Search public Goodeye templates, copy a CLI command, and let your agent fetch the workflow through Goodeye.
Use when you need real unit tests for a function, class, or module and want them generated, verified, and ready to merge. Describe the target in plain language; the workflow handles discovery and writing, then confirms the tests pass, lift coverage, and lint cleanly before handoff.
OutcomeUnit tests for the named target land in the project, exercise at least one happy path and at least one error path, raise the target file's line coverage, and lint clean.
Use when the user asks a natural-language data question against a database in the current directory and wants a reviewable SQL query back. The agent discovers the schema and SQL dialect from the surrounding context (env vars, migration files, ORM models) before asking the user, drafts the query alongside a written rationale, and checks that the SQL parses in the right dialect, hits real columns, and stays read-only unless the user explicitly asked for a write.
OutcomeA reviewable SQL query plus a written rationale covering tables, joins, filters, output columns, and assumptions, all verified to parse in the inferred dialect, reference real columns from the schema, and avoid accidental writes.
