Diego Rodrigues de Sa e Souza

Launches specialized Claude agents for targeted tasks. Analyzes requirements, selects appropriate agent, and executes with optimized configuration.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert knowledge synthesizer specializing in extracting insights from multi-agent interactions, identifying patterns, and building collective intelligence. Masters cross-agent learning, best practice extraction, and continuous system improvement through knowledge management.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Agent invocation syntax and boundary rules

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill to create or update the root AGENTS.md file to register AgenticDev skills for AI agent discovery. Triggers include "register AgenticDev", "update AGENTS.md", "setup agent guide", or initializing a new project.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Initialize or improve AGENTS.md files that define how coding agents operate in a repo. Use when asked to set up or replace an agent init command (Codex, Claude), standardize multi-agent behavior, or audit an existing AGENTS.md for clarity, commands, boundaries, and repo-specific context. For Claude Code, also create CLAUDE.md as a symlink to AGENTS.md.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Self-improvement loop for multi-agent workflows. Diagnose failures, improve tool descriptions, and learn from success/failure patterns.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Agent parameter passing, memory files, and data handoffs between agents

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use these when you want low-noise lint/test output (good for LLM/CI logs) while staying aligned with repo policy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Visual context analyzer for AI agents. Provides screenshots, accessibility scans, DOM snapshots, and element descriptions for web pages. Use when you need to see what a web page looks like, analyze accessibility issues, inspect DOM structure, or get detailed element information. Triggers on requests like "take a screenshot", "check accessibility", "what does this page look like", "analyze the UI", "inspect this element", or any visual/UI analysis task.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Upload tailored resume to cloud or attach to user session. Handles final formatting and delivery.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Deterministic custom subagent selection helper. Use when you need a reproducible, auditable decision on which custom subagents to activate for a user query (runs scripts/agent_evaluator.py).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Evaluate agent performance using a structured scoring rubric

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any SDK.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Standardized reference documentation section structure for agents - project guidance, conventions, related agents, and Skills. Use when implementing or updating agent documentation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create and optimize Claude Code subagent files (.claude/agents/*.md) following official best practices. Use when user asks to create a subagent, agent file, custom agent, or needs help structuring agent files with YAML frontmatter.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when architecting new Claude Code agents following Anthropic best practices. Guides through YAML frontmatter creation, agent structure definition, role boundaries, and validation. Critical for creating minimal agent files (~150 lines) with proper skill invocations. Examples: <example>Context: User wants to create a new agent for security auditing user: "Create a security-auditor agent" assistant: "I'll use the agent-creator skill to build this agent following Anthropic best practices" <commentary>New agent creation requires the agent-creator skill to ensure proper structure and YAML frontmatter.</commentary></example> <example>Context: Existing agent file is too verbose and needs refactoring user: "The architect agent is 2000 lines, refactor it to minimal structure" assistant: "I'll use the agent-creator skill to refactor this into a minimal ~150 line agent with a separate skill file" <commentary>Agent refactoring requires the agent-creator skill to separate identity from technical procedures.</commentary></example>

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Used to create a new agent. Used when a user wants to create a new agent

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Check agent configuration coverage across hierarchy levels and phases. Use to ensure complete agent system coverage.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Agent assignment matrix, blocker escalation, and TDM coordination patterns. Use when assigning work to specialists, managing blockers, or coordinating multi-agent workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert context manager specializing in information storage, retrieval, and synchronization across multi-agent systems. Masters state management, version control, and data lifecycle with focus on ensuring consistency, accessibility, and performance at scale.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.