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Found 2,307 Skills
[Tooling & Meta] Claude Code CLI setup, configuration, troubleshooting, and feature guidance. Triggers on claude code setup, hook not firing, MCP connection, context limit, skill creation, slash command setup.
Use the ctx7 CLI to fetch library documentation, manage AI coding skills, and configure Context7 MCP. Activate when the user mentions "ctx7" or "context7", needs current docs for any library, wants to install/search/generate skills, or needs to set up Context7 for their AI coding agent.
Exchange listing tracker. Use this skill whenever the user asks about exchange listing, delisting, or maintenance announcements. Trigger phrases include: any new coins listed recently, what did Binance list, new listings, delisted. MCP tools: news_feed_get_exchange_announcements, info_coin_get_coin_info, info_marketsnapshot_get_market_snapshot.
General web search and content extraction skill. It supports multi-source parallel search (WebSearch, MCP search tools, ctx7, agent-browser), web page main content extraction (defuddle/WebFetch) and structured article analysis. This skill is used when users need to search for information, research topics, find materials, obtain web content, read articles, or analyze web pages. Trigger scenarios include: search, research, investigation, fetch, check for me, help me find, read this link, analyze this article. Even if the user doesn't explicitly say "search", this skill should be triggered as long as it involves information acquisition and web content processing.
Review existing Perses dashboards for quality: fetch via MCP or API, analyze panel layout, query efficiency, variable usage, datasource configuration. Generate improvement report. Optional --fix mode. 4-phase pipeline: FETCH, ANALYZE, REPORT, FIX. Use for "review perses dashboard", "audit dashboard", "perses dashboard quality". Do NOT use for creating new dashboards (use perses-dashboard-create).
Use after analyze-and-document has generated CLAUDE.md for an AI Studio project. Installs project-level Claude Code configuration — rules, skills, settings, and optionally agents, hooks, and MCP servers — into the .claude/ directory so that all future sessions have the right guardrails and workflows.
Analysis of Lanhu design drafts and Axure prototypes. Directly read prototype pages, design drafts, and slice resources of Lanhu projects via lanhu MCP Server. Trigger scenarios: - Need to obtain Axure prototype pages from Lanhu for requirement analysis - Need to view Lanhu UI design drafts and design parameters - Need to extract slice resources from Lanhu design drafts - Need to collaborate via Lanhu team message board - Need to parse Lanhu invitation links Trigger words: Lanhu, lanhu, design draft, prototype, Lanhu link, design image, slice
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for prompt-injection, retrieval poisoning, memory contamination, planner drift, MCP or tool-boundary abuse, and agent exfiltration challenges. Use when the user asks to analyze prompt injection, retrieval poisoning, memory contamination, planner drift, tool-argument corruption, or secret exposure caused by an agent chain. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Configure, deploy, and manage Senpi Trading Runtime (OpenClaw plugin @senpi-ai/runtime) for automated on-chain position tracking with DSL trailing stop-loss protection. Use when a user needs to create or modify runtime YAML files, configure DSL (Dynamic Stop-Loss) exit engine parameters (phases, tiers, time-based cuts), set up the position_tracker scanner to monitor a wallet's positions on Hyperliquid, install/list/delete runtimes via CLI, or inspect DSL-tracked positions. The runtime does NOT create strategy wallets; create/get the strategy wallet via Senpi MCP first, then link that existing wallet in runtime YAML. Triggers on mentions of senpi, Senpi runtime, DSL exit, stop-loss tiers, position tracker, trailing stop, openclaw senpi, dsl_preset, or strategy YAML configuration."
Vector search indexing and querying workflows using MCP Vector Search, including setup, reindexing, auto-index strategies, and MCP integration.
昇腾（Ascend）推理生态开源代码仓库智能问答专家旨在为 vLLM、vLLM-Ascend、MindIE-LLM、MindIE-SD、MindIE-Motor、MindIE-Turbo 以及 msModelSlim (MindStudio-ModelSlim) 等仓库提供专家级且易于理解的解释。在处理昇腾（Ascend）推理生态相关项目的用户询问时，务必触发此技能（Skill），可解答使用方法、部署流程、支持模型、支持特性、系统架构、配置管理、调试、测试、故障排查、性能优化、定制开发、源码解析以及其他技术问题。支持中英文双语回复，并可借助 deepwiki MCP 工具检索仓库知识库，生成具备上下文感知且基于证据的回答。Ascend inference ecosystem open-source code repository intelligent question-and-answer (Q&A) expert. Provide expert-level yet comprehensible explanations for repositories such as vLLM, vLLM-Ascend, MindIE-LLM, MindIE-SD, MindIE-Motor, MindIE-Turbo, and msModelSlim (MindStudio-ModelSlim). Use this skill when addressing user inquiries related to these Ascend inference ecosystem projects, including topics such as usage, deployment process, supported models, supported features, system architecture, configuration management, debugging, testing, troubleshooting, performance optimization, custom development, source code analysis, and any other technical issues about these projects. Support responses in both Chinese and English. Use deepwiki MCP tools to query repository knowledge bases and generate context-aware, evidence-based responses.
Operate Notion Public API through UXC with a curated OpenAPI schema for search, block traversal, page reads, content writes, and data source/database inspection. Use when tasks need recursive reads or structured writes that Notion MCP does not expose directly.