「agent」の検索結果

AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, Azure to AWS, OpenAI/Gemini to Bedrock), route to the migration skills in this plugin (`gcp-to-aws`, `azure-to-aws`, `heroku-to-aws`, `llm-to-bedrock`). Do not use for: factual AWS Activate / programs / credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references/prompt-library/` tree.

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。

Configure AWS Security Agent for the current workspace — provision or reuse an agent space, IAM service role, and S3 bucket. Use when the user asks to "set up security agent", "configure security scanner", "is security agent configured", or on first-time use before any scan or pentest.

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。

Discover and validate Agent Skills, host plugins and subagents, MCP servers and configurations, hooks, and marketplace catalogs against the correct authority. Use when performing pre-merge review, external submission checks, portability audits, security checks, or validation of mixed agent-system repositories. Trigger with "validate this skill", "audit this plugin", "check this agent", "review this MCP config", or "is this marketplace ready".

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 converting, repairing, or packaging an existing local or external agent/team into Agentlas architecture for local install, Agentlas import, Codex plugin use, Claude adapter use, or open-source release.

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 types /agentlas-one on|off, /agentlas one on|off, or asks to enable/disable the persistent personal agent mode.

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 types /agentlas-graph, /agentlas graph, or /hep-graph to create, list, inspect, or run Agentlas automation graphs.

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 types /agentlas-search <query>, /agentlas search, or /hep-search to search across Local, Cloud, and Hub agent repositories.

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 types $hephaestus-upload, /hep-upload, or /agentlas-upload, or asks to upload, publish, or list an Agentlas agent or team. Ask Cloud (private) vs Agentlas Hub (public) FIRST, then publish through the bundled Hephaestus gate.

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 types /agentlas-storm, /agentlas storm, /hep-storm, or says @Hephaestus storm <goal> to drive a goal through the force-robust Stormbreaker loop with real Agentlas specialists.

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。

Agentlas 시스템 운용 절차 — hep-network 편성, hep-graph 자동화, cargo/Agent Cloud·marketplace 활용, workforce 로스터 재사용, 메모리 계약. One(개인 에이전트)이 Agentlas를 조작할 때 이 절차를 따른다.

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 types /agentlas-network, /agentlas network, $hephaestus-network, or /hep-network to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams.

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 types /agentlas-connect <channel>, /agentlas connect, or /hep-connect to connect Agentlas channels (Slack, Discord, Telegram, etc.).

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 types /agentlas-hub, /agentlas hub, or /hep-hub to staff only from the public Agentlas Hub marketplace.

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。

Set up a repo or project so an AI coding agent works well in it — the CLAUDE.md, the context, the guardrails, and the conventions the agent needs to be useful instead of lost. Use when asked how do I set up CLAUDE.md, configure my repo for Claude Code, my AI agent keeps getting my project wrong, or onboard an AI agent to my codebase. Produces a structured CLAUDE.md/project-context file (architecture, conventions, commands, do-nots), the right level of detail (enough to orient, not a novel), the guardrails that keep the agent safe (what not to touch, how to test), and a maintenance habit so it stays current — turning a repo an agent flails in into one it navigates like a teammate.

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 the pre-flight checklist before an agent drives a browser — the untrusted-web-content threat (every page is attacker-controllable), the credential and session-cookie exposure, the action-confirmation gates for purchases and posts, and the sandboxing that limits the damage. Use when asked let my agent browse safely, is it safe to give the agent computer/browser use, guardrails before the agent uses my browser, or review my browser agent's setup. Produces the sandbox decision, the content-injection defenses, the action gates, and the credential-isolation rules.

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。

Redesign seat-based pricing for the agent era — when one human runs ten agents, per-seat models collapse. Use when agents are eroding seat counts, when asked to migrate to usage- or outcome-based pricing, to price an agent/API tier, or to defend revenue as customers automate their own usage. Produces a pricing migration plan: the new value metric, fences, agent-tier design, cannibalisation math, and a phased migration for existing customers. For general pricing and packaging strategy use pricing-strategy.

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。

Review an LLM agent design and find where it will be unreliable, expensive, or unsafe. Use when asked to review an agent architecture, critique a multi-step/tool-using agent, debug an agent that loops or goes off-task, or harden an agent before launch. Produces a structured review — task fit, control flow, tools, memory/context, failure handling, cost, and safety — with prioritised findings and fixes.

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。

Talk to other coding agents on this machine (Claude Code, Codex, Copilot, Cursor, Gemini, AGY, Grok, OpenCode) through the magents MCP. Use when the user asks what another agent was working on, wants to carry on that work, send them a message, start an independent agent session, or check the shared inbox. Prefer magents MCP tools over hunting session files on disk.

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。

Writes turn-level tests for a LiveKit agent in the user's normal test suite: pytest (Python) or Vitest (Node.js). Use when the user asks to "write tests for my agent", "add a test for this tool", "test the handoff", "pin this bug", "why does my agent test fail", or after building or changing agent behavior that needs regression coverage. Covers the SDK's test session harness, assertions on messages, tool calls and handoffs, LLM judging of a reply against an intent, mocking tools, multi-turn tests, and judging whole conversations with the built-in judges. For interactive poking use debugging-livekit-agents. For grading whole conversations at scale use running-livekit-simulations.

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。

Render the multi-agent orchestration DAG for a session — parent→child subagent edges, tree depth, and fan-out — from the Agent Monitor workflow intelligence API. Cross-checks the orchestration dataset against the raw agent records and session detail. Use when visualizing how a session's agent structure was organized.

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。

Trace error propagation through a multi-agent session by agent depth — where failures originated, the depth at which they appeared, and how they cascaded up to parent agents — using the Agent Monitor workflow intelligence API and the session event stream. Use when a multi-agent run failed and you need to find the origin and blast radius of the failure.

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 agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging. Use when building multi-agent systems, defining tool interfaces, or implementing agent-to-agent communication.

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 an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.

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。

Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

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。