informatica-assessment
claudeAssess an Informatica PowerCenter estate with collect etl, ds lineage, and migration plan: dependency-ordered scored migration waves and an inventory, offline-capable, no LLM required
3 skills
phData Toolkit CLI foundation: install, PATH setup, project init, JDBC connection/datasource configuration
Plugin toolkit-core from marketplace phdata in phdata/agent-marketplace. Commands read from the repo's manifest — 5 days ago.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
connectAdd or verify a JDBC connection and datasource in toolkit.conf for any supported type — Snowflake, SQL Server, Oracle, Postgres, MySQL, Hive, Databricks, Athena — including JDBC driver installation for non-bundled types and verification via a scoped ds scan. Use when configuring data sources, fixing
llmConfigure the optional llmClient block in toolkit.conf so toolkit agent commands (discovery, pipeline-build, fix-sql, codegen ask) can call an LLM — Amazon Bedrock, OpenAI, or Anthropic. Use when agent commands fail for lack of an LLM, when switching providers or models, or when onboarding to the to
setupInstall and configure the phData Toolkit CLI end to end — verify Java, get the toolkit binary on PATH, authenticate, initialize a toolkit project, and extract Data Source tool defaults. Use when the toolkit is missing, toolkit_check.py fails, or a user is onboarding to phData Toolkit workflows.
statusShow a doctor-style report of the phData Toolkit CLI installation — binary, Java, project, datasources, and optional connectivity. Use when the user asks whether the toolkit is set up, why a toolkit command might be failing, or wants a health check before starting toolkit work.
"${CLAUDE_PLUGIN_ROOT}/scripts/toolkit-check" --hook
Assess an Informatica PowerCenter estate with collect etl, ds lineage, and migration plan: dependency-ordered scored migration waves and an inventory, offline-capable, no LLM required
3 skills
Convert Informatica PowerCenter mappings into Snowflake or Databricks pipelines via agent etl-extract, discovery with a grouped human-review queue, and pipeline-build — one migration-plan group at a time, or a small corpus in a single pass
2 skills
Synthetic, fake, mock, and test data via toolkit datagen: the agent writes a data spec, the toolkit generates related tables at any volume to CSV or into a database, reproducibly via a seed
2 skills
Dataspec-driven pipeline generation via toolkit agent discovery and pipeline-build: SQL, dbt, or PySpark transforms plus tests and a datagen spec
2 skills
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