[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-duckdb-query":3,"mdc-kgck0n-key":32,"related-org-duckdb-query":1982,"related-repo-duckdb-query":2098},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":22,"repoUrl":23,"updatedAt":24,"license":25,"forks":26,"topics":27,"repo":28,"sourceUrl":30,"mdContent":31},"query","run SQL queries against DuckDB","Run SQL queries against the attached DuckDB database or ad-hoc against files. Accepts raw SQL or natural language questions. 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Uses DuckDB Friendly SQL idioms.\nargument-hint: \u003CSQL or question> [--file path]\nallowed-tools: Bash\n---\n\nYou are helping the user query data using DuckDB.\n\nInput: `$@`\n\nFollow these steps in order.\n\n## Step 1 — Resolve state and determine the mode\n\nLook for an existing state file in either location:\n\n```bash\nSTATE_DIR=\"\"\ntest -f .duckdb-skills\u002Fstate.sql && STATE_DIR=\".duckdb-skills\"\nPROJECT_ROOT=\"$(git rev-parse --show-toplevel 2>\u002Fdev\u002Fnull || echo \"$PWD\")\"\nPROJECT_ID=\"$(echo \"$PROJECT_ROOT\" | tr '\u002F' '-')\"\ntest -f \"$HOME\u002F.duckdb-skills\u002F$PROJECT_ID\u002Fstate.sql\" && STATE_DIR=\"$HOME\u002F.duckdb-skills\u002F$PROJECT_ID\"\n```\n\nIf found, verify the databases it references are still accessible:\n\n```bash\nduckdb -init \"$STATE_DIR\u002Fstate.sql\" -c \"SHOW DATABASES;\"\n```\n\nNow determine the mode:\n\n- **Ad-hoc mode** if: the `--file` flag is present, or the SQL references file paths\u002Fliterals (e.g. `FROM 'data.csv'`), or `STATE_DIR` is empty.\n- **Session mode** if: `STATE_DIR` is set and the input references table names, is natural language, or is SQL without file references.\n\nIf no state file exists and no file is referenced, fall back to ad-hoc mode against `:memory:` — the user must reference files directly in their SQL.\n\nIf the state file exists but any ATTACH in it fails, warn the user and fall back to ad-hoc mode.\n\n## Step 2 — Check DuckDB is installed\n\n```bash\ncommand -v duckdb\n```\n\nIf not found, delegate to `\u002Fduckdb-skills:install-duckdb` and then continue.\n\n## Step 3 — Generate SQL if needed\n\nIf the input is natural language (not valid SQL), generate SQL using the Friendly SQL reference below.\n\nIn **session mode**, first retrieve the schema to inform query generation:\n\n```bash\nduckdb -init \"$STATE_DIR\u002Fstate.sql\" -csv -c \"\nSELECT table_name FROM duckdb_tables() ORDER BY table_name;\n\"\n```\n\nThen for relevant tables:\n\n```bash\nduckdb -init \"$STATE_DIR\u002Fstate.sql\" -csv -c \"DESCRIBE \u003Ctable_name>;\"\n```\n\nUse the schema context and the Friendly SQL reference to generate the most appropriate query.\n\n## Step 4 — Estimate result size\n\nBefore executing, estimate whether the query could produce a very large result that would\nconsume excessive tokens when returned to this conversation.\n\n**Session mode** — check row counts for the tables involved:\n\n```bash\nduckdb -init \"$STATE_DIR\u002Fstate.sql\" -csv -c \"\nSELECT table_name, estimated_size, column_count\nFROM duckdb_tables()\nWHERE table_name IN ('\u003Ctable1>', '\u003Ctable2>');\n\"\n```\n\n**Ad-hoc mode** — probe the source:\n\n```bash\nduckdb :memory: -csv -c \"\nSET allowed_paths=['FILE_PATH'];\nSET enable_external_access=false;\nSET allow_persistent_secrets=false;\nSET lock_configuration=true;\nSELECT count() AS row_count FROM 'FILE_PATH';\n\"\n```\n\n**Evaluate**:\n- If the query already has a `LIMIT`, `count()`, or other aggregation that bounds the output -> safe, proceed.\n- If the source has **>1M rows** and the query has no LIMIT or aggregation -> tell the user:\n  *\"This query would return a very large result set. Displaying it here would consume a lot of tokens and increase cost. I'd recommend adding `LIMIT 1000` or an aggregation to keep the output manageable.\"*\n  Ask for confirmation before running as-is.\n- If the data size is **>10 GB** -> additionally warn:\n  *\"This table is over 10 GB — the query may take a while to complete.\"*\n  Proceed if the user confirms.