SKILL_TEMPLATE
[1-2 sentence description of what this skill does]. Triggers on [specific phrases/contexts that should activate this skill]. Outputs [what the skill produces].
Build customer case studies as marketing and chasm-crossing reference assets during PRD v1.0 Market Adoption. Triggers on requests to build case studies, produce customer stories, create reference content, or when user asks "build a case study", "customer story", "reference
$ npx -y skills add mattgierhart/PRD-driven-context-engineering --skill prd-v10-case-study-builder --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/prd-v10-case-study-builderContext preview
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Build customer case studies as marketing and chasm-crossing reference assets during PRD v1.0 Market Adoption. Triggers on requests to build case studies, produce customer stories, create reference content, or when user asks "build a case study", "customer story", "reference
name: prd-v10-case-study-builder description: > Build customer case studies as marketing and chasm-crossing reference assets during PRD v1.0 Market Adoption. Triggers on requests to build case studies, produce customer stories, create reference content, or when user asks "build a case study", "customer story", "reference account", "case study interview", "before/after story", "social proof page", "logo wall". Outputs CFD-CASE-* evidence entries, GTM-CASE-* marketing assets, and updates ADO-REF-* with story status. context: fork allowed-tools: - Read - Write - Edit - Glob - Grep execution_modes: default: standard supports: [quick, standard, deep]
Position in workflow: v1.0 Mom Test Interview → **v1.0 Case Study Builder** → v1.0 Testimonial Collector, GTM channels
Default is **standard**. See [`.claude/rules/08-skill-execution-modes.md`](../../rules/08-skill-execution-modes.md) for selection logic.
| Mode | What this skill produces | |------|--------------------------| | **quick** | Short-format case (testimonial + 1-paragraph story + logo); single placement | | **standard** | Full case study (1,500 words) + short and medium derivatives + customer-approved + 3 channel placements | | **deep** | Long-form case (2,500–4,000 words) + multi-format derivatives (PDF, blog, video, conference talk) + measurable outcome quantified + outcome-attribution interview |
Turns customer success — already documented as CFD-* evidence and ADO-REF-* candidates — into structured **case studies**. Case studies are the pragmatist buyer's #1 reference signal: they need to see a customer in their segment achieving the outcome they want, with enough detail to make it credible.
This is an **operational** "doing" skill, not a strategy skill. The strategic question (which segment, what story angle, what outcome to highlight) was answered by [prd-v10-chasm-adoption-moore](../prd-v10-chasm-adoption-moore/SKILL.md). This skill produces the artifact.
1. **Identify candidate customers** — Pull from ADO-REF-* candidates and CFD-* entries with strong outcome quantification. Must satisfy:
2. **Run the case-study interview** — Extended Mom Test interview (45–60 min), focused on:
3. **Structure the story** — Situation → Complication → Question → Resolution (the McKinsey SCQR pattern):
4. **Quantify outcome** — Specific numbers beat vague claims:
5. **Get customer review** — Send draft to customer for accuracy + tone + legal. Iterate until approved. 6. **Produce in 3 formats**:
Customer: Acme Logistics (beachhead segment: freight forwarders, 50-200 employees, US PNW). ADO-REF-002.
**Interview**: 50 minutes with Acme's VP Operations.
**Quantified outcome**:
**SCQR**:
**Three formats produced**:
| Trigger | Mode | |---------|------| | First reference customer in beachhead is ready to talk | standard | | Chasm-crossing push needs 3+ in-segment case studies | deep | | Pricing-page logo wall expansion | quick (short format only) | | Sales enablement asset for new segment | standard | | Investor / partner update
PRD-Led Context Engineering — Memory as Infrastructure. An ontology layer for product teams building products that solve real problems — with AI agents that remember. Gated PRD, typed IDs, markdown knowledge graph, Claude Code skills & hooks.
Repo: mattgierhart/PRD-driven-context-engineering
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