {
+    expect(() =>
+      parseStructuredQuery("intent: web\nexpand: performance")
+    ).toThrow(/cannot mix expand/);
+  });
+
+  test("empty query returns null", () => {
+    expect(parseStructuredQuery("")).toBeNull();
+    expect(parseStructuredQuery("  \n  \n  ")).toBeNull();
+  });
+
+  test("intent with blank lines is fine", () => {
+    const result = parseStructuredQuery(
+      "intent: web perf\n\nlex: performance\n\nvec: speed"
+    );
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBe("web perf");
+    expect(result!.searches).toHaveLength(2);
+  });
+
+  test("intent preserves full text including colons", () => {
+    const result = parseStructuredQuery(
+      "intent: web performance: LCP, FID, CLS\nlex: performance"
+    );
+    expect(result).not.toBeNull();
+    expect(result!.intent).toBe("web performance: LCP, FID, CLS");
+  });
+});
+
+// =============================================================================
+// Constants exported
+// =============================================================================
+
+describe("intent constants", () => {
+  test("INTENT_WEIGHT_SNIPPET is 0.3", () => {
+    expect(INTENT_WEIGHT_SNIPPET).toBe(0.3);
+  });
+
+  test("INTENT_WEIGHT_CHUNK is 0.5", () => {
+    expect(INTENT_WEIGHT_CHUNK).toBe(0.5);
+  });
+});