List the 18 transformation operations of Hydra ETL with their required parameters. Call this BEFORE writing a transformations.yaml: any operation missing from this list does not exist and will be rejected.

Return the full JSON schema of one transformation operation: every parameter, its type and its default value. Call this when hydra_list_operations is not enough.

List the connector types accepted by the 'type' key of a source or a destination. Any other type fails at run time: S3, BigQuery and Snowflake are not supported.

List the actions usable in a workflow step of type 'action'. Careful: an unknown action is silently ignored at run time and the step is still counted as successful, so check the name before writing it.

List the Hydra ETL jobs present in the workspace. A job is a folder holding a pipeline.yaml. Returns relative paths, usable as they are in the other tools.

Read the manifests of an existing job. Call this before modifying a job, so you start from its real content instead of rewriting it from memory.

Validate a job with the official Hydra ETL validator: the structure of the four manifests, and the resolution of pipeline.from to a declared source and of pipeline.to to a declared destination. This is the ground truth — if this tool refuses, the job will not run.

Write the manifests of a job, AFTER validation. Each manifest is passed as YAML text. If validation fails, nothing is written and the errors are returned: fix them and call the tool again. Writing does not run the job.

Run a Hydra ETL job and return the execution log. Only call this tool if the user explicitly asked for the run: it writes real data to the destination.

Explain a Hydra ETL validation error in plain language and propose the fix. Use this when hydra_validate_job or hydra_write_job returns a message you cannot interpret.

List the workflows in the workspace. A workflow orchestrates several jobs: dependencies, parallel execution, retries, cron triggering. Use this as soon as the request chains several jobs.

Read an existing workflow.yaml file and return its raw YAML. Call this before modifying a workflow, so you start from its real content instead of rewriting it from memory.

Write a workflow, AFTER validation. A step is either type='job' with the path of a job folder, or type='action'. depends_on is ALWAYS a list: steps with no dependency in common run in parallel. If validation fails, nothing is written.

Run a workflow and return the trace, step by step. Only call this tool if the user asked for the run: the jobs it contains write real data to their destinations.

Show the columns and the first rows of a data file (CSV, JSON, Parquet). Call this BEFORE writing a job, to learn the real column names instead of guessing them — and AFTER a run, to check the result.

Check that a job does what the user actually asked for. This completes hydra_validate_job: that one says whether the YAML is correct, this one whether the job answers the request. Twelve deterministic rules: operation requested but missing, numeric comparison without a cast, load mode contradicted, inconsistent file extension, plaintext secret, unsupported technology. Call this AFTER writing a job, before presenting it.

Find, among real Hydra ETL jobs, the ones closest to the request, and return their manifests. Call this BEFORE writing an unusual job: an example that runs beats a reconstruction from memory.