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Found 13,205 Skills
Manage concentrated liquidity (CLMM) positions on DEXs like Meteora and Raydium. Create, monitor, and rebalance LP positions automatically.
NEAR AI agent development and integration. Use when building AI agents on NEAR, integrating AI models, creating agent workflows, or implementing AI-powered dApps on NEAR Protocol.
Guidelines for creating AI agent skills. Use when writing new skills, documenting coding patterns, or reviewing skill files. Triggers when creating or modifying files in the skills/ directory.
Guides architects on when and how to use goal-seeking agents as a design pattern. This skill helps evaluate whether autonomous agents are appropriate for a given problem, how to structure their objectives, integrate with goal_agent_generator, and reference real amplihack examples like AKS SRE automation, CI diagnostics, pre-commit workflows, and fix-agent pattern matching.
GoPlus AgentGuard — AI agent security guard. Automatically blocks dangerous commands, prevents data leaks, and protects secrets. Use when reviewing third-party code, auditing skills, checking for vulnerabilities, evaluating action safety, or viewing security logs.
Request interactive code review from users using the agent-review CLI tool. Automatically captures user feedback on code changes.
Use this skill to analyze a brand from their website before creating content. Triggers: "analyze brand", "research brand", "brand guidelines", "brand profile", "understand brand", "brand colors", "brand voice", "before creating content for" Extracts: colors, typography, voice/tone, products, audience, competitive positioning. Outputs a reusable brand_profile.json that producer skills can use.
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
Audit and annotate an AI-generated implementation plan for requirements traceability, YAGNI compliance, and assumption risks. Use when reviewing, validating, or auditing an implementation plan or design proposal produced by an AI agent.
Use when writing or refactoring Ruby code that integrates Claude Code via the claude-agent-sdk gem (ClaudeAgentSDK.query, ClaudeAgentSDK::Client, streaming input, ClaudeAgentOptions configuration, tools/permissions, MCP servers, hooks, structured output, budgets, sandboxing, session resumption/rewind, and Rails patterns like jobs or ActionCable).
Design agent-native applications on Eve Horizon. Apply parity, granularity, composability, and emergent capability principles to make apps that agents can build, operate, and extend naturally.