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概要と使いどころ
Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.
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。
Decomposition playbook and anti-temptation rules for an orchestrator agent that routes work through the Surogates subagent task layer. Pair this skill with an AgentDef whose tool filter strips the implementation tools (terminal, file, web, code) — that's how 'don't do the work yourself' is enforced structurally, not just behaviorally.
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 Arbor executor workflow: clone the repo from the git bundle your brief hands you, implement and evaluate exactly ONE hypothesis with the file tools, then report structured results via worker_complete. Preloaded automatically on arbor-executor task workers. Never touch the held-out test split.
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。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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。
Browser automation, debugging, and performance analysis using Puppeteer CLI scripts. Use for automating browsers, taking screenshots, analyzing performance, monitoring network traffic, web scraping, form automation, and JavaScript debugging.
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 how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.
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 implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent 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。
Prismatic API access patterns and GraphQL reference. Covers the two-tier access hierarchy (MCP tools → Prism CLI), CLI usage rules, GraphQL query patterns, pagination, authentication, and managing platform resources programmatically.
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 Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace.
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 Symphony's generated typed TAPD tools for tracker workflow actions. Provides TAPD capability semantics and workpad 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。
Use Symphony's generated typed Linear tools for tracker workflow actions. Provides Linear capability semantics and workpad 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。
Reverse engineers malware binaries using NSA's Ghidra disassembler and decompiler to understand internal logic, cryptographic routines, C2 protocols, and evasion techniques at the assembly and pseudo-C level. Activates for requests involving malware reverse engineering, disassembly analysis, decompilation, binary analysis, or understanding malware internals.
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。
Identifying and validating cross-site scripting vulnerabilities using Burp Suite's scanner, intruder, and repeater tools during authorized security assessments.
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。
You are an expert in compounding growth and referral marketing with access to referral program data and third-party tools. Your goal is to help design and optimize programs that turn customers into Revenue (Cuan) engines.
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。
Develops comprehensive threat actor profiles for APT groups, criminal organizations, and hacktivist collectives by aggregating TTP documentation, historical campaign data, tooling fingerprints, and attribution indicators from multiple intelligence sources. Use when briefing executives on sector-specific threats, updating threat model assumptions, or prioritizing defensive controls against specific adversaries. Activates for requests involving MITRE ATT&CK Groups, Mandiant APT profiles, CrowdStrike adversary naming, or sector-specific threat briefings.
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。
Investigates phishing email incidents from initial user report through header analysis, URL/attachment detonation, impacted user identification, and containment actions using SOC tools like Splunk, Microsoft Defender, and sandbox analysis platforms. Use when a reported phishing email requires full incident investigation to determine scope and impact.
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。
Maps observed adversary behaviors, security alerts, and detection rules to MITRE ATT&CK techniques and sub-techniques to quantify detection coverage and guide control prioritization. Use when building an ATT&CK-based coverage heatmap, tagging SIEM alerts with technique IDs, aligning security controls to adversary playbooks, or reporting threat exposure to executives. Activates for requests involving ATT&CK Navigator, Sigma rules, MITRE D3FEND, or coverage gap analysis.
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 skill when the user needs to set up bookkeeping, track revenue and expenses, prepare for taxes, choose accounting software, understand SaaS revenue recognition, or manage the financial operations of their bootstrapped business. Covers bookkeeping setup, tax preparation, accounting tools, and financial hygiene for the Agentic Company.
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 reading state from a running PlayCanvas app, to reach its live Application through the Engine devtools hook without changing app code.
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。
Scaffold Quarkus + LangChain4j projects end-to-end and add agentic components to existing ones — AI services, tools, agents and multi-agent workflows, RAG pipelines, MCP clients and servers (Model Context Protocol), guardrails, and embedding store setups. Use this whenever the user wants a new Quarkus + LangChain4j project or module created, or an agentic component added to an existing project in this stack, including a baseline pom.xml, application.properties, project layout, or starter classes.
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。
See the difference between Chat and Cowork with a live side-by-side comparison for understanding why Cowork is built differently. Use when evaluating AI tools, for comparing chat versus agent capabilities, during an AI tool decision, when switching from ChatGPT or Claude Chat, or when the user says "what is different about cowork", "cowork vs chat", "why not just use chatgpt", "show me the difference", "compare chat and cowork", or "why should I use cowork instead of chat".
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 skill when routing adversary findings in Phase 4. Provides routing logic, iteration limit enforcement, and escalation protocols.
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。
Guide for managing the Agent Registry - database-backed agent configuration system. Use when asked to "configure agents", "manage skills", "set tool permissions", "create context rules", or when working with agent assignments per platform/chat. Covers dashboard UI, API endpoints, CLI commands, and MCP tools.
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 Gemini CLI 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。