An AI-driven writing framework that automates B2B case study creation using the STAR method, data visualization, and deep industry research.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install case-study-writing
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install case-study-writing using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Case Study Writing?
The Case Study Writing skill is a professional-grade tool designed for technical content creators and marketers who need to produce high-impact customer success stories. By utilizing the Openclaw Skills architecture, this agent automates the labor-intensive process of industry research, data analysis, and narrative structuring. It follows the proven STAR framework—Situation, Task, Action, and Result—to ensure every story is grounded in quantified metrics and compelling customer evidence.
This skill bridges the gap between raw technical data and persuasive marketing content. By integrating with advanced search APIs and data visualization engines, it allows teams to generate content that proves value through rigorous evidence rather than generic claims. Using Openclaw Skills for this workflow ensures consistency across your entire portfolio of customer success stories.
Case Study Writing Use Cases
- Building a library of B2B customer success stories to drive sales enablement and lead generation.
- Creating data-backed portfolio pieces that demonstrate technical ROI to high-level stakeholders.
- Synthesizing complex project outcomes into structured, skimmable marketing assets for website landing pages.
- Automating industry benchmark research to provide authoritative context for specific customer wins.
- Generating visual performance charts to prove the efficiency gains and financial impact of a product implementation.
How Case Study Writing Works
- The user triggers the skill with a customer win or a specific use case scenario, providing raw data or interview notes.
- The agent performs automated research via integrated search assistants to find relevant industry statistics and benchmarks.
- Information is organized into the STAR framework, prioritizing quantified results and selecting the most impactful customer quotes.
- Python-based visualization tools are invoked to create graphical representations of the "before and after" performance metrics.
- The final content is output in multiple optimized formats, ranging from SEO-ready web copy to concise social media snippets.
Case Study Writing Setup
# Install the inference.sh CLI to enable the skill
curl -fsSL https://cli.inference.sh | sh && infsh login
# Run industry research to support your narrative
infsh app run tavily/search-assistant --input '{"query": "SaaS onboarding metrics 2024 industry benchmarks"}'
Case Study Writing Data Schema & Taxonomy
This skill structures content around a rigorous B2B taxonomy to ensure maximum credibility and search visibility.
| Data Point | Description | Format |
|---|---|---|
| Framework | STAR (Situation, Task, Action, Result) structure | Markdown Headers |
| Snapshot | High-level summary of industry, size, and results | ASCII/Markdown Box |
| Metrics | Quantified data points (Time, Money, Efficiency) | Markdown Table |
| Visuals | Comparative impact charts for results | PNG (via Python-executor) |
| Attribution | Verified customer quotes and professional titles | Blockquotes |
Case Study Writing Advanced Features
- Multi-agent research integration using Tavily and Exa to pull real-time market data and competitor landscapes into Openclaw Skills.
- Programmatic data visualization with Matplotlib for creating professional-grade, verifiable impact charts directly from the CLI.
- Automated social media snippet generation designed for cross-platform distribution on LinkedIn and Twitter.
- Seamless extension support for adding secondary capabilities like advanced web searching and custom prompt engineering modules.
SKILL.md
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