Is there a limit on how many keywords the Convert Keywords tab can handle?

The single-batch tab sends your entire list in one API call with no batching, and the Claude path caps output at 2,000 tokens, so long lists can produce truncated JSON and fail. For anything beyond a modest list, use the Bulk Processing tab, which batches 10 to 50 keywords per call (default 25) with a 1 second pause between batches.

How does consolidation work and can I trace which keywords went where?

With consolidation on, the model groups keywords sharing the same intent into a single question, so you get fewer questions than keywords by design. Every output row includes an original_keywords column listing exactly which inputs each question covers, plus a keyword_count. With consolidation off, it asks for one question per keyword.

Does the tool check that every keyword was converted?

No. There is no validation that the model's original_keywords cover your full input, and in bulk mode a failed batch is skipped without its keywords appearing in the output. Reconcile the keyword_count total against your input size if completeness matters.

How are commas handled when I paste keywords?

The paste box splits on commas only when the input contains no line breaks at all. If you paste one keyword per line, commas inside a keyword are preserved. Avoid mixing both separators in one paste.

What does the topic column do in bulk mode?

If you select a topic or category column, keywords are grouped by that value and each group is processed with its topic passed to the model as context, which produces more specifically framed questions. Batching still applies within each group, and the topic is echoed back in the output for filtering.

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Keyword to Questions

Use cases

FAQ page creation People Also Ask targeting Content brief development Featured snippet optimisation

Claude Sonnet 4.5/4, Haiku 4.5 or GPT-4o/4o-mini.

Three question styles: Natural Conversational, Direct Simple, Formal Professional.

Optional keyword consolidation (groups similar intent into single questions).

OpenAI uses structured JSON schema responses.

Streamlit App Requires API Key

Platform

Browser-based (no installation required)

Input

Anthropic or OpenAI API key

Keywords: comma/newline separated or CSV/Excel

Optional: topic context for better questions

Output

Questions with source keywords and keyword count. FAQ template. CSV/Excel with all data.

Launch App View Source

Features

Three question styles (Natural/Direct/Formal)
Keyword consolidation for similar intent
Configurable batch size for bulk
FAQ template text file export
Expandable question cards with source keywords

How to use

1 Enter API key and select model
2 Choose question style (Natural/Direct/Formal)
3 Paste keywords or upload file
4 Toggle consolidation for similar keywords
5 Download CSV, FAQ template, or Excel

Frequently asked questions

Is there a limit on how many keywords the Convert Keywords tab can handle?: The single-batch tab sends your entire list in one API call with no batching, and the Claude path caps output at 2,000 tokens, so long lists can produce truncated JSON and fail. For anything beyond a modest list, use the Bulk Processing tab, which batches 10 to 50 keywords per call (default 25) with a 1 second pause between batches.
How does consolidation work and can I trace which keywords went where?: With consolidation on, the model groups keywords sharing the same intent into a single question, so you get fewer questions than keywords by design. Every output row includes an original_keywords column listing exactly which inputs each question covers, plus a keyword_count. With consolidation off, it asks for one question per keyword.
Does the tool check that every keyword was converted?: No. There is no validation that the model's original_keywords cover your full input, and in bulk mode a failed batch is skipped without its keywords appearing in the output. Reconcile the keyword_count total against your input size if completeness matters.
How are commas handled when I paste keywords?: The paste box splits on commas only when the input contains no line breaks at all. If you paste one keyword per line, commas inside a keyword are preserved. Avoid mixing both separators in one paste.
What does the topic column do in bulk mode?: If you select a topic or category column, keywords are grouped by that value and each group is processed with its topic passed to the model as context, which produces more specifically framed questions. Batching still applies within each group, and the topic is echoed back in the output for filtering.

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