new-product
About
This Claude Skill generates enterprise-grade product white papers by sourcing content from Google Drive documentation. It's triggered by requests like "create a product white paper" and is designed for SaaS, hardware, or service offerings. The skill follows a structured workflow to produce strategic, research-backed documents for executive and technical audiences.
Quick Install
Claude Code
Recommended/plugin add https://github.com/christopheryeo/claude-skillsgit clone https://github.com/christopheryeo/claude-skills.git ~/.claude/skills/new-productCopy and paste this command in Claude Code to install this skill
Documentation
Product White Paper
Generate enterprise-grade product white papers that serve as strategic assets for educating buyers and presenting research-backed solutions to complex business problems.
Workflow
Follow these steps to generate a product white paper:
-
Understand the Product: Clarify which product requires a white paper and identify the target audience (C-suite executives, technical decision-makers, or both)
-
Gather Source Material: Search Google Drive for existing product documentation, including:
- Product specifications and feature descriptions
- Technical architecture documentation
- Customer case studies or testimonials
- Competitive analysis
- ROI data or success metrics
- Implementation guides
- Governance and compliance documentation
-
Read the Structure Guide: Load
references/white-paper-essentials.mdto understand the required structure and tone -
Generate the White Paper: Create the white paper following the six-section structure, incorporating information from the gathered source material
-
Present in Chat: Output the complete white paper in the chat window formatted in markdown for easy copy-paste
Search Strategy
When searching Google Drive for source material, use multiple targeted searches:
For product information:
name contains '[product-name]' and (mimeType = 'application/vnd.google-apps.document' or mimeType = 'application/pdf')
For technical documentation:
fullText contains '[product-name]' and (fullText contains 'architecture' or fullText contains 'technical' or fullText contains 'specification')
For business value content:
fullText contains '[product-name]' and (fullText contains 'ROI' or fullText contains 'value' or fullText contains 'benefit' or fullText contains 'case study')
Cast a wide net initially, then narrow based on relevance. Review multiple documents to synthesize comprehensive content.
White Paper Structure
The white paper must follow this six-section structure (detailed in references/white-paper-essentials.md):
- Executive Summary - High-impact summary of strategic and technical takeaways
- The Strategic Imperative - Problem articulation, market context, and business justification
- The Solution Blueprint - Product features, capabilities, and operational benefits
- Building Trust - Governance, assurance, explainability, and risk mitigation
- Enterprise Value and ROI - Multi-dimensional value framework and workforce augmentation
- Implementation and Next Steps - Roadmap, change management, and clear call-to-action
Tone and Quality Standards
Adhere to these principles:
- Educational, not promotional: Establish expertise through depth and research, avoid overt sales language
- Formal and auditable: Use engineering/legal-grade formality with verifiable claims
- Research-backed: Ground all assertions in evidence from source materials
- Executive-relevant: Balance technical depth with strategic business value
- Conversion-oriented: Include clear takeaways and actionable next steps
Output Format
Present the white paper directly in the chat window using markdown formatting:
- Use proper heading hierarchy (# for title, ## for main sections, ### for subsections)
- Bold key terms and concepts for scannability
- Include bullet points for lists of features or benefits
- Maintain professional formatting for easy copy-paste into document editors
Key References
- Detailed structure and requirements: See
references/white-paper-essentials.mdfor comprehensive guidance on each section's purpose, required elements, and tone
GitHub Repository
Related Skills
sglang
MetaSGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.
evaluating-llms-harness
TestingThis Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.
llamaguard
OtherLlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.
langchain
MetaLangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.
