Skill UI

This orchestrator dynamically manages and loads multiple specialized Go skills based on the current task context. Whether you are designing an API, debugging a panic, auditing security, or optimizing performance, it automatically combines the most relevant skills (e.g., gRPC loads testing, error handling, and core Go skills). It acts as a comprehensive guide to Go best practices and modern development patterns.

Generate professional, ATS-optimized CVs and resumes by consolidating data from multiple sources (LinkedIn, GitHub, Portfolio). This skill tailors your content to specific Job Descriptions (JD), adapts tone based on seniority, and outputs paste-ready plain text optimized for tools like FlowCV or Canva. It also provides a detailed ATS flaw report and actionable improvement suggestions.

Generates a highly structured, machine-parseable shooting script for short videos based on a specified topic, style, and duration. It outputs a detailed shot list including image prompts, video prompts, voiceovers, and on-screen text, making it ideal for automated AI video generation workflows.

This skill facilitates the systematic triage and closure of open promises or commitments within a project context. It guides the user to reliably close these commitments using verifiable, real-world outcomes via the acc_act(runtime="outcome") command. It emphasizes maintaining rigorous provenance discipline, ensuring that status updates are based only on external or runtime validated results, thereby maximizing data integrity and accountability.

This guide provides a comprehensive reference on Agent Skills, a standardized and powerful method for providing structured context, workflows, and tools to Large Language Models (LLMs). It details the anatomy of the SKILL.md file, the three-stage progressive disclosure loading process, and best practices for creating both capability (tool-based) and process (workflow-based) primitives. Use this resource when designing, reviewing, or debugging agent-driven applications to ensure reliable and context-efficient performance.

This skill fetches the latest, live documentation and code examples for specific libraries and frameworks (e.g., Next.js, React, Prisma). Instead of relying on static or outdated training data, it utilizes the Context7 MCP to provide accurate, up-to-date answers for setup questions, API references, and code generation based on current best practices.

This is an advanced, structured workflow designed to conduct deep, multi-source investigations. It synthesizes current public evidence with user-provided context to generate highly structured reports. The workflow explicitly differentiates between verifiable facts, user-supplied evidence, logical inferences, and actionable recommendations, making it ideal for complex comparative analysis or continuous monitoring tasks.