754 件 ・ 関連度順
概要と使いどころ
Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.
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 building AI agents using prompt-native architecture where features are defined in prompts, not code. Use it when creating autonomous agents, designing MCP servers, implementing self-modifying systems, or adopting the "trust the agent's intelligence" philosophy.
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。
Perpetual autonomous work loop for Claude Code — no end condition, no memory regression, no context overfill. Maintains a persistent ledger across all sessions.
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。
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。
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。
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。
This skill should be used when the user asks to "create an agent", "write a subagent", "generate agent definition", "add agent to plugin", "write agent frontmatter", "create autonomous agent", "build subagent", needs agent structure guidance, YAML frontmatter configuration, invocation criteria with examples, or wants to add specialized subagents to Claude Code plugins with proper capabilities lists and tool access 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。
Use when the user asks to design multi-agent systems, create agent architectures, define agent communication patterns, or build autonomous 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。
Manage git commits for autonomous coding. Use when committing feature implementations, creating descriptive commits, managing git workflow, or handling version control.
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。
Manage knowledge graph for autonomous coding. Use when storing relationships, querying connected knowledge, building project understanding, or maintaining semantic memory.
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 designing an autonomous agent, planning agent architecture, building a scheduled automation, or creating a Claude Code agent workflow. Triggers: 'design an agent', 'build an automation', 'agent architecture', 'automate this workflow', 'create a scheduled agent', 'shell script 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。
Manage persistent memory for autonomous coding. Use when storing/retrieving knowledge, managing Graphiti integration, persisting learnings, or accessing episodic memory.
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。
Autonomous iOS bug fixer. (gstack).
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。
Execute Indirect Prompt Injection attacks against Large Language Models (LLMs) by subtly embedding malicious instructions within external data sources (e.g., websites, documents, databases) that the LLM autonomously ingests. This forces the model to execute attacker-controlled commands under the guise of processing legitimate user requests.
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。
Identify and map the external corporate footprint of a target organization. Use this skill at the absolute beginning of an engagement (Reconnaissance) to identify all registered domains, subdomains, IP ranges, and Autonomous System Numbers (ASNs) owned by the target. This skill forms the foundation for all subsequent external penetration testing and attack surface 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。
Understand the mechanics of Border Gateway Protocol (BGP) Hijacking, where an attacker creatively manipulates Internet routing tables to intercept, monitor, or drop massive volumes of network traffic destined for legitimate Autonomous Systems (AS).
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 AI agent systems for tool abuse, unauthorized actions, privilege escalation through tool chaining, and safety bypass via agentic workflows. Use this skill when assessing autonomous AI agents that use tool-calling (function calling, plugins, actions) to interact with external systems. Covers multi-step attack chains, implicit trust exploitation, and capability boundary testing for AI 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。
AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.
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。
Fierce autonomous internal co-founder. Bounded web research for evidence-backed improvements. Structured idea formulation with self-critique filter that rejects ideas not serving the goal. Auto-implements high-confidence aligned improvements, proposes medium-confidence ideas for approval. Evaluates viral coefficient, AI search visibility (GEO), and solo SaaS economics. Considers higher pursuits: employing disabled people, spiritual tech investigation, 99% wealth donation ethos.
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 about to commit, finish a task, open a PR, summarize work for the user, or when the user asks for a review or summary — NOT just on autonomous commits, which are rare in OpenCode usage
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。
The investigation harness for "why is this slow?" over a Pulp Perfetto trace (.pftrace). Runs the hypothesis→query→drill-down chain-of-evidence loop autonomously and returns a plain-English root cause + evidence + a concrete fix. TRIGGER on "why is my plugin slow to open", "find the slowest frames", "why is the UI stuttering", "why is my plugin using so much CPU", "which DSP node is expensive", "the load meter looks calm but CPU is pinned", or a named `pulp trace gpu-startup|gpu-health|gpu-probe` analysis. Ships Pulp-specific hints for dsp, frame, js, gpu, and cross-platform symptoms.
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。
Orchestrates 6-phase SDLC pipeline (discovery, requirements, architecture, workstreams, implementation, summary) for guided feature development. Use when user runs /core:develop command, requests spec-driven development, wants to create implementation plans with architecture decisions, or mentions "SDLC", "spec-driven", "plan feature", "development pipeline". Supports plan persistence, wave-based resume, autonomous mode, and architecture/implementation verification.
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 whenever the user asks to "open a PR", "ship this", "create the pull request", "make a PR", or once a Vue feature/fix is verified and ready to push. Full lifecycle: branch → commit (commitizen) → issue → draft PR → CI → ready → autonomous monitor loop (fix comments, resolve threads, iterate until CI green + zero unresolved threads). `--perfect` adds a CodeRabbit convergence loop on top. Never works on `main`/`master`, never uses `--no-verify`.
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。