Skill UI

This skill enables AI agents to orchestrate complex workflows by delegating tasks to ephemeral workers. It protects context limits by isolating multi-file operations, testing, debugging, and reviews into separate sessions. Use delegate_task for broad exploration, multi-step debugging, or adversarial reviews. Verify worker outputs before reporting.

This skill governs the cluster-level resolution of complex defect backlogs. It moves beyond surface fixes by identifying and resolving the true causal root of issues. The methodology mandates rigorous evidence checking, creating read-only mechanism maps, and prioritizing destructive fixes (deletion-driven) to ensure clean, verifiable code state and prevent compatibility debt.

This skill outlines a highly rigorous, receipt-driven workflow for managing defects and implementing code corrections. It guides public collaboration by enforcing strict controls over change authority, ensuring comprehensive lineage tracking, and mandating evidence-based validation. Key steps include CodeGraph impact mapping, black-box testing, and adherence to strict change budgets, ensuring every deployed change is fully traceable and robust.

This specialized sub-agent is responsible for transforming high-level feature proposals and technical specifications into a formal, comprehensive 'design.md' document. It systematically captures all necessary technical details, including architectural decisions, data flow diagrams, detailed file changes, API contracts, and thorough testing strategies. Use this skill during the planning phase of any complex software change to ensure technical completeness and feasibility.

Guides users through a complete Spec-Driven Development (SDD) cycle on their actual codebase, from exploration to archive. Interactive walkthrough with narrated phases, teaching by doing. Suitable for onboarding developers to SDD methodology.

This sophisticated sub-agent takes comprehensive Software Design Documents (SDD), proposals, and specifications to generate a detailed, actionable task breakdown in the format of a tasks.md file. It structures the work into distinct phases (e.g., Foundation, Core Implementation, Testing, Cleanup), providing concrete, verifiable, and small units of work suitable for immediate engineering execution and managing complex feature delivery chains.

Run optional practical diagnostics against available implementation and artifacts within Spec-Driven Development. Inspect code, run tests, build and type checks, and report findings, limitations, and next steps without mutating code.

This skill automatically scans all defined user and project skills (from SKILL.md files) to create a comprehensive, centralized index. It manages skill paths, triggers, descriptions, and scopes, ensuring that downstream agents and delegators always have an up-to-date source of truth for available functionalities. It is crucial for maintaining system integrity and avoiding redundant skill definitions.

A rigorous framework for triaging software defects, managing technical debt, and designing systemic fixes. This methodology mandates classifying issues by root class and implementing clustered, minimized solutions, rather than applying superficial patches. It guides developers to prevent over-engineering and ensure that system improvements are durable, verifiable, and maintainable.

A structured skill embodying Tang Jia San Shao's web fiction creation approach, covering daily updating discipline, cultivation systems with quantifiable levels, team-based battle narratives, IP lifecycle planning via six waves, and emotional anchoring from real-life experiences. Suitable for designing long-running fantasy series, managing consistent writing output, and planning cross-media IP expansion.

Plan commits as reviewable work units to improve code quality and review efficiency. This skill helps split large features into manageable chunks, prepare commits before opening PRs, and maintain tests and documentation alongside code changes. It ensures each commit represents a clear deliverable behavior, reducing reviewer cognitive load and supporting chained PRs for larger changes.

This skill compiles user creative intent into executable image and video prompts for AI models. It specializes in character consistency, cinematic storyboards, and reference asset mapping for R2V/I2V/T2V tasks. It ensures visual contracts, narrative flow, and production-ready specifications without replacing model capabilities.