duckdb-docs（鸭数据库文档）

You are helping the user find relevant DuckDB or DuckLake documentation.

Query: $@

Follow these steps in order.

Step 1 — Check DuckDB is installed

command -v duckdb

If not found, delegate to /duckdb-skills:install-duckdb and then continue.

Step 2 — Ensure required extensions are installed

duckdb :memory: -c "INSTALL httpfs; INSTALL fts;"

If this fails, report the error and stop.

Step 3 — Choose the data source and extract search terms

The query is: $@

Data source selection

There are two search indexes available:

Both indexes share the same schema:

By default, search DuckDB docs and filter to version = 'lts'. Use different versions when:

• The user explicitly asks about current/nightly features → version = 'current'
• The user asks about a blog post or wants background/motivation → version = 'blog'
• The user asks about DuckLake → search the DuckLake index with version = 'stable'
• When unsure, omit the version filter to search across all versions.

Search terms

If the input is a natural language question (e.g. "how do I find the most frequent value"), extract the key technical terms (nouns, function names, SQL keywords) to form a compact BM25 query string. Drop stop words like "how", "do", "I", "the".

If the input is already a function name or technical term (e.g. arg_max, GROUP BY ALL), use it as-is.

Use the extracted terms as SEARCH_QUERY in the next step.

Step 4 — Ensure local cache is fresh

The cache lives at $HOME/.duckdb/docs/CACHE_FILENAME (where CACHE_FILENAME is duckdb-docs.duckdb or ducklake-docs.duckdb per Step 3).

First, ensure the directory exists:

mkdir -p "$HOME/.duckdb/docs"

Then check whether the cache file exists and is fresh (≤2 days old):

CACHE_FILE="$HOME/.duckdb/docs/CACHE_FILENAME"
if [ -f "$CACHE_FILE" ]; then
    MTIME=$(stat -f %m "$CACHE_FILE" 2>/dev/null || stat -c %Y "$CACHE_FILE")
    CACHE_AGE_DAYS=$(( ( $(date +%s) - MTIME ) / 86400 ))
else
    CACHE_AGE_DAYS=999
fi
echo "Cache age: $CACHE_AGE_DAYS days"

If CACHE_AGE_DAYS ≤ 2 → skip to Step 5.

Otherwise (stale or missing) → fetch the index:

duckdb -c "
LOAD httpfs;
LOAD fts;
ATTACH 'REMOTE_URL' AS remote (READ_ONLY);
ATTACH '$HOME/.duckdb/docs/CACHE_FILENAME.tmp' AS tmp;
COPY FROM DATABASE remote TO tmp;
" && mv "$HOME/.duckdb/docs/CACHE_FILENAME.tmp" "$HOME/.duckdb/docs/CACHE_FILENAME"

Replace REMOTE_URL and CACHE_FILENAME per Step 3. If the fetch fails (network error), report the error and stop.

Step 5 — Search the docs

duckdb "$HOME/.duckdb/docs/CACHE_FILENAME" -readonly -json -c "
LOAD fts;
SELECT
    chunk_id, page_title, section, breadcrumb, url, version, text,
    fts_main_docs_chunks.match_bm25(chunk_id, 'SEARCH_QUERY') AS score
FROM docs_chunks
WHERE score IS NOT NULL
  AND version = 'VERSION'
ORDER BY score DESC
LIMIT 8;
"

Replace CACHE_FILENAME, SEARCH_QUERY, and VERSION per Step 3. Remove the AND version = 'VERSION' line if searching across all versions.

If the user's question could benefit from both DuckDB docs and blog results, run two queries (one with version = 'stable', one with version = 'blog') or omit the version filter entirely.

Step 6 — Handle errors

• Extension not installed (httpfs or fts not found): run duckdb:memory: -c "INSTALL httpfs; INSTALL fts;" and retry.
• ATTACH fails / network unreachable: inform the user that the docs index is unavailable and suggest checking their internet connection. The DuckDB index is hosted at https://duckdb.org/data/docs-search.duckdb and the DuckLake index at https://ducklake.select/data/docs-search.duckdb.
• No results (all scores NULL or empty result set): try broadening the query — drop the least specific term, or try a single-word version of the query — then retry Step 5. If still no results, tell the user no matching documentation was found and suggest visiting https://duckdb.org/docs or https://ducklake.select/docs directly.

Step 7 — Present results

For each result chunk returned (ordered by score descending), format as:

### {section} — {page_title}
{url}

{text}

---

After presenting all chunks, synthesize a concise answer to the user's original question ($@) based on the retrieved documentation. If the chunks directly answer the question, lead with the answer before showing the sources.