1.4万 件 ・ 関連度順
概要と使いどころ
Apply cognitive task analysis to expert work that depends on perceptual cues, branching judgment, and recurring monitoring loops. Use when decomposing expert capability into agent structure, simulation design, or validation interviews. NOT for ordinary step-by-step SOP capture or simple pipelines with no tacit cue layer.
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Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.
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Designs and verifies fail-closed continuation of a living durable agent after its VM, process, provider session, backend, or context window disappears. Use for body leases, generation fencing, cold-birth failure, process GC, native resume, cross-harness rebodiment, resurrection capsules, capability translation, ambiguous-effect reconciliation, and capacity-aware handoff. NOT for reviving an intentionally retired identity, generic disaster recovery, copying credentials or raw transcripts, ordinary process restart, or claiming metaphysical continuity.
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。
Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.
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Design scheduling agents. Use for timezone-safe negotiation, focus protection, and privacy-safe free-busy handling. NOT for calendar UI, project planning, or general agent architecture.
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Plan, evaluate, and adopt agent infrastructure for a named workload. Use for agent runtime/framework selection, agent evaluation or observability plans, memory and tool boundaries, infrastructure cost controls, and organizational adoption. Covers workload-first comparison, risk and recovery planning, held-out evaluation, cost accounting, and staged rollout. Not a vendor ranking or a production certification. NOT for implementing a specific agent behavior (agentic-patterns), building a specific agent (ai-engineer), prompt optimization (prompt-engineer), or conventional ETL workflow design (jury_rig-architect).
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。
Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use jury_rig-architect), specific tool implementation.
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 or review a declared control-command profile and its verb/backend lifecycle matrix. Distinguish policy denial, unsupported capability, delivery acknowledgement, independently observed effect, and unknown outcome; bind authorization to principal, target, scope, current policy, expiry, and fencing epoch. NOT for claiming runtime correctness, proving an adapter from declarations, or approving a control-panel button without independent runtime evidence.
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 and audits deterministic, authority-filtered partitions of trust-typed context for already admitted bodies or abstract continuation slots. Use when causal context, obligations, disclosure boundaries, vector-space identity, capacity, and omission proofs must survive partitioning. NOT for spawning or admitting agents, choosing worker count, retrieving arbitrary knowledge, writing successor prompts, or granting tools, leases, identity, or effect authority.
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。
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
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。
Build production-grade AI agents from scratch using patterns inspired by production-grade agentic systems like Claude Code. Covers two audiences — (1) workflow builders who need planner+executor pipelines, human-in-the-loop checkpoints, and multi-agent orchestration, and (2) application embedders who need HTTP/SSE APIs, multi-user session management, and React frontend integration. Use when asked to build an AI agent, create a coding assistant, embed an agent in an app, build an API agent, clone Claude Code, build a CLI agent, design an agent architecture, scaffold an agentic system, or automate a multi-step workflow. Triggers on keywords like agent builder, agent blueprint, coding assistant, CLI agent, agentic tool, claude code clone, agent scaffold, agent architecture, workflow automation, multi-agent, planner executor, SSE streaming, agent API.
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。
Convert Claude's Markdown output to each channel's native text syntax before delivery. Adds zero-dependency formatting for WhatsApp, Telegram, and Slack (marker substitution). Also ships a Signal rich-text helper (parseSignalStyles) used by the Signal 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。
Add image vision to NanoClaw agents. Resizes and processes WhatsApp image attachments, then sends them to Claude as multimodal content blocks.
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。