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Documentation Index

Fetch the complete documentation index at: https://developers.scrunch.com/llms.txt

Use this file to discover all available pages before exploring further.

These prompts produce ranked lists optimized for two jobs: sharing the wins with stakeholders and triaging where to act next. Each one returns a top-10 or bottom-10 view sorted by observation count or visibility rate.
The highest-visibility prompts — what’s driving them, and what do they have in common?
For [brand name], pull prompt variants filtered to brand_present = true. Sort by observation_count descending. Return the top 10.

For each:
- Show the seed prompt text
- Show the platform
- Show the observation count
- Note whether it's branded or unbranded
- Note the tag/topic

Summarize: what do [brand name]'s best-performing prompts have in common? Topic, framing, funnel stage?
The most-observed queries where [brand name] is absent — ranked by how much it matters.
For [brand name], pull prompt variants filtered to brand_present = false. Sort by observation_count descending. Return the top 10.

For each:
- Show the seed prompt text
- Show the platform
- Show the observation count
- Note whether it's branded or unbranded
- Note which competitors appear instead (if any)

Prioritize: which of these 10 gaps represents the most urgent fix, and why?
The highest-observation prompts where [competitor name] appears and [brand name] doesn’t — what to fix first.
For [brand name], get the competitor ID for [competitor name]. Pull variants filtered to:
- competitor_present = [competitor ID]
- brand_present = false

Sort by observation_count descending. Return top 10.

These are the highest-stakes losses — prompts where [competitor name] is getting the AI mention and [brand name] isn't. For each, identify what content [brand name] would need to create or optimize to compete.
The owned pages that AI cites most often — understand what makes them work so you can replicate it.
For [brand name], pull variants filtered to citation_domain = [brand domain]. Sort by observation_count descending. Return top 10.

These are the prompts where [brand name]'s own content is getting cited most by AI. Note which pages are cited and what topics they cover. These are the pages to protect, expand, and use as a model for other content.
Tag groups with the lowest visibility rate — combining gap size and observation volume into a single priority score.
For [brand name], get all tags. For each tag, pull:
- Total variant count for that tag
- brand_present = true count for that tag

Calculate visibility rate per tag. Return the 10 tags with the lowest visibility rate. Rank by urgency: low visibility rate combined with high observation count = highest priority.

Reporting Digests

Package these rankings into a pre-call brief, monthly digest, or QBR summary.

Monthly Client Report

Full workflow: pull all the data and have Claude write and save the complete report.