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概要と使いどころ
Live SEO data via DataForSEO MCP server: SERP analysis, keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis, competitor and content analysis, business listings, AI visibility (LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "AI visibility check", or "real search data".
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。
When the user requests to create or customize an academic personal website from a GitHub template repository. This skill handles the complete workflow of forking academic template repositories (like academicpages.github.io), extracting structured personal information from memory or provided data, and systematically updating configuration files (_config.yml), navigation menus (_data/navigation.yml), content pages (_pages/about.md), and publication listings (_publications/). It specifically handles academic profiles including personal details, education background, research experience, publications, skills, and contact information. Triggers include requests to 'fork and customize academic homepage', 'build personal academic website', 'create research portfolio', or 'set up GitHub pages with academic template'.
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Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.
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。
Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive 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。
Research venture capital firms, angel investors, and funding sources for startup fundraising. Use when: "投资人调研", "找VC", "research investors", "VC list", "funding sources", "investor database", "天使投资人", "venture capital", "融资对象", "投资人画像". Generates a structured investor research report with firm profiles, investment thesis, portfolio companies, contact strategies, and warm introduction paths. Part of UniqueClub founder toolkit. Learn more: https://uniqueclub.ai Pairs with pitch-deck-creator for complete fundraising preparation.
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 V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-*.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating user timing marks.
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。
Modify, debug, or extend the s6-overlay supervision tree inside the Hermes Agent Docker image — adding new services, debugging profile gateways, understanding the Architecture B main-program pattern.
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 covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.
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 comprehensive threat actor profiles using open-source intelligence (OSINT) techniques to document adversary motivations, capabilities, infrastructure, and TTPs for proactive defense.
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。
Map advanced persistent threat (APT) group tactics, techniques, and procedures (TTPs) to the MITRE ATT&CK framework using the ATT&CK Navigator and attackcti Python library. The analyst queries STIX/TAXII data for group-technique associations, generates Navigator layer files for visualization, and compares defensive coverage against adversary profiles. Activates for requests involving APT TTP mapping, ATT&CK Navigator layers, threat actor profiling, or MITRE technique coverage 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。
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。
Reconcile a converted/built web page against its source prototype with two complementary probes — a PIXEL/layout diff (stretched images, dropped wraps, blank renders, colour flips) and a STRUCTURAL content+typography diff (dropped/mis-slotted headings, eyebrows, CTAs; rendered-face font forks). Stack-agnostic via profiles (eds | generic). Use after converting a prototype to EDS/AEM (the stardust:deploy Step 10), or for any prototype↔build fidelity check; invocable as stardust:diff and from 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。
UI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation. Searchable local data: 79 searchable styles (50 active), 192 product palettes and reasoning profiles, 74 font pairings, 119 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.
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。
Command and Control framework deployment, configuration, and operational tradecraft for red team engagements. Covers Cobalt Strike (malleable C2 profiles, Beacon types HTTP/HTTPS/DNS/SMB, Beacon Object Files for in-memory execution, sleep and jitter tuning, named pipe pivoting), Sliver (implant generation across mTLS/WireGuard/DNS transport, operator multiplayer mode, armory extensions), Mythic (agent ecosystem with Apollo/Poseidon/Medusa, C2 profile configuration, translation containers), Havoc (Demon agent with sleep obfuscation via Ekko/Zilean, indirect syscalls, dotnet inline execution), Metasploit (msfvenom payload generation, multi/handler staging, Meterpreter post-exploitation modules), redirector architecture using Apache mod_rewrite and Nginx, domain fronting through CDN providers, DNS-based C2 for restrictive network egress, and TLS certificate management for infrastructure OPSEC. Tools: Cobalt Strike, Sliver, Mythic, Havoc, Metasploit Framework. Aligns to MITRE ATT&CK T1071 (Application Layer P...
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 red team operations methodology covering full engagement lifecycle from planning through reporting. Addresses engagement scoping and rules of engagement negotiation, multi-tier C2 infrastructure design with redirectors and domain fronting, malleable traffic profiles and beacon tradecraft, OPSEC discipline including attribution avoidance and indicator management, EDR and AMSI evasion techniques using direct syscalls and unhooking, data collection with chain-of-custody controls, and structured reporting with purple team debrief workflows. Covers assumed-breach, external-to-internal, insider threat, and hybrid physical-cyber engagement scenarios with MITRE ATT&CK mapping throughout. Targets operators planning or executing adversary simulation engagements against mature defenders.
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 Browser Use cloud API to spin up cloud browsers for Clawdbot and run autonomous browser tasks. Primary use is creating browser sessions with profiles (persisted logins/cookies) that Clawdbot can control. Secondary use is running task subagents for fast autonomous browser automation. Docs at docs.browser-use.com and docs.cloud.browser-use.com.
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 and qualify B2B prospects using web search. Builds structured profiles with company intel, key contacts, pain points, and engagement recommendations.
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。
Send LinkedIn connection requests to a list of people via browser automation and track status in a CSV/TSV file. Use when the user wants to bulk-connect with a list of people on LinkedIn (founders, speakers, leads, etc.) from a spreadsheet or list containing LinkedIn profile URLs. Handles Connect button, Follow-mode profiles, already-connected detection, stale URL fallback via LinkedIn search and Google search, and incremental status tracking.
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。
Control and interact with a live browser session on any scraped page — click buttons, fill forms, navigate flows, and extract data using natural language prompts or code. Use when the user needs to interact with a webpage beyond simple scraping: logging into a site, submitting forms, clicking through pagination, handling infinite scroll, navigating multi-step checkout or wizard flows, or when a regular scrape failed because content is behind JavaScript interaction. Also useful for authenticated scraping via profiles. Triggers on "interact", "click", "fill out the form", "log in to", "sign in", "submit", "paginated", "next page", "infinite scroll", "interact with the page", "navigate to", "open a session", or "scrape 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。
Enriches inbound leads with firmographic and technographic data. Takes minimal lead info and enriches via WebSearch, Apollo, or ZoomInfo to produce a complete lead record with company size, revenue, tech stack, social profiles, and decision-maker details.
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。
Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).
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。
Profiles DAG execution performance including latency, token usage, cost, and resource consumption. Identifies bottlenecks and optimization opportunities. Activate on 'performance profile', 'execution metrics', 'latency analysis', 'token usage', 'cost analysis'. NOT for execution tracing (use dag-execution-tracer) or failure analysis (use dag-failure-analyzer).
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。
App Store and Google Play submission automator with Fastlane, screenshot automation, metadata management, and TestFlight/internal testing. Activate on: app store submission, Fastlane, TestFlight, Google Play Console, screenshot automation, metadata management, app review, code signing, provisioning profiles. NOT for: CI/CD pipeline setup (use github-actions-pipeline-builder), app architecture (use react-native-architect), analytics (use mobile-analytics-crash-reporting-expert).
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。