4,385 件 ・ 関連度順
概要と使いどころ
Appwrite Python SDK skill. Use when building server-side Python applications with Appwrite, including Django, Flask, and FastAPI integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite Ruby SDK skill. Use when building server-side Ruby applications with Appwrite, including Rails and Sinatra integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite PHP SDK skill. Use when building server-side PHP applications with Appwrite, including Laravel and Symfony integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite .NET SDK skill. Use when building server-side C# or .NET applications with Appwrite, including ASP.NET and Blazor integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite Rust SDK skill. Use when building server-side Rust applications with Appwrite. Covers async client setup with API keys, user management, TablesDB database/table/row operations, file storage, function executions, permissions, queries, and error handling. Uses the crates.io `appwrite` package and Tokio.
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。
Prometheus provider for obz. Covers all 6 metric commands using standard PromQL. This skill should be used when the user mentions "Prometheus", "PromQL", "obz metric -p prom", or needs to query metrics from a Prometheus server.
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。
Operate and debug the DNS C2 system non-interactively. This skill should be used when Claude needs to launch an exploit, send commands to a compromised session and collect output, diagnose why a payload is not calling home, or inspect C2 server state. Triggers on requests like "run the exploit", "send whoami to the session", "why isn't the payload calling back", "check what sessions are active", or "debug the C2".
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 whenever the user wants to use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.
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 research-coordinator protocol: the OBSERVE -> IDEATE -> SELECT -> DISPATCH -> DECIDE cycle over a durable Idea Tree. Preloaded automatically on /auto-research sessions. The coordinator never edits code or runs commands — executors do that in isolated worktrees; the coordinator steers the tree with idea_tree / dispatch_experiments / merge_experiment.
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。
系统架构图绘制。当需要绘制任何系统架构图、云架构设计图、微服务架构图、Serverless架构图、混合云架构图时使用此技能，支持腾讯云及通用架构场景。基于 Draw.io XML 生成 .drawio 文件，支持二次可视化编辑。
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。
Threat actor infrastructure tracking involves monitoring and mapping adversary-controlled assets including command-and-control (C2) servers, phishing domains, exploit kit hosts, bulletproof hosting, a
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。
Optimize cloud and AI costs for modern SaaS stacks (Vercel, Supabase, Neon, Stripe, and AI APIs). Covers token efficiency, serverless database scaling, edge function optimization, and burn rate monitoring. Use when planning infrastructure, investigating high bills, or auditing API 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。
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。
Set up the prerequisites for the Quarkus + LangChain4j agentic stack in the coding agent you are running — detect and (with approval) install the toolchain, register the Quarkus Agents MCP and context7 MCP servers, and write the conventions file into your project. User-invoked only, via /setup-agentic-scaffolding; it prepares the environment the /scaffold-project and /audit-project skills depend on.
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。
Use when a report or article needs to be split into individual claims before it is graded, cited or used as evidence — the user asks "what does this report actually claim?", "split this into claims", "separate the facts from the judgements", or another skill needs a claim list. Turns one document into five to twelve atomic claims, each typed (observation, attribution, assessment, actor claim, victim disclosure) and anchored to the verbatim sentence it rests on, so every extraction can be checked against the source. Preserves the source's own hedging. Does not grade. Invoked by /quality-of-information-check; its output feeds /ach, /key-assumptions-check, /intelligence-writing, /writing-assessments and /threat-actor-profiling.
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。
Detect and remove the tells of AI-generated writing in BOTH English and Spanish, and read back the evidence honestly. Use when the user asks to "de-AI" / "humanize" / "un-slop" a draft, to examine whether text carries the tells (delve, tapestry, "it's not just X, it's Y", "here's the thing", em-dash overuse, an assistant's own closing line left in the document), to compare documents for overlap, or mentions signs-of-ai / SignsOfAI. Backed by the SignsOfAI engine — for a measured 0–100 score, sentence-rhythm burstiness, originality, citations, a writer baseline or perplexity, hand off to that engine (web app, CLI or MCP server) as described below. It cannot determine who wrote a text and must never imply that it can.
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。
Comprehensive backend API development skill for building robust, scalable APIs. Use when creating new endpoints, services, or backend functionality. Keywords: API, backend, endpoint, service, REST, GraphQL, server, controller, route
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。
Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.
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。
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
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。
Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.
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。
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
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。
Next.js App Router principles. Server Components, data fetching, routing patterns.
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。