Skill UI

This skill helps plan work by creating a concise Product Development Requirement (PDR) and implementation-sized tasks within the YYLO Ledger system. It reads project instructions, defines scope, risks, and acceptance criteria, then registers tasks using CLI commands. It ensures proper task ownership and dependencies without starting actual implementation or deployment.

A framework for breaking down work into clear, small, verifiable tasks. Use for feature implementation, bug fixes, refactoring, or any multi-step work. Emphasizes short plans, specific actions, and project-specific verification.

Polis Protocol transforms static AI agent workflows into a self-improving, dynamic team environment. It uses a learning router to assign tasks based on an agent's historical track record and effectiveness on specific domains, rather than fixed roles. It is vendor-agnostic, allowing diverse agents (e.g., Claude, Gemini) to collaborate under a unified, auditable governance structure where agents can propose and vote on amending the protocol's core rules.

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.

Create and maintain a reusable product marketing context document covering positioning, ICP, personas, use cases, messaging and brand voice. Use at project start so later marketing tasks don't repeat core context.

This skill provides sophisticated project estimation by adapting to human-only, hybrid, or agent-first development modes. It uses research-backed PERT statistics and confidence bands (P50, P75, P90) to forecast development timelines for tasks, backlogs, and capacity planning. It continuously calibrates estimates based on actual completion data, ensuring accuracy in AI-assisted and hybrid development environments.

This skill covers principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. It applies to batch pipelines, multi-agent systems, and interactive applications. Key concepts include task-model fit recognition, manual prototyping, pipeline architecture, file system state management, and structured output design for reliable parsing.

Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Uses Python libraries like pandas and numpy for algorithmic trading and financial modeling tasks.

Implement proven methodologies and tool workflows from top security researchers for effective reconnaissance, vulnerability discovery, and bug bounty hunting. Automate common tasks while maintaining thorough coverage of attack surfaces.

Search and retrieve Remotion documentation using Algolia API and Markdown URLs. Helps developers find accurate API references and implementation guides for video creation tasks without memorizing details. Supports workflow for discovering current docs and fetching source code.

Automate browser and Windows desktop application interactions using Playwright and OpenReverse for reverse engineering, evidence collection, and UI-driven workflows. Supports network observation and structured UI operations for security analysis tasks.

This skill addresses vague or ambiguous user requests by initiating a structured, multi-round questioning process. Instead of making assumptions, it systematically clarifies dimensions like audience, scope, tone, and format across several rounds (up to three). This structured approach ensures the resulting output is highly accurate and requires minimal revision cycles.