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概要と使いどころ
Compare two sessions side-by-side using Agent Monitor data — per-model token usage (input/output/cache_read/cache_write + compaction baselines), pricing engine cost breakdowns, workflow intelligence (complexity scores, tool flow transitions, subagent effectiveness), session metadata (thinking_blocks, turn_count, turn_duration_ms, usage_extras), and full event timelines with all 10+ event types.
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Capture a hard-won "golden path" from the current session as a reusable Agent Skill, so future sessions start already knowing it. Use it (1) right after non-trivial debugging, after working out a multi-step operational workflow, or after rediscovering project facts you didn't know up front — e.g. how to reach the dev/prod database, where credentials and env vars live, how to deploy, run migrations, or verify a change live; and (2) whenever the user says "remember this", "save this as a skill", "make a skill for this", "don't make me re-explain this next time", or otherwise wants a workflow preserved across sessions. Proactively recognize the moment even when unprompted: if a task took several attempts before it worked, used non-obvious tooling, or is likely to recur, harvest it without asking first. Delegates to a subagent when your tool supports one, or works inline, to extract the proven procedure into a new project-local or global skill.
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 a phased delivery orchestration plan for creative-direction-driven work: which skills run when, what locks at which gate, how handoffs occur, and how the cadence implements in the team's tools (Jira, Linear, Notion, Figma, GitHub) with AI agents via MCP and CLI. A temporal map of phases, lock points, handoff specs, gate definitions, and QA verification gates. Distinct from `creative-brief` (static project brief) and `creative-direction` (aesthetic direction). Triggers on integration orchestrator, delivery cadence, project orchestration, when does the brief lock, how to phase creative direction, design-development handoff, QA gate, agent-driven QA, and when a creative-direction project is starting, mid-flight with broken cadence, or integrating AI agents into PM workflow. Does NOT fire for project scoping (use `creative-brief`), aesthetic direction (use `creative-direction`), or general project management without a creative-direction throughline.
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 when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.
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 when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, review-depth fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.
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 when the user wants to build an evaluation system for an LLM/agent application but doesn't know where to start — they have traces, prompts, RAG pipelines, or nothing at all. Also use when the user mentions evaluation, eval, benchmarking, testing LLM quality, measuring agent performance, assessing RAG accuracy, or wants to compare prompts/models. This skill is the entry router: it asks diagnostic questions then recommends which sub-skill (local workflow) to use next.
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。
When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.
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。
Audits legal AI skills, prompts, workflows, MCP/tool instructions, and agent packages for prompt injection, malicious instructions, unsafe scripts, suspicious metadata, credential exposure, exfiltration paths, persistence mechanisms, and supply-chain risk. Use before installing, importing, publishing, promoting, modifying, or trusting third-party or generated AI skills and legal workflows. Do not use as a generic code review unless skill trust, workflow safety, prompt injection, or supply-chain hygiene is in scope.
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 when starting Claude Code projects, writing CLAUDE.md/spec.md, dispatching subagents, or requesting Agent Teams parallel development. Covers Spec-Driven Development, Context Engineering, and post-dev 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。
On-demand procedures for the ComfyUI sidebar panel agent that are too long to sit in the system prompt. Read it when a task lands in one of these areas. subgraph boundary rails and blueprint reuse, merging or composing workflows across tabs, pinning your edits to one workflow, opening staged or downloaded workflow files, untangling Get/Set-bus and rgthree toggle-heavy graphs, authoring rgthree Fast Groups nodes, the LoRA Manager autocomplete-node limitation, the CivitAI browser flow, downloading model weights, reading hardware and runtime stats, Prompt Director audits, custom-node crash recovery, run-to-node render debugging, and multi-stage pipeline chaining. Each section is a lookup, not background reading. Reach for the one you need instead of guessing, and follow the tool's own description for parameter detail.
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。
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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。
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
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 when the user wants to optimize configurable system parameters against a measurable scalar objective, especially for model training, inference, quantitative strategies, reinforcement learning, scientific workflows, or other expensive black-box evaluations where reading the project can improve trial 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。
Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/. Classifies incoming tasks and routes to brainstorm, direct edit, or task workflow. Use when beginning a new coding session, resuming work, starting a new task, or re-establishing project context.
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。
Bootstrap project-specific Trellis coding specs with a platform-neutral single-agent workflow. Use when creating or refreshing .trellis/spec guidelines, analyzing a codebase with GitNexus, ABCoder, or source inspection, decomposing package/layer spec work, and writing real codebase-backed spec docs without placeholder text.
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。
LlamaIndex 官方用户文档离线知识库，用于检索并回答 LlamaIndex Python 框架的安装、RAG、数据加载、索引、检索与查询、Agent、Workflow、模型、Embedding、向量库、评估、可观测性、部署、LlamaCloud 和 LlamaParse 等问题，也可生成有文档依据的示例代码与排障建议。当用户提到 LlamaIndex、llama-index、LlamaParse、VectorStoreIndex、QueryEngine、Retriever、AgentWorkflow 或相关集成用法时使用；纯源码贡献、内部实现审查或与 LlamaIndex 无关的通用 AI 问题不使用。
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。
Creates new specialized agents using the 5-phase workflow (ANALYZE > DESIGN > CREATE > VALIDATE > REFINE). Use when building a new AI agent or validating an existing agent specification.
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。
Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement
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 when the agent must open a URL, fill a form, click through a flow, screenshot a page, or extract data from a live page. Covers two providers (agent-browser local CLI, agentic-browser cloud) and the shared @e ref 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。
Create, revise, validate, or package Bot Generator Bot agent specifications and runnable MetaHarness agents using its CLI or MCP. Use for this repository's agent creation workflow, not unrelated chatbot products.
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。
Rules for writing concise, token-efficient workflow and skill files. Prevents over-building that requires costly optimization passes. Use when creating or editing workflow files, SKILL.md files, or new skill 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。
Slack CLI for agents: read URLs/threads/history/unreads/later/canvases/workflows, create/edit canvases from Markdown, search messages/files, download attachments, lookup users, list/create/invite channels, open DMs, compose messages, manage Slack-native drafts, schedule sends, and explicit sends/edits/deletes/reactions/mark-read/uploads.
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。
Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
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 Pattern
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。