Loading...
Loading...
Found 6,201 Skills
Turn a weekly changelog .md into a finished branded changelog video (square 1080, ~45-60s, Annie VO, animated brand background, mock-UI visualizations, lowkey captions). Use when the user provides a changelog/digest markdown and wants the weekly video, or says "changelog video". Self-contained — fonts, background, lexicon, and scripts ship in this skill.
Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.
Only to be triggered by explicit /parallel-task commands.
Build and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.
GitHub Copilot Coding Agent 자동화. 이슈에 ai-copilot 라벨 부착 → GitHub Actions가 GraphQL로 Copilot에 자동 할당 → Copilot이 Draft PR 생성. 원클릭 이슈-to-PR 파이프라인.
Self-referential completion loop for AI CLI tools. Re-runs the agent on the same task across turns with fresh context each iteration, until the completion promise is detected or max iterations is reached.
AI 코딩 에이전트를 시각적 Kanban 보드에서 관리. To Do→In Progress→Review→Done 흐름으로 병렬 에이전트 실행, git worktree 자동 격리, GitHub PR 자동 생성.
Standardize and validate SKILL.md files to match the project specification. Use when creating new skills, converting existing skills to standard format, or validating skill file structure. Handles section heading conversion, frontmatter standardization, and missing section detection.
Fast headless browser CLI for AI agents. Supports deterministic element selection via accessibility tree snapshots and refs (@e1, @e2).
AI 에이전트와 협업하는 에이전틱 개발의 범용 원칙. 분해정복, 컨텍스트 관리, 추상화 수준 선택, 자동화 철학을 정의. 모든 AI 코딩 도구에 적용 가능.
AI 에이전트 협업 개발의 핵심 원칙. 분해정복, 컨텍스트 관리, 추상화 수준 선택, 자동화 철학, 검증 회고를 정의. 모든 AI 에이전트 사용 시 최적의 협업 패턴 적용.
Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.