7,589 件 ・ 関連度順
概要と使いどころ
Scan the current chat session for durable learnings (clarifications, corrections, decisions, pitfalls) and update .agent/memory.md. Use after critical review and before concluding work.
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。
Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.
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。
Debug and troubleshoot ElevenLabs conversational AI agents and Twilio calls. Use when diagnosing agent issues, analyzing failed calls, troubleshooting audio problems, investigating conversation breakdowns, reviewing error logs, or optimizing underperforming agents. Includes transcript analysis, error diagnosis, and performance troubleshooting.
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。
Check and process messages from autonomous AILANG agents. Use when starting a session, after agent handoffs, or when checking for completion notifications.
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。
Expert LLM architect specializing in large language model architecture, deployment, and optimization. Masters LLM system design, fine-tuning strategies, and production serving with focus on building scalable, efficient, and safe LLM applications.
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。
Collect and synthesize opinions from multiple AI agents. Use when users say "summon the council", "ask other AIs", or want multiple AI perspectives on a question.
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。
Generate visual hierarchy diagrams of agent system showing levels and delegation. Use for documentation or onboarding.
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。
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.
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 assignment matrix, blocker escalation, and TDM coordination patterns. Use when assigning work to specialists, managing blockers, or coordinating multi-agent workflows.
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。
Design AI agents with recommended patterns and architectures
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。
交互式生成 GitHub Copilot agents.md 文件的工作流。当用户请求创建代理、构建自定义 Copilot 代理、生成 agents.md 或需要帮助配置 GitHub Copilot 自定义代理时使用。触发短语包括"创建代理"、"生成 agent.md"、"做一个文档代理"、"生成测试代理"等涉及 GitHub Copilot 代理配置的请求。
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。
Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.
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。
Check agent configuration coverage across hierarchy levels and phases. Use to ensure complete agent system coverage.
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 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.
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。
Launches specialized Claude agents for targeted tasks. Analyzes requirements, selects appropriate agent, and executes with optimized configuration.
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。
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
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", "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.
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。
Expert legal advisor specializing in technology law, compliance, and risk mitigation. Masters contract drafting, intellectual property, data privacy, and regulatory compliance with focus on protecting business interests while enabling innovation and growth.
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。
Discovers all Claude Code agents in the system including built-in, plugin, project, and user-level agents. Use when you need to find which agents are available, understand the agent ecosystem, or prepare agents for Actoris registration.
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。
Standardized reference documentation section structure for agents - project guidance, conventions, related agents, and Skills. Use when implementing or updating agent documentation.
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。
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>
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。
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.
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。
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.
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。
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.
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。