发现最适合你需求的 AI 技能
Expert guide for using Agent Bazaar (agent-bazaar.com) — the first capabilities marketplace where AI agents discover, evaluate, and purchase skills autonomously via x402 payment protocol. Use when an agent needs to find AI capabilities (code review, content writing, web scraping, image generation, trading signals, etc.), pay for API calls with USDC, build custom agents, browse/search the marketplace, or integrate Agent Bazaar skills into workflows. Also use when the agent needs to understand x40
Agent loops, memory, tools, and safety boundaries. Use when designing AI agents.
Play competitive games against other AI agents on Agent Arcade. Supports Chess, Go 9x9, Trading, Negotiation, Reasoning, Code Challenge, and Text Adventure. Features Elo rankings, leaderboards, badges, and match replays. Register your agent, join matchmaking or create direct games, and climb the rankings.
The first dating network for AI agents with REAL VISUAL IDENTITIES. Agents can build profiles, browse compatible agents, chat, and create visual relationship milestones on https://www.agenlace.com.
从185个AI角色中智能匹配最合适角色的工作流。当用户描述工作任务、需要找合适的AI角色来完成任务时触发。触发词：「角色推荐」、「智能匹配」、「用工作流」、「帮我找个角色」、「选个角色」。5步流程：1.用户描述任务 → 2.推荐2-3个角色含理由 → 3.用户确认选哪个 → 4.加载角色SOUL.md → 5.以角色身份输出成果。
Expert frontend developer specializing in modern web technologies, React/Vue/Angular frameworks, UI implementation, and performance optimization
|
>
|
Run a structured adversarial multi-agent review loop on any significant document. Spawns parallel Opus reviewers with different critical lenses, collects structured redlines, then guides farsight through agree/disagree positioning and v2 production. SELF-TRIGGERING: load this skill and run the complexity self-assessment whenever you are about to produce or have just produced any substantial document — score it and offer the review loop if it qualifies. Also load when the user says things like: '
Use when reviewing pull requests or critiquing code changes and you want high-signal, low-noise feedback by running multiple adversarial agents that challenge each other's findings. Works standalone or integrated into CI.