\n\nSkip this step for queries that are intrinsically bounded (e.g. `DESCRIBE`, `SUMMARIZE`, aggregations, `count()`).\n\n## Step 5 — Execute the query\n\n**Ad-hoc mode** (sandboxed — only the referenced file is accessible):\n\n```bash\nduckdb :memory: -csv \u003C\u003C'SQL'\nSET allowed_paths=['FILE_PATH'];\nSET enable_external_access=false;\nSET allow_persistent_secrets=false;\nSET lock_configuration=true;\n\u003CQUERY>;\nSQL\n```\n\nReplace `FILE_PATH` with the actual file path extracted from the query or `--file` argument.\nIf multiple files are referenced, include all paths in the `allowed_paths` list.\n\n**Session mode** (user-trusted database):\n\n```bash\nduckdb -init \"$STATE_DIR\u002Fstate.sql\" -csv -c \"\u003CQUERY>\"\n```\n\nFor multi-line queries, use a heredoc with `-init`:\n\n```bash\nduckdb -init \"$STATE_DIR\u002Fstate.sql\" -csv \u003C\u003C'SQL'\n\u003CQUERY>;\nSQL\n```\n\nAlways use heredocs (`\u003C\u003C'SQL'`) for multi-line queries to avoid shell quoting issues.\n\n## Step 6 — Handle errors\n\n- **Syntax error**: show the error, suggest a corrected query, and re-run.\n- **Missing extension** (e.g. `Extension \"X\" not loaded`): delegate to `\u002Fduckdb-skills:install-duckdb \u003Cext>`, then retry.\n- **Table not found** (session mode): list available tables with `FROM duckdb_tables()` and suggest corrections.\n- **File not found** (ad-hoc mode): use `find \"$PWD\" -name \"\u003Cfilename>\" 2>\u002Fdev\u002Fnull` to locate the file and suggest the corrected path.\n- **Persistent or unclear DuckDB error**: use `\u002Fduckdb-skills:duckdb-docs \u003Cerror message or relevant keywords>` to search the documentation for guidance, then apply the fix and retry.\n\n## Step 7 — Present results\n\nShow the query output to the user. If the result has more than 100 rows, note the truncation and suggest adding `LIMIT` to the query.\n\nFor natural language questions, also provide a brief interpretation of the results.\n\n---\n\n## DuckDB Friendly SQL Reference\n\nWhen generating SQL, prefer these idiomatic DuckDB constructs:\n\n### Compact clauses\n- **FROM-first**: `FROM table WHERE x > 10` (implicit `SELECT *`)\n- **GROUP BY ALL**: auto-groups by all non-aggregate columns\n- **ORDER BY ALL**: orders by all columns for deterministic results\n- **SELECT * EXCLUDE (col1, col2)**: drop columns from wildcard\n- **SELECT * REPLACE (expr AS col)**: transform a column in-place\n- **UNION ALL BY NAME**: combine tables with different column orders\n- **Percentage LIMIT**: `LIMIT 10%` returns a percentage of rows\n- **Prefix aliases**: `SELECT x: 42` instead of `SELECT 42 AS x`\n- **Trailing commas** allowed in SELECT lists\n\n### Query features\n- **count()**: no need for `count(*)`\n- **Reusable aliases**: use column aliases in WHERE \u002F GROUP BY \u002F HAVING\n- **Lateral column aliases**: `SELECT i+1 AS j, j+2 AS k`\n- **COLUMNS(*)**: apply expressions across columns; supports regex, EXCLUDE, REPLACE, lambdas\n- **FILTER clause**: `count() FILTER (WHERE x > 10)` for conditional aggregation\n- **GROUPING SETS \u002F CUBE \u002F ROLLUP**: advanced multi-level aggregation\n- **Top-N per group**: `max(col, 3)` returns top 3 as a list; also `arg_max(arg, val, n)`, `min_by(arg, val, n)`\n- **DESCRIBE table_name**: schema summary (column names and types)\n- **SUMMARIZE table_name**: instant statistical profile\n- **PIVOT \u002F UNPIVOT**: reshape between wide and long formats\n- **SET VARIABLE x = expr**: define SQL-level variables, reference with `getvariable('x')`\n\n### Data import\n- **Direct file queries**: `FROM 'file.csv'`, `FROM 'data.parquet'`\n- **Globbing**: `FROM 'data\u002Fpart-*.parquet'` reads multiple files\n- **Auto-detection**: CSV headers and schemas are inferred automatically\n\n### Expressions and types\n- **Dot operator chaining**: `'hello'.upper()` or `col.trim().lower()`\n- **List comprehensions**: `[x*2 FOR x IN list_col]`\n- **List\u002Fstring slicing**: `col[1:3]`, negative indexing `col[-1]`\n- **STRUCT.* notation**: `SELECT s.