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Found 11,954 Skills
Multi-path parallel product analysis with cross-model test-time compute scaling. Spawns parallel agents (Claude Code agent teams + Codex CLI) to explore product from multiple perspectives, then synthesizes findings into actionable optimization plans. Can invoke competitors-analysis for competitive benchmarking. Use when "product audit", "self-review", "发布前审查", "产品分析", "analyze our product", "UX audit", or "信息架构审计".
Ethereum development knowledge for AI agents — from idea to deployed dApp. Fetch real-time docs on gas costs, Solidity patterns, Scaffold-ETH 2, Layer 2s, DeFi composability, security, testing, and production deployment. Use when: (1) building any Ethereum or EVM dApp, (2) writing or reviewing Solidity contracts, (3) deploying to mainnet or L2s, (4) the user asks about gas, tokens, wallets, or smart contracts, (5) any web3/blockchain/onchain development task. NOT for: trading, price checking, or portfolio management — use a trading skill for those.
Hypothesis-driven deep research swarm. Spawns specialist sub-agents to investigate a task across codebase patterns, web sources, MCP tools, installed skills, and project dependencies — with evidence grading and adversarial challenge. Activates on: research, investigate, discover, deep research, how should I, what's the best way, explore options, analyze approaches, scout, prior art, feasibility.
Browser automation for AI agents. Use when the user needs to interact with websites, navigate pages, fill forms, click buttons, take screenshots, extract data, test web apps, or automate any browser task. Triggers include "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data", "test this web app", "login to a site", or any task requiring programmatic web interaction.
The complete AI web agency toolkit. One skill to run a full client website project — from intake to design to build to deploy. Orchestrates sub-skills and sub-agents for fast, high-quality delivery.
Save current session state to Apple Notes at session end. Triggers on handoff, bye, done, wrap up, or Chinese equivalents. Multi-agent architecture with private (per-agent) and shared (cross-agent) notes. Three-tier memory: Active, Archive, Long-term. Use whenever the user wants to end a session, save progress, or says anything indicating they are done for now.
Manages Atlassian Jira and Confluence via the Rovo MCP Server. Handles MCP setup, OAuth authentication, and troubleshooting. Runs agentic project management: Confluence plans, Jira Epics with child tickets, agent team coordination, and resuming interrupted work from Jira state. Supports uploading images/attachments to Confluence pages via REST API. Reads and writes Confluence page comments (footer, inline, reply threads). Creates git branches linked to Jira tickets (GitHub and Bitbucket). Use this skill whenever the user mentions Jira, Confluence, Atlassian, tickets, epics, sprints, project boards, wiki pages, or Confluence spaces. Also trigger when the user wants to plan a project, break work into tasks, track progress, resume interrupted work, upload images to wiki pages, manage comments on Confluence pages, or create git branches linked to tickets — even if they don't mention Atlassian by name.
Perform complex, long-running research tasks using Gemini Deep Research Agent. Use when asked to research topics requiring multi-source synthesis, competitive analysis, market research, or comprehensive technical investigations that benefit from systematic web search and analysis.
Autonomous workflow execution pipeline with CSV wave engine. Session discovery → plan validation → IMPL-*.json → CSV conversion → wave execution via spawn_agents_on_csv → results sync. Task JSONs remain the rich data source; CSV is brief + execution state.
Requirement planning to wave-based CSV execution pipeline. Decomposes requirement into dependency-sorted CSV tasks, computes execution waves, runs wave-by-wave via spawn_agents_on_csv with cross-wave context propagation.
Use when tasks require all-in-one multimodal understanding or generation with Alibaba Cloud Model Studio Qwen Omni models, including image-plus-audio interaction, voice assistants, and realtime multimodal agents.
Audit skill SKILL.md files for compliance with the agentskills.io specification. Checks frontmatter fields (name, description, compatibility, metadata, argument-hint) and metadata sub-fields (author, scope, confirms). Use when adding new skills, reviewing skill quality, or ensuring all skills follow the spec. Triggers: "audit skills", "check skill spec", "skill compliance", "are my skills up to spec", "/claude-skill-spec-audit".