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概要と使いどころ
Guidelines and instructions for maintaining, extending, and debugging the Konoha MCP Tools Orchestrator, MCP middleware, and multi-archetype website builder across 7 coding clients (Antigravity IDE/CLI, Cursor, Claude Code, OpenCode, Command Code, Codex, Pi/pi.dev).
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。
Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon detection, C2 protocol reverse engineering, or command-and-control infrastructure mapping.
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。
Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.
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。
Audit, detect, and remediate Shadow Credentials misconfigurations on msDS-KeyCredentialLink in Active Directory. Focuses on access-controls, monitoring Event ID 5136, and credential-management hygiene.
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。
Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.
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。
Extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.
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。
PumpOS — static HTML/CSS/JS web desktop for the Pump SDK with 169 Pump-Store apps, live token dashboards, interactive DeFi tools, PWA support, and Vercel deployment.
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 the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.
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。
Model Context Protocol server exposing 53 tools, 3 resource types, and 3 prompts for AI agent consumption — quoting, building transactions, fee management, analytics, AMM operations, social fees, wallet operations over stdio transport.
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 a new interactive design tool under /tools (like the color converter or contrast checker) — component, page, navigation, route lists, SEO, and tests. Use when building a new utility tool.
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。
Route requests for current library, framework, SDK, API, CLI, or cloud-service documentation through available documentation tools and primary sources.
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 Cline SDK skill for building AI agents. Covers the direct Agent runtime, ClineCore sessions, custom tools, plugins, events, LLM providers, scheduling, multi-agent teams, and production deployment. Use for any task involving @cline/sdk or its sub-packages.
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。
Diagnose common Cognitum Seed device issues — won't pair, no WiFi, firmware stuck, MCP tools not appearing in Claude Code. Use when the user reports a Seed-related symptom and asks "why isn't this working?".
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。
Generate audit-ready internal control design documents from As-Is business process inventories. Produces control IDs, assertion mappings, procedures, SoD analysis, KPIs, materiality thresholds, and implementation roadmaps. Use when building internal controls for new audit engagements, SOX/J-SOX compliance, or process improvement initiatives.
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 about "Hyprland configuration", "hyprland.lua", "hyprland.conf", "Hyprland Lua config", "hyprctl", "Hyprland keybinds", "Hyprland window rules", "Hyprland monitors", "Hyprland dispatchers", "Hyprland animations", "Hyprland workspaces", "Hyprland IPC", "Hyprland plugins", "hyprlock", "hypridle", "hyprpaper", "hyprcursor", "hyprpicker", "hyprsunset", "xdg-desktop-portal-hyprland", "Hyprland on NixOS", "Hyprland Home Manager", "Hyprland layouts", "Hyprland dwindle", "Hyprland master layout", "Hyprland FAQ", "Hyprland performance", "Hyprland Nvidia", "Hyprland screen sharing", "Hyprland special workspace", "Hyprland smart gaps", "Hyprland multi-monitor", "Hyprland tearing", or any topic related to configuring, troubleshooting, or extending the Hyprland Wayland compositor and its ecosystem 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。
Domain knowledge for using PrintKK print-on-demand API tools effectively. PrintKK is a print-on-demand platform that lets sellers create custom products, manage designs, upload images, and fulfill orders via API. Use this skill whenever the user wants to interact with PrintKK — browsing products, creating designs, placing orders, managing images, or building integrations with the PrintKK API. Also trigger when the user mentions "PrintKK", "print on demand", "POD fulfillment", custom product design workflows, or wants to automate their PrintKK store operations.
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。
Analyze pi (coding-agent) session JSONL and ego-benchmark-harness run artifacts to explain slow or failed individual tasks, compare execution-path differences between agents or browser tools, and count tool calls and error types. Use this skill whenever users ask to analyze a pi session, explain why a task was slow or failed, compare two runs, investigate an error, locate the session corresponding to tasks.jsonl, inspect an agent execution path, count tool calls, analyze a run ID, or perform any forensic or retrospective analysis of JSONL under ~/.pi/agent/sessions/ or agent-home/.pi/agent/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。
ego-browser (ego-lite) is a Chromium-based browser that gives AI agents a CLI-accessible Node.js runtime for driving a real browser. Use this skill whenever the user needs to interact with a website opening pages, filling forms, clicking buttons, taking screenshots, extracting page data, testing web apps, logging into sites, automating browser operations, or any other browser automation task. Triggers include requests to "open a website", "visit a URL", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "extract content from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also used for exploratory testing, dogfooding, QA, bug hunting, or reviewing app quality. Prefer ego-browser over any built-in browser automation, web fetch, or other web 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。
Compare standardized metrics across multiple ego-benchmark-harness runs by recalculating them from tasks.jsonl and session JSONL, never from HTML reports. Covers overall aggregates (success rate/average score), Odysseys per-rubric pass rates, duration distributions (avg/p50/p90/max), turns/tools/cost, error and exception counts, per-task success matrices, helper distributions, and the share of DOM operations. Use whenever users ask to compare data or metrics across runs, calculate aggregate/Odysseys/duration/turn/error/helper metrics, inspect differences among runs, or compare multiple rwb/real-world-bench runs. Use pi-session-analyzer instead for deep forensic analysis of why an individual task was slow or failed.
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。
Get literature into a research run when the plugin fetches nothing — fetch the source yourself with web_fetch / web_search or take a file the person already has, READ it with the pdf_* tools or ocr, then ingest record and text together with rs_cite, bind locators, and cite with [@key]. Use when a run needs sources, when a library export has to come in, when a citation key is unknown, or when a claim cannot be checked against a source.
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。
Write p5.js prototypes into the lab — sketches that actually run in a browser, seed-reproducible, with controls generated from the sketch's own parameters. Use for generative art, flow fields, particle systems, noise, animation, anything sketched visually in the browser.
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 for AI SDK for Python basics. Configure a model, make messages, stream, declare tools, build a basic 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。
Load when creating, scaffolding, configuring, debugging, testing, containerizing, or publishing a C#/.NET Model Context Protocol (MCP) server using the official Microsoft ModelContextProtocol SDK; not for non-.NET MCP servers, general ASP.NET Core APIs without MCP, or consuming external MCP tools as a client.
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。
Load when creating, editing, or debugging Lottie/Bodymovin JSON for the local Skia Skottie player: logo/type/SVG animation, loaders, icons, UI microinteractions, lower thirds, charts, diagrams, scene motion, effects, slots, or controls; not for static raster/SVG, CSS-only motion, or video editing.
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。