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.
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This skill should be used when building AI agents using prompt-native architecture where features are defined in prompts, not code. Use it when creating autonomous agents, designing MCP servers, implementing self-modifying systems, or adopting the "trust the agent's intelligence" philosophy.
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Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction.
日本語の概要は準備中です。原文の説明を表示しています。
Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Make an out-of-session agent AgentOps-native via skills + ao CLI + CI, not hooks.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
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Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.
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Conduct structured interviews with the user. Use when multiple decisions need user input: ask ONE question at a time, wait for response, record answer, then proceed to next question.
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Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
日本語の概要は準備中です。原文の説明を表示しています。
Agent skill for multi-repo-swarm - invoke with $agent-multi-repo-swarm
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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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Agent skill for matrix-optimizer - invoke with $agent-matrix-optimizer
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Complete operational workflow for implementer agents (Codex, Gemini, etc.) making code changes and writing tests. Defines the Code Change Loop, Test Writing Loop, and Issue Filing process with circuit breakers, severity levels, and escalation rules. Includes bundled scripts for specialist-review (code review) and test-review-request (test audit) that delegate to Claude CLI. Use this skill when starting any implementation task.
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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.
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Without identity infrastructure, every Claude Code session starts from zero. The agent has no name, no remembered preferences, no sense of who it works with or what it has learned. Context compaction erases everything mid-session. This skill fixes that — no external tools required.
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Register and manage on-chain AI agent identity via ERC-8004.
日本語の概要は準備中です。原文の説明を表示しています。
Agent skill for dev-backend-api - invoke with $agent-dev-backend-api
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Use when creating expert agents. Generates agent.md with frontmatter, hooks, required sections, and skill references.
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Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
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Agent skill for coder - invoke with $agent-coder
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Agent skill for consensus-coordinator - invoke with $agent-consensus-coordinator
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Agent Context Isolation
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "write a subagent", "generate agent definition", "add agent to plugin", "write agent frontmatter", "create autonomous agent", "build subagent", needs agent structure guidance, YAML frontmatter configuration, invocation criteria with examples, or wants to add specialized subagents to Claude Code plugins with proper capabilities lists and tool access definitions.
日本語の概要は準備中です。原文の説明を表示しています。