gooseworks-ai/customer-story-builder
> Take raw customer inputs — interview transcripts, survey responses, Slack quotes, support tickets, review excerpts — and generate a structured case study draft with problem/solution/result narrative, pull-quotes, metric callouts, and multi-format outputs (full case study, one-pager, social proof snippet, sales deck slide). Pure reasoning skill. Use when a product marketing team has customer signal but no time to write the story.
npx skills add https://github.com/gooseworks-ai/goose-skills --skill customer-story-builder
Turn raw customer signal into a polished case study — plus every derivative format you need. One input (messy transcript or quote), all outputs (case study, one-pager, social snippet, deck slide).
Core principle: The best customer stories already exist in your support tickets, Slack channels, and call recordings. You just need to extract and structure them.
10. Metrics — Any numbers: time saved, revenue impact, efficiency gains, before/after
11. Primary use case — What were they using the product for?
12. Key transformation — What changed? (The "before → after" in one sentence)
13. Output formats needed — Full case study, one-pager, social snippet, sales slide, or all?
From the raw inputs, identify and extract:
Pull the 3-5 strongest verbatim quotes from the raw input:
# [Headline: Outcome-driven, not product-driven]
*[Subhead: Customer name + one-line result]*
---
## About [Customer]
[2-3 sentences: company, industry, size, what they do]
## The Challenge
[2-3 paragraphs: What was the problem? Why did it matter? What had they tried?]
> "[Problem quote]"
> — [Name], [Title] at [Company]
## Why [Your Product]
[1-2 paragraphs: How did they find you? What made them choose you?]
## The Solution
[2-3 paragraphs: How did they use the product? Which capabilities mattered most?]
> "[Solution/experience quote]"
## The Results
[Results summary with metric callouts]
### Key Metrics
- **[Metric 1]:** [Number + context]
- **[Metric 2]:** [Number + context]
- **[Metric 3]:** [Number + context]
> "[Result quote]"
## What's Next
[1 paragraph: Future plans, expansion, what they're excited about]
---
**Industry:** [X] | **Company size:** [X] | **Use case:** [X] | **Product:** [X]
# [Customer Name]: [Headline Result]
**Challenge:** [2 sentences]
**Solution:** [2 sentences — what they use and how]
**Results:**
- [Metric 1]
- [Metric 2]
- [Metric 3]
> "[Hero quote]"
> — [Name], [Title]
[CTA: Learn more / Request a demo]
For website testimonial section:
"[Short, punchy quote — max 2 sentences]"
— [Name], [Title] at [Company]
[Result: X% improvement in Y]
For LinkedIn post:
[Customer Name] just shared their results:
→ [Metric 1]
→ [Metric 2]
→ [Metric 3]
"[Quote]"
Here's their story: [link]
For cold email insert:
[Company in their industry] saw [key metric] after switching to [Product].
"[Short quote about the result]" — [Name], [Title]
Slide title: "[Customer] — [Key Result]"
Left side:
- Challenge: [1 line]
- Solution: [1 line]
- Result: [1 line with metric]
Right side:
> "[Hero quote]"
— [Name], [Title]
[Customer logo]
For website or marketing collateral:
[BIG NUMBER]
[Label — e.g., "hours saved per week"]
— [Customer Name]
Generate 2-3 of these from the strongest metrics.
Before finalizing, verify:
Save all assets to clients/<client-name>/product-marketing/customer-stories/[customer-slug]/:
case-study-full.md — Complete case studyone-pager.md — Sales leave-behindsocial-snippets.md — All social proof formatsslide-content.md — Deck slide contentraw-inputs.md — Original source material (for reference)| Component | Cost |
|-----------|------|
| All story generation | Free (LLM reasoning) |
| Total | Free |
None. Pure reasoning skill. Takes raw text input and produces structured outputs.
Take gooseworks-ai/customer-story-builder from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.