* FROM (SELECT {'a': 1, 'b': 2} AS s)`\n- **Square bracket lists**: `[1, 2, 3]`\n- **format()**: `format('{}->{}', a, b)` for string formatting\n\n### Joins\n- **ASOF joins**: approximate matching on ordered data (e.g. timestamps)\n- **POSITIONAL joins**: match rows by position, not keys\n- **LATERAL joins**: reference prior table expressions in subqueries\n\n### Data modification\n- **CREATE OR REPLACE TABLE**: no need for `DROP TABLE IF EXISTS` first\n- **CREATE TABLE ... 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Explores the schema (tables, columns, row counts) and writes a SQL state file so subsequent queries can restore this session automatically via duckdb -init.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1990,1991,1992],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-07-12T07:54:35.248848",{"slug":1995,"name":1995,"fn":1996,"description":1997,"org":1998,"tags":1999,"stars":22,"repoUrl":23,"updatedAt":2010},"convert-file","convert data files between formats","Convert any data file to another format: CSV, Parquet, JSON, Excel, GeoJSON, and more. Use when the user says \"convert to parquet\", \"save as xlsx\", \"export as JSON\", \"make this a CSV\", \"turn into parquet\", or any variation of format-to-format conversion for data files. Also triggers when the user wants to write Parquet, Excel, or other binary formats that Claude cannot produce natively.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2000,2001,2004,2007],{"name":13,"slug":14,"type":15},{"name":2002,"slug":2003,"type":15},"Data Engineering","data-engineering",{"name":2005,"slug":2006,"type":15},"Excel","excel",{"name":2008,"slug":2009,"type":15},"Spreadsheets","spreadsheets","2026-07-12T07:54:39.62274",{"slug":2012,"name":2012,"fn":2013,"description":2014,"org":2015,"tags":2016,"stars":22,"repoUrl":23,"updatedAt":2026},"duckdb-docs","search DuckDB documentation and blog posts","Search DuckDB and DuckLake documentation and blog posts. Returns relevant doc chunks for a question or keyword using full-text search against a locally cached index.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2017,2020,2023],{"name":2018,"slug":2019,"type":15},"Documentation","documentation",{"name":2021,"slug":2022,"type":15},"Research","research",{"name":2024,"slug":2025,"type":15},"Search","search","2026-07-12T07:54:38.216517",{"slug":2028,"name":2028,"fn":2029,"description":2030,"org":2031,"tags":2032,"stars":22,"repoUrl":23,"updatedAt":2037},"install-duckdb","install and update DuckDB extensions","Install or update DuckDB extensions. Each argument is either a plain extension name (installs from core) or name@repo (e.g. magic@community). Pass --update to update extensions instead of installing.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2033,2034],{"name":17,"slug":18,"type":15},{"name":2035,"slug":2036,"type":15},"Engineering","engineering","2026-07-12T07:54:42.330952",{"slug":4,"name":4,"fn":5,"description":6,"org":2039,"tags":2040,"stars":22,"repoUrl":23,"updatedAt":24},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2041,2042,2043],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":2045,"name":2045,"fn":2046,"description":2047,"org":2048,"tags":2049,"stars":22,"repoUrl":23,"updatedAt":2056},"read-file","read and profile data files","Read any data file (CSV, JSON, Parquet, Avro, Excel, spatial, SQLite) or remote URL (S3, HTTPS). Use when user references a data file, asks \"what's in this file\", or wants to preview\u002Fprofile a dataset. Not for source code.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2050,2051,2054,2055],{"name":13,"slug":14,"type":15},{"name":2052,"slug":2053,"type":15},"Data Quality","data-quality",{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-07-12T07:54:33.514298",{"slug":2058,"name":2058,"fn":2059,"description":2060,"org":2061,"tags":2062,"stars":22,"repoUrl":23,"updatedAt":2070},"read-memories","recall past Claude Code session logs","Search past Claude Code session logs to recall prior decisions, patterns, or unresolved work. Use when user says \"do you remember\", \"what did we do\", references past conversations, or you need context from prior sessions.