Diego Rodrigues de Sa e Souza

Spawn Agentica multi-agent patterns

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Designing features for the "Action Era" that are AI-accessible by default

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Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration

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Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.

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Generate a rules file for any AI coding agent. Interactive setup that scans installed skills, asks about workflow preferences, and writes a tailored instruction file for Claude Code, Cursor, Windsurf, Copilot, Gemini, Roo Code, or Amp. Supports global (user-level), project team-shared, and project dev-specific scopes.

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AI agents as force multipliers for quality work. Core skill for all 19 QE agents using PACT principles.

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Build functional software prototypes and MVPs without deep technical skills by using AI agents as "developers in your pocket." Use this skill when you need to validate a new product concept, build custom back-office tools (e.g., a real estate data manager), or create high-fidelity demos to unblock engineering roadmaps.

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Patterns for multi-agent coordination, task decomposition, handoffs, and workflow orchestration. Best practices for building and managing agent systems.

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Provides the "how-to" for workflow / task execution orchestration. Defines methods for planning multi-phase task/workflows, implementing them through agent delegation, and managing artifacts.

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Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.

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Write effective AGENTS.md files for AI coding agents.

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Salesforce Agentforce AI agents and autonomous automation (2025)

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Reference guide for Agentica multi-agent infrastructure APIs

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AI assistant for creating clear, actionable task descriptions for GitHub Copilot agents

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Assess agentic layer maturity using the 12-grade classification system (Class 1-3). Use when evaluating codebase readiness, identifying next upgrade steps, or tracking progress toward the Codebase Singularity.

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Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

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AgentHero AI - Hierarchical multi-agent orchestration system with PM coordination, file-based state management, and interactive menu interface. Use when managing complex multi-agent workflows, coordinating parallel sub-agents, or organizing large project tasks with multiple specialists. All created agents use aghero- prefix.

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Security best practices and guidelines for the Jarvy CLI codebase - a cross-platform development environment provisioning tool that executes system commands with elevated privileges

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Agentica server + Claude proxy setup - architecture, startup sequence, debugging

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Dependency management guidelines for Jarvy - crate selection criteria, feature flag best practices, version management, security auditing with cargo-audit and cargo-deny.

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Interactive prompt engineering coach that elevates vague prompts through Socratic dialogue, multiple transformation styles, and guided learning. Use when improving prompts, learning agentic engineering, or wanting coached guidance rather than automated transformation. NEVER auto-executes - always displays and asks first.

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Design and implement agentic AI workflows and patterns. Covers ReAct, planning agents, tool use, memory systems, and multi-agent orchestration. Use when building autonomous AI agents, implementing complex task automation, or designing intelligent workflow systems.

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Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity

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Guide for using and supporting the AGENTS.md standard in VS Code. Use this when asked about AGENTS.md, custom instructions, or repo-level AI agent configuration.

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