Skill UI

A comprehensive, expert-level guideline for building Agentic User Interfaces (UIs). This system emphasizes conversational interactions, clear outcomes, and minimal user controls, allowing users to delegate complex tasks to AI. It provides structured rules covering color tokens, typography, accessibility (WCAG 2.2 AA), and component anatomy for professional developers and designers.

This skill summarizes the current conversation into a structured handoff document, ideal for passing work to a fresh AI agent or starting a new session. It avoids content duplication by referencing existing artifacts (PRDs, plans, issues, commits) using their paths or URLs, ensuring the receiving agent has a concise and actionable overview of the project's state, open decisions, and next steps.

This powerful skill pauses deep technical discussions to conduct a comprehensive, multi-dimensional reassessment. It analyzes conceptual drift, identifies unverified assumptions, and detects potential cognitive biases (e.g., confirmation bias, sunk cost fallacy). Use it when the conversation is becoming overly detailed, or when a strategic check-in is needed to ensure the focus remains on the core objective and the correct problem is being solved.

This skill orchestrates the process of converting a detailed, multi-turn conversation, complex workflow, or troubleshooting path into a standardized, reusable SKILL.md format. It guides the user through proposing a structured plan, ensuring all necessary steps, triggers, and inputs are captured before materializing the final, callable skill for future use.

A dedicated skill for performing manual data synchronization and knowledge recall with OpenViking. It allows users to explicitly trigger chat transcript syncing from OpenClaw sessions and perform targeted memory searches via command line, without disrupting normal conversation flow or occupying the standard context engine slot.

This tool accesses a persistent FTS5 knowledge base containing previously indexed project documentation, local content, and session memory. Instead of feeding entire raw sources into the conversation context, it allows users to perform targeted, efficient searches using specific queries and source scoping. This is ideal for quickly retrieving technical details, project specifications, or historical context without lengthy re-reading.

A comprehensive workflow designed to convert unstructured conversational data, meeting notes, and ad-hoc decisions into highly structured, linkable entries within Notion. This tool ensures that all captured knowledge—whether an FAQ, a 'how-to' guide, or a formal decision log—is properly documented, categorized, and linked to maintain a cohesive, searchable knowledge base for easy reuse across teams.

This advanced tool surfaces critical, often unrecorded, evidence of human-AI collaboration during development sessions. It analyzes git diffs and conversational context across multiple layers to classify the signal level (HIGH/MEDIUM/LOW), measure technical complexity, detect decision forks, and quantify the specific contribution of the AI model, providing structured data for post-session retrospectives and accountability.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

This skill enforces a high standard for all generated code, prioritizing correctness, clarity, and idiomatic patterns across all languages. It helps minimize code bloat by removing unnecessary abstractions and verbose patterns, while also optimizing the agent's output by using targeted diffs and eliminating excessive conversational overhead. Use this for all code generation, refactoring, or review tasks.

This skill generates a comprehensive discovery call brief designed for sales professionals. Users input prospect details and product info, and the AI outputs a structured guide including market research summaries, hypotheses about pain points, deep-dive questioning frameworks, and clear success criteria. It ensures every sales conversation is strategic, context-driven, and leads to a defined next step.

Generates a comprehensive and actionable playbook designed for Customer Success Managers (CSMs) and Account Teams. This playbook structures all necessary elements for a renewal conversation, including detailed account health assessments, stakeholder mapping, risk registers, ROI value stories, and commercial negotiation strategies. It ensures that the team is prepared 90-180 days before the renewal date to maximize retention and identify expansion opportunities.