Skill UI

This guide details the comprehensive setup of Granola for large-scale, multi-departmental enterprise environments. It covers creating isolated workspaces (e.g., Engineering, HR, Sales), integrating Identity Providers using SSO/SCIM, and implementing granular compliance controls (data retention, external sharing, MFA) to ensure data security and departmental autonomy.

A comprehensive reference architecture for deploying meeting intelligence platforms (like Granola) across large organizations. This blueprint details the core data capture pipeline, integration topology using middleware (Zapier), multi-workspace structure (Sales, HR, Engineering), and robust security layers (SSO, AES-256) to ensure automated workflows from meeting to action item across all departments.

A comprehensive toolkit designed to professionalize LLM prompt workflows. It moves prompts from ad-hoc drafts to measurable, production-ready assets through A/B testing against structured test cases, immutable version tracking, and governance guidelines. Essential for marketing teams needing verifiable quality and safety for AI-generated content.

This sophisticated framework enables cross-functional 'what-if' scenario modeling. Unlike simple stress tests, it maps compounding adversity across all business domains (Finance, Product, Engineering, etc.). Use it when facing complex, multi-variable risks or making strategic decisions with significant downside potential, allowing teams to map cascading failure paths and define proactive hedges.

Generate tailored roadmap narratives, release notes, changelogs, and stakeholder updates for executives, engineering, and customer audiences, with structured formats, templates, and checklists for consistent product messaging.

An interactive tool designed to discover, select, and assemble specialized teams of AI agents. It supports structured agent collections across different domains (e.g., Engineering, Marketing). Users select multiple roles for a specific task, and the skill launches them in parallel, synthesizing their independent findings into a unified report, including consensus and conflict analysis.

This skill functions as a Narrative Psychologist, mapping and engineering the full emotional journey a customer must take across any content format (e.g., landing pages, email sequences, sales decks). It systematically designs the emotional progression—from the initial state (e.g., skepticism or anxiety) through controlled tension, relief, and anticipation—to the precise emotional state required for a desired action, ensuring the narrative flow is believable and persuasive.

This skill acts as a technical translator, helping Product Managers understand complex systems, codebases, APIs, and technical concepts. It goes beyond simply explaining technology by connecting technical details to real-world product implications (the 'so what'). It structures findings into summaries, workings, product impacts, and crucial questions for engineering, ensuring all insights are immediately actionable for product decisions.

This professional writing assistant specializes in creating clear, compelling, and highly structured documentation for Product Managers (PMs). It helps users draft, refine, and polish various deliverables—including product briefs, status updates, and executive emails—by adhering to best practices like leading with conclusions, maintaining extreme conciseness, and tailoring the tone to the specific audience (e.g., engineering team vs. executive leadership).

Provides C-level strategic guidance for startups deciding on advanced AI implementation. Covers critical decisions including model build-vs-buy analysis (API vs. fine-tune vs. in-house), regulatory compliance risk assessment (EU AI Act, NIST RMF), economic modeling for self-hosting breakeven, and optimal AI team scaling. This is a high-level advisory tool, not a tactical engineering guide.

Provides high-level strategic guidance for founders and Chief Data Officers (CDOs) in startups. This skill covers critical decisions such as AI training data rights and consent provenance, selecting optimal data architectures (warehouse, lakehouse, data mesh), valuing customer data as a strategic asset for M&A or fundraising, and planning data team organizational evolution. It focuses exclusively on strategic decision-making, not tactical engineering.

This skill automates a structured Product Management (PM) design review process. It assesses a Figma design against defined product requirements (PRD) and user flows, ensuring functional completeness and readiness for engineering handoff. It checks for requirements coverage, handles edge cases (empty/error/loading states), identifies functional concerns (not aesthetic), and provides a clear, actionable approval status.