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_productsfor 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_researchon 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