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Found 131 Skills
Build AI agents with Strands Agents SDK. Use when developing model-agnostic agents, implementing ReAct patterns, creating multi-agent systems, or building production agents on AWS. Triggers on Strands, Strands SDK, model-agnostic agent, ReAct agent.
Meta-skill for understanding and customizing Mindfold Trellis - the AI workflow system for Claude Code and Cursor. This skill documents the ORIGINAL Trellis system design. When users customize their Trellis installation, modifications should be recorded in a project-local `trellis-local` skill, NOT in this meta-skill. Use this skill when: (1) understanding Trellis architecture, (2) customizing Trellis workflows, (3) adding commands/agents/hooks, (4) troubleshooting issues, or (5) adapting Trellis to specific projects.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Orchestrates multi-agent AI systems with task delegation, agent communication, shared memory, and workflow coordination. Use when users request "multi-agent system", "agent orchestration", "AI agents", "agent coordination", or "autonomous agents".
Add Agent Swarm (Teams) support to Telegram. Each subagent gets its own bot identity in the group. Requires Telegram channel to be set up first (use /add-telegram). Triggers on "agent swarm", "agent teams telegram", "telegram swarm", "bot pool".
A-share multi-agent AI investment research and analysis tool - 15 AI analysts collaborate to complete technical analysis, fundamental analysis, market sentiment judgment, capital flow tracking (northbound capital/main capital), macroeconomic analysis and game theory deduction, and output structured trading suggestions and risk assessment. Supports Shanghai and Shenzhen A-share stock codes and Chinese names. Multi-agent AI stock analysis for China A-shares. 15 specialized analysts collaborate across technical analysis, fundamental analysis, sentiment analysis, smart money flow tracking, macro economics, and game theory to deliver structured buy/sell/hold recommendations with risk assessment.
This skill should be used when the user asks to "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration. Part of the context engineering skill suite — also activates when the user mentions "context engineering" or "context-engineering" in the context of belief-based agent reasoning.
Multi-agent discussion rooms — debate or poll a problem from multiple perspectives. Standalone or invoked by other skills as a sub-routine. Mode=debate: N agents argue in rounds, converge. Mode=poll: N agents independently analyze, aggregate by consensus. Not for implementation (use system-architecture). Not for verification (use review-chain). For clarifying requirements first, see discover. For decomposing work after a decision, see task-breakdown.
Spawn specialized sub-agents with context handoff for complex multi-phase tasks. Enables expertise delegation within a session with automatic context merging and depth limiting to prevent infinite loops.
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with meta-judge evaluation specifications and multi-agent evaluation
Agent Workflow Designer