Exasol ai setup

Skill exasol-labs/exasol-agent-skills/plugins/exasol/skills/exasol-ai-setup

Exasol skills for AI agents. Optimized for Claude Code and OpenAI Codex 🤖

Install

npx -y skills add exasol-labs/exasol-agent-skills --skill exasol-ai-setup

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What its author says it does

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Set up notebook-connector configuration for Exasol AI workflows through the Secrets Python API. Covers secure-store creation, backend-specific config values, Python validation, and handoff to downstream notebook-connector skills.

SKILL.md

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Exasol AI Setup Skill

Trigger when the user mentions notebook-connector, secure config store, Secrets, configure notebook-connector, AI setup, set up credentials for TE, set up credentials for TXAIE, first-time notebook-connector setup, or similar setup tasks.

Purpose

This skill establishes the Python-managed secure configuration that later notebook-connector skills depend on.

After configuration is complete:

activate exasol-itde for local Docker DB lifecycle
activate exasol-notebook-connections for Python DB and BucketFS helper APIs
activate exasol-transformers for Transformers Extension setup and usage
activate exasol-text-ai for Text AI Extension setup and usage
activate exasol-bucketfs or exasol-udfs only for deeper BucketFS or SLC work beyond notebook-connector setup

Routing Algorithm

Choose the narrowest path that matches the user request:

Python-based configuration
- Trigger phrases: Secrets, AILabConfig, StorageBackend, save config in python, notebook cell, script
- Load: references/secrets-python.md
- Use scripts from: scripts/
Validation / smoke tests
- Trigger phrases: check config, verify connection, validate notebook-connector, smoke test
- Load: references/validation.md
- Use scripts from: scripts/
Downstream notebook-connector work
- Trigger phrases: bring_itde_up, open_pyexasol_connection, open_sqlalchemy_connection, open_ibis_connection, open_bucketfs_bucket, initialize_te_extension, initialize_text_ai_extension, deploy_license
- Hand off to exasol-itde, exasol-notebook-connections, exasol-transformers, or exasol-text-ai after setup validation succeeds

Multiple routes can apply. Load all matching references before responding.

Default Guidance

Prefer the Python path when the user wants notebook cells, automation, or agent-generated code.
Before handing off to DB helpers, BucketFS helpers, TE, or TXAIE work, run scripts/validate_config.py to confirm the Secrets store is populated for the expected backend.
Use AILabConfig as the source of the common key names stored in Secrets.

Validation

After writing or updating config, verify it before handing off to downstream skills:

run scripts/validate_config.py

Success signals:

the backend resolves to the expected value (onprem or saas)
the required setup values for this skill are present in the store so downstream notebook-connector workflows can proceed

Expected failure mode:

if required setup values for this skill such as storage_backend, db_schema, backend-specific connection values, or real credentials are missing, or the store still contains template values such as my-db-host or placeholder SaaS IDs/PATs, setup validation should fail until the user replaces them with real values

Safety Rules

Do not guess SaaS account IDs, PATs, passwords, or BucketFS credentials.
Do not read secrets from config files unless the user explicitly provides them.