Search Indexed Content

Search a unified knowledge base with a multi-strategy ranking pipeline. Two parallel matchers run on every query: a Porter-stemming matcher ("caching" finds "cached", "caches", "cach") and a trigram-substring matcher ("useEff" finds "useEffect"). Their ranked lists are merged via Reciprocal Rank Fusion, so a document that ranks well in both surfaces above one that wins only on a single strategy. Multi-term queries get an additional proximity-rerank pass that boosts passages where the query terms appear close together. Typos are corrected via Levenshtein distance and re-searched. Result snippets are window-extracted around the matched terms, not blindly truncated.

The knowledge base is unified: queries reach indexed content you stored (ctx_index, ctx_fetch_and_index, ctx_batch_execute output) AND auto-captured session memory written by hooks (decisions, errors, blockers, plans, user prompts, rejected approaches, tool failures, compaction guides — 26 event categories). File-backed sources carry a content hash and auto-flag staleness when the source file changes.

WHEN:

• You want to recall something that exists in storage (recently indexed content, prior session events, auto-memory) instead of re-reading raw sources

• You have multiple related questions about the same body of knowledge — batch every question into one call (the ranking pipeline runs per-query but the round-trip cost is paid once)

• You want to scope the query to one labelled source (pass source — partial match is fine)

• You want a chronological view across current session + prior sessions + persistent auto-memory (pass sort: "timeline" — the default relevance mode only ranks within the current session)

• You want to filter ranked results by content shape (pass contentType: "code" to surface implementation snippets or contentType: "prose" to surface explanations)

WHEN NOT:

• The data you want to query has never been stored in the knowledge base AND no session memory has accumulated around it — capture first (run a gather-and-index call), then come back here to query

• You have one ad-hoc question against data that is not in the knowledge base — answer it inline by running code in the sandbox tool; one round-trip instead of capture-then-query

RETURNS: Per-query ranked sections with window-extracted snippets. Use 2-4 specific technical terms per query. Common session-memory source labels: decision (user corrections / preferences), error and error-resolution (past failures + their fixes), blocker, plan, user-prompt, rejected-approach, compaction (post-compact session guide). See ctx_stats for live category counts. Each response carries a throttle counter (call #N/M in the rolling time window); results taper toward the soft cap and calls block after the hard cap. Tune via CONTEXT_MODE_SEARCH_WINDOW_MS, CONTEXT_MODE_SEARCH_MAX_RESULTS_AFTER, CONTEXT_MODE_SEARCH_BLOCK_AFTER.

EXAMPLE: ctx_search(queries: ["root cause", "proposed fix", "test coverage"], source: "issue-#683") EXAMPLE: ctx_search(queries: ["what did we decide about caching"], source: "decision", sort: "timeline") EXAMPLE: ctx_search(queries: ["useEffect cleanup pattern"], source: "react-docs", contentType: "code", limit: 5) EXAMPLE: ctx_search(queries: ["last user prompt", "active skills", "open blockers"], sort: "timeline")