batch-product-research

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Codex-native batch Amazon keyword research using LaunchFast MCP. Use when the user wants a ranked comparison across many keywords and optionally wants HTML and CSV artifacts written to disk.

hashgraph-online By hashgraph-online schedule Updated 4/3/2026

name: batch-product-research description: | Codex-native batch Amazon keyword research using LaunchFast MCP. Use when the user wants a ranked comparison across many keywords and optionally wants HTML and CSV artifacts written to disk.

Batch Product Research

Use this skill for 1-20 keywords.

Inputs

Accept:

  • comma-separated keywords
  • numbered lists
  • a local file path containing keywords

Defaults:

  • maximum 20 keywords per run
  • report path: ./artifacts/launchfast/batch-research/report-[YYYY-MM-DD].html
  • csv path: ./artifacts/launchfast/batch-research/report-[YYYY-MM-DD].csv

Workflow

1. Normalize input

  • trim whitespace
  • deduplicate case-insensitively
  • if there are more than 20 keywords, split into chunks of 20 and process chunk-by-chunk

2. Run balanced product research

  • run research_products for every keyword
  • prefer parallel tool calls where practical
  • do not require delegation

3. Score each keyword

For each keyword compute:

  • search volume
  • total niche revenue
  • average price
  • average reviews
  • average revenue per seller
  • top-seller dominance
  • estimated margin using conservative assumptions
  • opportunity score and verdict

Use verdicts:

  • VIABLE
  • MARGINAL
  • NOT RECOMMENDED
  • ERROR

4. Optional deeper passes

For VIABLE or MARGINAL keywords only:

  • run research_products(... focus="financial")
  • optionally run amazon_keyword_research on the top 2-3 ASINs if keyword depth matters for the user’s goal

5. Present ranked results

Always include a comparison table first.

Then provide concise cards or sections for the strongest keywords.

6. Write artifacts when useful

If the user asked for files, or a file materially improves the result:

  • write an HTML report
  • write a CSV export

Keep the file generation deterministic. Prefer Python for CSV writing.

Output

At minimum return:

  • number of keywords processed
  • ranking table
  • top recommendations
  • artifact paths when files were written
Install via CLI
npx skills add https://github.com/hashgraph-online/awesome-codex-plugins --skill batch-product-research
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