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2063,2066,2069],{"name":2064,"slug":2065,"type":15},"Claude Code","claude-code",{"name":2067,"slug":2068,"type":15},"Memory","memory",{"name":2024,"slug":2025,"type":15},"2026-07-12T07:54:40.860856",{"slug":2072,"name":2072,"fn":2073,"description":2074,"org":2075,"tags":2076,"stars":22,"repoUrl":23,"updatedAt":2083},"s3-explore","explore and query remote storage data","Explore and query data on S3, Cloudflare R2, GCS, MinIO, or any S3-compatible storage. Use when the user mentions an s3:\u002F\u002F, r2:\u002F\u002F, gs:\u002F\u002F, or gcs:\u002F\u002F URL, asks \"what's in this bucket\", wants to list remote files, preview remote Parquet\u002FCSV\u002FJSON, or query data on object storage without downloading it. Also triggers when the user wants to know the size, schema, or row count of remote datasets.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2077,2080,2081,2082],{"name":2078,"slug":2079,"type":15},"Cloud","cloud",{"name":2002,"slug":2003,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},"2026-07-12T07:54:36.928868",{"slug":2085,"name":2085,"fn":2086,"description":2087,"org":2088,"tags":2089,"stars":22,"repoUrl":23,"updatedAt":2096},"spatial","query spatial data with DuckDB","Answer questions about spatial data using DuckDB. Use when the user mentions locations, coordinates, lat\u002Flng, distances, maps, addresses, \"near\", \"within\", \"closest\", geographic names, or spatial file formats (GeoJSON, Shapefile, GeoPackage, GPX, GeoParquet). Also triggers when the user wants to find places, buildings, or roads — Overture Maps provides free global data on S3 with zero API keys. Handles spatial joins, distance calculations, containment checks, density analysis, and format conversions for geographic data.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2090,2091,2092,2095],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":2093,"slug":2094,"type":15},"Maps","maps",{"name":20,"slug":21,"type":15},"2026-07-12T07:54:32.004105",9,{"items":2099,"total":2097},[2100,2106,2113,2119,2124,2130,2137],{"slug":1985,"name":1985,"fn":1986,"description":1987,"org":2101,"tags":2102,"stars":22,"repoUrl":23,"updatedAt":1993},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2103,2104,2105],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":1995,"name":1995,"fn":1996,"description":1997,"org":2107,"tags":2108,"stars":22,"repoUrl":23,"updatedAt":2010},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2109,2110,2111,2112],{"name":13,"slug":14,"type":15},{"name":2002,"slug":2003,"type":15},{"name":2005,"slug":2006,"type":15},{"name":2008,"slug":2009,"type":15},{"slug":2012,"name":2012,"fn":2013,"description":2014,"org":2114,"tags":2115,"stars":22,"repoUrl":23,"updatedAt":2026},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2116,2117,2118],{"name":2018,"slug":2019,"type":15},{"name":2021,"slug":2022,"type":15},{"name":2024,"slug":2025,"type":15},{"slug":2028,"name":2028,"fn":2029,"description":2030,"org":2120,"tags":2121,"stars":22,"repoUrl":23,"updatedAt":2037},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2122,2123],{"name":17,"slug":18,"type":15},{"name":2035,"slug":2036,"type":15},{"slug":4,"name":4,"fn":5,"description":6,"org":2125,"tags":2126,"stars":22,"repoUrl":23,"updatedAt":24},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2127,2128,2129],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":2045,"name":2045,"fn":2046,"description":2047,"org":2131,"tags":2132,"stars":22,"repoUrl":23,"updatedAt":2056},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2133,2134,2135,2136],{"name":13,"slug":14,"type":15},{"name":2052,"slug":2053,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"slug":2058,"name":2058,"fn":2059,"description":2060,"org":2138,"tags":2139,"stars":22,"repoUrl":23,"updatedAt":2070},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2140,2141,2142],{"name":2064,"slug":2065,"type":15},{"name":2067,"slug":2068,"type":15},{"name":2024,"slug":2025,"type":15}]