「awe」の検索結果

Guide plan → instrument → execute → validate with explicit checkpoints and questions. Use for ambiguous tasks or when enforcing a consistent agent workflow.

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。

Economic identity and reputation system for autonomous agents on Base.

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。

Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.

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。

Designs multi-agent systems with coordinated agent swarms, task distribution, inter-agent communication, and emergent collective behavior.

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 Scrum Master specializing in agile transformation, team facilitation, and continuous improvement. Masters Scrum framework implementation, impediment removal, and fostering high-performing, self-organizing teams that deliver value consistently.

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。

Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".

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 markdown reports from issues. Filter by type, priority, epic, date range. Supports summary, detailed, progress, completion, velocity, and backlog analysis views.

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。

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

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 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.

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。

Evaluate a codebase for agent-friendliness based on autonomous agent best practices. Use when asked to "evaluate for agents", "check agent readiness", "audit for autonomous execution", "assess agent-friendliness", or when reviewing infrastructure for unattended agent operation. Also use when asked about making a codebase more suitable for AI agents or autonomous 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。

Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.

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。

Pre-commit and pre-merge validation checks. Use before committing changes or declaring work complete to ensure all quality gates pass.

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 .agent/baseline.md and later compare against it. Use when capturing baseline build/lint/test results or investigating newly introduced findings.

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。

Transform implementation plans into concise stakeholder-friendly summaries with file change overviews, component listings, and optional flow diagrams.

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 prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.

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。

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

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。

Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.

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。

Ready-to-use prompt templates for specialized agents. Use when building n8n workflows, AI integrations, or sales materials. Contains structured prompts for automation-architect, llm-engineer, and sales-automator agents.

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。

Automatically applies when designing multi-agent systems. Ensures proper tool schema design with Pydantic, agent state management, error handling for tool execution, and orchestration patterns.

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。

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.

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。

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?'

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。

Human and agent coordination protocol for repos using .agentprotocol. Use to manage TODO intake, open and archived work items, and plan/build docs with deterministic indexes.

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。

Run prompt with OpenAI or Gemini provider via agent CLI

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 release-swarm - invoke with $agent-release-swarm

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。