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Found 24 Skills
Core standards for all GitHub workflow agents. Covers authentication, smart defaults, repository discovery, dual MD+HTML output, screen-reader-compliant HTML accessibility standards, safety rules, progress announcements, parallel execution, and output quality. Apply when building any GitHub workflow agent - issues, PRs, briefings, analytics, community reports, team management.
An intelligent assistant designed for long-form online novel creation, supporting full-process management from setting generation to main text writing, including intelligent quality control and state synchronization. (Yunshu Optimized)
Interactive guide for creating new agent skills from scratch. Use this skill when the user wants to create a skill, write a SKILL.md, package a skill folder, or convert an existing workflow into a reusable skill. Also trigger when the user mentions "create skill", "new skill", "SKILL.md", "teach the agent", or wants to standardize a repeatable process into a skill.
Clarify scope through dialogue, surface key decisions and open questions. Use before planning.
Standardize the article editing process to ensure clear modification scope, trackable progress, and documented changes. Use this skill when the user says "edit article", "revise article", "adjust content", or "modify this piece".
Plan and file goals and feature issues through conversation. Use when the user wants to create goals, plan features, file issues, or discuss what to build next.
Conduct targeted code exploration on a repository, and document the process of "Asking Questions → Reading Code → Reaching Conclusions" as searchable evidence for direct reuse when similar questions arise next time. There are three types: question (investigate code around a specific problem and provide conclusions), module-overview (organize the structure, boundaries, entry points, and dependencies of a module), spike (conduct lightweight technical exploration of multiple possible directions without making final decisions). Trigger scenarios: When users say "Let's explore first", "How is X implemented in this repository", "Quickly get familiar with this module", "Archive the exploration results". For the distinction from learning / tricks / decisions, refer to the root skill `easysdd`.
驗證規格檔案的完整性與一致性，確保所有必要的規格元素都已定義且符合標準格式。
Directory convention, numbering system, and workflow for multi-session implementation plans. Follow when creating phased feature plans that span multiple sessions.
Enter this sub-process when conducting code optimization — handle tasks where 'behavior remains unchanged, structure changes' (structure / performance / readability). Shift single-module internal optimization from 'AI random refactoring' to 'first scan to generate a checklist, confirm each item with the user, execute step-by-step according to the method library, and require manual approval for each step'. Trigger scenarios: Users mention phrases like 'optimize it / refactor / rewrite / split it / poor performance / code is too long' without any accompanying behavior changes. Do not handle new requirements (route to feature), bugs (route to issue), or cross-module architecture restructuring (route to architecture + decisions).
Use when partner provides a complete implementation plan to execute in controlled batches with review checkpoints - loads plan, reviews critically, executes tasks in batches, reports for review between batches
Proposal-first development workflow with commit hygiene and decision authority rules. Enforces: propose before modifying, atomic commits, no force flags, warnings-as-errors. Use for any project where AI agents are primary developers and need guardrails.