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Found 5,792 Skills
Audit AI agent skills for security vulnerabilities. Use when scanning installed skills against the OWASP Agentic Skills Top 10, checking skills before running them, gating CI/CD on skill safety, or generating audit reports (text, JSON, SARIF, HTML) for stakeholders.
Dispatch implementation tasks to agent teammates in git worktrees. Triggers: 'delegate', 'dispatch tasks', 'assign work', or /delegate. Spawns teammates, creates worktrees, monitors progress. Supports --fixes flag. Do NOT use for single-file changes or polish-track refactors.
Spin up a single agent as an advisor — second opinion on the current task. Use when the user says "advisor", "second opinion", "what does X think", or wants an outside take without delegating the work itself.
Use when the user asks to design multi-agent systems, create agent architectures, define agent communication patterns, or build autonomous agent workflows.
Full-Process Web Novel/Story World Builder, suitable for users' overall novel writing needs such as saying "I want to write a novel", "Write a web novel", "Create a novel from scratch", "Help me write a novel of XX genre", "I want to write a novel", "Give me the entire novel creation process", "Auto-write a novel", "One-stop novel creation service", "Help me finish a novel", "How to write a novel with only an idea", etc. It automatically coordinates the full process of topic selection, outline design, writing, review, and polishing. Even if you only have a rough idea, it can help you complete a full work from 0 to 1 and build a unified story world. **All chapter-level operations are processed in parallel by sub-Agents, with each Agent responsible for a maximum of 3 chapters**
Make and receive private payments on Solana via VeilPay. Use when an agent needs to send funds without an on-chain link between sender and recipient, generate shareable payment links, claim incoming payments, perform confidential transfers, or query encrypted balances. Powered by the Umbra ZK shielded pool on Solana mainnet.
Manages Neo4j Aura Agents via the v2beta1 REST API — create, list, get, update, delete, and invoke Aura agents backed by an AuraDB instance. Use when configuring Aura Agent tools (CypherTemplate, SimilaritySearch, Text2Cypher), setting system prompts, deploying agents to REST or MCP endpoints, or invoking agents with natural language queries. Covers OAuth2 auth, organization/project scoping, tool parameter schemas, and InvokeAgentResponse format. Does NOT cover AuraDB instance provisioning — use neo4j-aura-provisioning-skill. Does NOT cover vector index creation — use neo4j-vector-index-skill.
Optimize and structure context for agents and LLMs by reducing noise, prioritizing relevance, organizing memory, defining constraints, and managing token budgets.
Triage GitHub issues by applying type, effort, priority, and area labels. Runs in an isolated context to avoid polluting the main conversation with issue details. Delegates to a specialized triage agent with label validation hooks.
Extract a validated learning from the current session, store it in the central agent learnings file, and sync the resulting Learnings section into the agent definitions used by the supported CLIs. User-only maintenance workflow for durable agent guidance.
Create implementation task plans in `_/local-plans/<plan-name>.md`. First investigate the codebase using the Explore Agent, then document it in verifiable granularity and parallel-executable units, following the standard format (Background & Purpose, Current Status, Design, File Structure Tree, Implementation Steps, Verification Methods) that can be validated by the plan-verifier Agent. Used for requests like "Make a plan", "Design", "Task decomposition", "Think about implementation approach". plan, planning, design, implementation plan, task decomposition, create-plan
Conventional Commits 1.0.0 + 베스트 프랙티스 워크플로 (diff → staging → type 결정 → secrets blocklist → 사전 체크리스트) + 5 founding principle (atomic / leaves-repo-green / why-over-what / imperative / searchable) + project dialect scaffolding. 커밋을 4 reader (`git log` 스캐너 / `git blame` 추적자 / `git bisect` 사냥꾼 / AI agent — `/clear` 컨텍스트 복원 / PR 리뷰 / changelog 생성 / NL 질의)에게 동시에 도움되는 영구 history로 다룸. 본 파일은 한국어 prose 변형. 룰 자체 (영문 default body, lowercase summary, imperative mood, atomic / why-over-what 등 §0 전 원칙)는 영문 SKILL.md와 동일 — 변형 무관. ALWAYS trigger 조건은 영문 SKILL.md frontmatter §ALWAYS와 동일. Triggers (multi-lingual): EN: commit, git commit, stage, commit message, breaking change, conventional commits, revert, fixup, amend, cherry-pick, changelog KO: 커밋, 깃 커밋, 스테이지, 커밋 메시지, 커밋 룰, 컨벤셔널 커밋, 리버트, 되돌리기, 어맨드, 커밋 컨벤션, 커밋 메시지 검토 JA: コミット, git コミット, ステージ, コミットメッセージ, ブレーキング チェンジ, リバート, アメンド ZH: 提交, git 提交, 暂存, 提交信息, 提交消息, 重大变更, 回滚, 修订 Audience: 한국어를 모국어로 쓰는 개발자. §0 founding principle을 한국어로 먼저 잡고 싶은 사용자에게 적합. §1-§14 룰 자체는 영문 SKILL.md를 정본으로 참조 — 본 변형이 룰을 새로 정의하지 않음.