Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/parallel-web/parallel-cursor-plugin/parallel-data-enrichmentnpx skills add parallel-web/parallel-cursor-plugin --skill parallel-data-enrichmentgit clone --depth 1 https://github.com/parallel-web/parallel-cursor-pluginWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.01209 |
| Opus 5 | $0.00031 | $0.00605 |
| Sonnet 5 | $0.00012 | $0.00242 |
| Haiku 4.5 | $0.00006 | $0.00121 |
Grade A, and why
parallel-data-enrichment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to parallel-data-enrichment — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 suggestrequiresparallel-cli≥ 0.3.0. If it errors with anything resemblingno 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 mentionparallel-cli update(orpipx 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:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 98 lines · 62 tokens per session scan A fe4ac98b003f
parallel-data-enrichment is a skill published in the GitHub repository parallel-web/parallel-cursor-plugin (3 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 1,209 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to parallel-data-enrichment, differing in 18 lines, and is treated as a copy.
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