Data 6,433 installs

parallel-data-enrichment

by parallel-web/parallel-agent-skills

Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or…

Skill content

Bulk enrichment of company, people, or product data with web-sourced fields like CEO names, funding, and contact info.

- Accepts inline JSON data or CSV files; outputs enriched results to CSV

- Runs asynchronously with progress tracking via monitoring URL and polling commands

- Requires parallel-cli tool and internet access; handles large datasets with configurable timeouts

- Supports flexible field requests through natural language intent descriptions (e.g., "CEO name and founding year")

Data Enrichment

Enrich: $ARGUMENTS

Before starting

Inform the user that enrichment may take several minutes depending on the number of rows and fields requested.

Optional: Suggest output columns

If the user gave a vague intent ("enrich these companies with useful info") and you're not sure what columns to add, ask the API for a suggestion before kicking off the run:

parallel-cli enrich suggest "Find CEO and recent funding info" --json

The response is an envelope: {title, processor, enriched_columns, warnings}. Extract just the enriched_columns array (not the whole envelope) and pass it as the value of --enriched-columns on enrich run, in place of --intent - the two flags are alternative ways to specify what to enrich, not combined. If suggest returned a processor, pass it through explicitly via --processor on the run call (it's a tuned recommendation for the schema). Skip this whole section if the user already specified the fields they want.

enrich suggest requires parallel-cli ≥ 0.3.0. If it errors with anything resembling no such command / No such command / unknown command, do not bail - skip the suggestion step, fall through to step 1 with --intent, complete the run, and mention parallel-cli update (or pipx upgrade parallel-web-tools) in the final response so the user picks up the feature next time.