What is build-sql-transformation?

A guide for creating or editing saved SQL transformations in Keboola using Snowflake or BigQuery. A SQL transformation turns a query into a repeatable step that can build tables from existing data.

Use it to create a transformation, change its SQL, build a table from other Keboola tables, or run the saved transformation once.

It provides a structured way to turn an ad hoc query into a saved transformation without changing the wrong Keboola project. It can also clarify whether the saved transformation should be run immediately.

build-sql-transformation — Skill for Claude Code and Codex by keboola

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add keboola/mcp-server --skill build-sql-transformation

Clone the repo

git clone --depth 1 https://github.com/keboola/mcp-server

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/keboola/mcp-server/build-sql-transformation/github.svg)](https://agentmods.dev/skills/keboola/mcp-server/build-sql-transformation)

Your own site

<a href="https://agentmods.dev/skills/keboola/mcp-server/build-sql-transformation"><img src="https://agentmods.dev/badge/skills/keboola/mcp-server/build-sql-transformation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/keboola/mcp-server/build-sql-transformation"><img src="https://agentmods.dev/badge/skills/keboola/mcp-server/build-sql-transformation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,002 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00054	$0.01002
Opus 5.5	$0.00022	$0.00401
Sonnet 5.5	$0.00011	$0.00200
Haiku 4.5	$0.00005	$0.00100

Measured today against content hash 969b92fe73e2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

build-sql-transformation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

integrations/chatgpt-plugin/skills/build-sql-transformation/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build a SQL transformation

Create a new SQL transformation, or update an existing one, in the one project the user confirms.

Input

What the transformation should produce, from which tables, and whether to run it once it is saved. For an existing transformation, its name or ID.

Steps

Pick the project. Call get_accessible_projects (with with_llm_instruction=true on the first call in the conversation). Show the projects and ask the user which one the transformation belongs in. Never pick a project on your own, even when only one is listed: confirm it. Do this even when the session looks scoped already or a data tool would work without it: this plugin always narrows the session to the projects the user confirms. If get_accessible_projects fails because no programmatic token is present, the login is bound to one project: confirm it with the user and skip step 2.
Scope the session to that project. Call set_project_scope with project_ids=[<the confirmed id>]. This must happen before any write. If the result carries a non-null scope_token, pass it on every later tool call. Every write below also passes the confirmed id as project_id: other conversations on the same login share the scope, and a scope they moved makes the write fail instead of landing in another project.
Get context. Call get_project_info with project_id=<the confirmed id>. Note the SQL dialect (Snowflake or BigQuery). Python, R and DuckDB transformations are out of scope for this skill; say so and stop. If its toolset_restrictions say only read-only tools are available, tell the user they cannot save transformations in this project and stop.
Find the inputs. Use search with item_types=["table"] for the source tables, then get_tables with table_ids=[...] for their fullyQualifiedName and column quotedName values.
Prototype the SQL. Run the SELECT part through query_data with a small LIMIT and show the user sample rows. Fix errors here, before anything is saved.
Save it.
- New transformation: call create_sql_transformation with project_id=<the confirmed id>. Reference input tables by fully qualified name; create output tables with the dialect's delimited plain name ("daily_orders" on Snowflake, a backticked name on BigQuery), never a fully qualified one, and list the names without delimiters in created_table_names=[...]. Give it a name and description that state its purpose.
- Existing transformation: find it with search and item_types=["transformation"], read it with get_configs and configs=[...] to get the block_id and code_id values, then call update_sql_transformation with project_id=<the confirmed id>, configuration_id=..., parameter_updates=[...] (operations such as set_code or str_replace) and change_description=.... A storage=... value replaces all mappings: include every mapping you want to keep.
Run it, if the user asked. Ask before running. Call run_job with project_id=<the confirmed id> and the transformation's component_id=... and configuration_id=..., then poll get_jobs with job_ids=[...] until the job ends. On failure, continue with the debug-failed-job skill.
Report. Give the transformation name, the output tables, the job result and the links the tools returned.

Read the full file on GitHub · 59 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

today First seen · 59 lines · 54 tokens per session scan A 969b92fe73e2

Subscribe to this mod's changes

build-sql-transformation is a skill published in the GitHub repository keboola/mcp-server (85 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 1,002 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-23.

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