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Parallel Data Enrichment

  • 8 installs
  • 3 repo stars
  • Updated May 6, 2026
  • parallel-web/parallel-cursor-plugin

This is a copy of parallel-data-enrichment by parallel-web - installs and ranking accrue to the original listing.

Helps with ai & agent building tasks during AI-assisted development.

About

parallel-data-enrichment is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • parallel-data-enrichment
  • AI & Agent Building
  • AI-coding skill

Parallel Data Enrichment by the numbers

  • 8 all-time installs (skills.sh)
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/parallel-web/parallel-cursor-plugin --skill parallel-data-enrichment

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Listed on Skillselion
Installs8
repo stars3
Last updatedMay 6, 2026
Repositoryparallel-web/parallel-cursor-plugin

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

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.

Step 1: Start the enrichment

Use ONE of these command patterns (substitute user's actual data):

For inline data:

parallel-cli enrich run --data '[{"company": "Google"}, {"company": "Microsoft"}]' --intent "CEO name and founding year" --target "output.csv" --no-wait --json

For CSV file:

parallel-cli enrich run --source-type csv --source "input.csv" --target "output.csv" --source-columns '[{"name": "company", "description": "Company name"}]' --intent "CEO name and founding year" --no-wait --json

If this is a follow-up to a previous research task and you have its interaction_id, add context chaining:

parallel-cli enrich run --data '...' --intent "..." --target "output.csv" --no-wait --json --previous-interaction-id "$INTERACTION_ID"

The enrichment will run with the full context of that prior research — so you can enrich entities discovered earlier without restating what was already found. Note: enrichment does not itself produce a new interaction_id, so you cannot chain a further follow-up off of an enrichment.

IMPORTANT: Always include --no-wait so the command returns immediately instead of blocking.

Parse the --json output to extract taskgroup_id and url. The output is {taskgroup_id, url, num_runs} — there is no interaction_id field, do not look for one. Immediately tell the user:

  • Enrichment has been kicked off
  • The monitoring URL where they can track progress

Tell them they can background the polling step to continue working while it runs.

Step 2: Poll for results

Pick a concrete output path (e.g., /tmp/enrichment-acme.json). Note: the file is JSON regardless of the extension you choose — it's an array of {input, output} objects, not a CSV. Name it .json to avoid confusing yourself or the user.

parallel-cli enrich poll "$TASKGROUP_ID" --timeout 540 --output "/tmp/enrichment-<descriptive-name>.json"

Important:

  • Use --timeout 540 (9 minutes) to stay within tool execution limits
  • The --target from step 1 is unused in --no-wait mode — only --output here determines where results are saved, and the file is always JSON

If the poll times out

Enrichment of large datasets can take longer than 9 minutes. If the poll exits without completing: 1. Tell the user the enrichment is still running server-side 2. Re-run the same parallel-cli enrich poll command to continue waiting

Response format

After step 1: Share the monitoring URL (for tracking progress).

After step 2: 1. Report number of rows enriched 2. Preview first few rows from the output file (it's a JSON array of {input, output} objects) 3. Tell the user the full path to the output file

Do NOT re-share the monitoring URL after completion — the results are in the output file.

If the parallel-cli binary is not installed

If the shell reports command not found: parallel-cli (i.e. the binary itself is missing — distinct from a No such command error from a stale CLI, which the in-body guidance above covers), stop immediately. Do NOT search the web yourself, do NOT use any built-in search tools, and do NOT try to answer the query from your own knowledge. Instead, tell the user:

1. parallel-cli is not installed 2. Run /parallel-setup to install it 3. Then retry their request

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