Install
$ agentstack add skill-cartodb-agent-skills-carto-query-datawarehouse ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
carto-query-datawarehouse
Run SQL — spatial or otherwise — against any connection CARTO has registered. The CLI exposes two surfaces:
carto sql query—SELECTqueries that return rows. Has a 1-minute timeout. Optional client-side caching.carto sql job— DDL/DML jobs (CREATE TABLE AS SELECT,UPDATE,INSERT). No timeout; polls until done; returns no rows.
Plus a sibling for usage analytics:
carto activity query— DuckDB-backed SQL over downloaded CARTO activity data. Local execution, separate from warehouse SQL.
When to use this skill
- The user wants to count rows, run an exploratory
SELECT, or build a transformation. - The user is debugging slow / failing SQL.
- The agent needs to materialize an intermediate table before authoring a map.
- The user wants to run an ad-hoc spatial join, buffer, or H3 aggregation.
Quick reference
# Read query (returns rows; 1-min timeout)
carto sql query "SELECT * FROM dataset.table LIMIT 10"
# Long-running job (DDL/DML; polls to completion; no rows back)
carto sql job "CREATE TABLE my_ds.out AS SELECT ..."
# From file
carto sql query --file query.sql
# Piped
echo "SELECT 1" | carto sql query
| Use | Command | |---|---| | Exploratory SELECT (small result, fast) | sql query | | Cached SELECT (deterministic, 1y TTL) | sql query ... --cache | | CREATE TABLE AS SELECT, large UPDATE | sql job | | 5+ minute aggregation | sql job (queries time out at 1 min) |
--cache switches to GET with a cached response (1 year, 1 min timeout). Use only for queries that are deterministic and small enough for a URL.
What's in this skill
| Topic | Reference | |---|---| | sql query vs sql job, caching, timeouts | [references/sql-jobs-and-caching.md](references/sql-jobs-and-caching.md) | | Spatial SQL idioms — BigQuery dialect | [references/spatial-sql-bigquery.md](references/spatial-sql-bigquery.md) | | Spatial SQL idioms — Snowflake dialect | [references/spatial-sql-snowflake.md](references/spatial-sql-snowflake.md) | | Spatial SQL idioms — Postgres / PostGIS dialect | [references/spatial-sql-postgres.md](references/spatial-sql-postgres.md) | | Querying CARTO activity data (local DuckDB) | [references/activity-queries.md](references/activity-queries.md) |
Always-on guidance
- Always specify a connection. `
insql query ...is the connection name fromconnections list`, not the warehouse project ID. - Use
--jsonwhen an agent will parse the output. Default text output is for humans. - Prefer
sql jobfor any query that might exceed 60 s.sql queryhas a hard 1-minute server-side timeout regardless of the user's patience. - Don't
SELECT *on warehouse tables blindly. Spatial tables can be 100M+ rows; always project columns and addLIMITfor exploration. - Dialect mismatch is the #1 source of confusion.
ST_DWithinexists in PostGIS and Redshift, but isST_DWITHINin Snowflake and lives underST_DWithinin BigQuery'sbigquery-public-data.geo_us_boundariesstyle. The reference per dialect explains the canonical form. - For activity-data analysis (who edited what, quota usage, login patterns), use
activity query— it runs DuckDB SQL locally over downloaded data. See [references/activity-queries.md](references/activity-queries.md).
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: CartoDB
- Source: CartoDB/agent-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.