Diego Rodrigues de Sa e Souza

AgentDB Persistent Memory Patterns operates on 3 fundamental principles:

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AgentDB Reinforcement Learning Training operates on 3 fundamental principles:

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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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Use this skill in the scenario of intelligent agent application development.

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Asistente especializado en investigación académica, redacción científica, ACD, metodología cualitativa y análisis de datos con prevención de plagio

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Orchestrate Gemini CLI agent teams for parallel multi-agent collaboration

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AgentDB Vector Search Optimization operates on 3 fundamental principles:

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Comprehensive templates, patterns, and best practices for creating Claude Code subagents and skills. Use when building new agents/skills or need reference examples for proper structure and formatting.

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Create and manage AI agent skills following best practices. Use when creating new skills, optimizing context, designing multi-agent systems, or implementing progressive disclosure patterns.

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Define tools for the support agent. Use when adding new capabilities like refund processing, license transfer, knowledge lookup, or any agent action.

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Economic identity and reputation system for autonomous agents on Base.

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Build multi-agent AI workflows with orchestration, tool use, and state management

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Run prompt with OpenAI or Gemini provider via agent CLI

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Expert in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous workflows.

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Extract and display the final message from a Claude agent JSONL file. Use when the user wants to see an agent report, view agent output, extract agent results, check what an agent produced, or read the final response from a subagent. Triggers on requests like "show me agent report", "what did agent X produce", "extract agent output", "view agent results", or "get the report from agent ad42ecb".

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Expert research analyst specializing in comprehensive information gathering, synthesis, and insight generation. Masters research methodologies, data analysis, and report creation with focus on delivering actionable intelligence that drives informed decision-making.

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North star guidance for the agent-resources project. Use this skill to understand project context, get inspiration for development decisions, and resolve uncertainty about feature priorities or design choices. Reference when asking 'why does this project exist?' or 'what should we optimize for?'

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Get external agent review and feedback. Routes Anthropic models through Claude Agent SDK (uses local subscription) and other models through OpenRouter API. Use for code review, architecture feedback, or any external consultation.

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Run section orchestrators to coordinate multi-component workflows. Use when starting work on a section.

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Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration. Use when: the task directly matches context manager responsibilities within plugin agent-orchestration. Do not use when: a more specific framework or task-focused skill is clearly a better match.

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Optimize agent instruction files by extracting sections into separate files and referencing them. Reduces context size while preserving information.

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Create new AgentOps skills via interactive interview. Supports from-scratch and clone modes with tiered complexity.

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Create/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.

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Interactive code review for agent iterations. Captures comments, tracks resolution status, and integrates with git diffs.

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