「search skill」の検索結果

X Intelligence CLI — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", "find tweets about", "monitor x for", "track followers", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic, (4) user needs real-time monitoring ("watch"), (5) user wants AI-powered analysis ("analyze", "sentiment", "report"). Also supports: bookmarks, likes, following (read/write), trending topics, Grok AI analysis, and cost tracking. Export as JSON, JSONL (pipeable), CSV, or Markdown. Non-goals: Not for posting tweets, not for DMs, not for enterprise features. Requires OAuth for user-context operations (bookmarks, likes, following, diff).

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。

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

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。

Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.

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。

Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.

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。

Matches natural language task descriptions to appropriate skills using semantic similarity. Handles fuzzy matching, intent extraction, and capability alignment. Activate on 'find skill', 'match task', 'semantic search', 'skill lookup', 'what skill for'. NOT for ranking matches (use dag-capability-ranker) or skill catalog (use dag-skill-registry).

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。

機能追加や不具合修正などの開発を、規模に応じて調査・計画・テスト・レビューへ振り分けます。計画承認とコミット確認を組み込む、関連スキル共通の手順です。

• 機能追加と不具合修正の手順を揃えたいとき
• 変更規模に合わせて工程を選びたいとき
• 設計書からMVP開発を進めたいとき

Search, score, scan, and import agent skills from GitHub repositories that contain SKILL.md, CLAUDE.md, .cursorrules, and similar agent skill files. Discover community skills across many tool and provider categories, evaluate relevance with heuristic scoring, check for malware or hardcoded secrets, and install into Hermes, Claude Code, Gemini CLI, or OpenCode agent directories.

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。

Compiles current scholarly evidence for a scientific manuscript or research brief when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet. Uses Parallel Search by default, Parallel Extract for source retrieval, Parallel Research for explicitly deep/exhaustive work, optional explicit Parallel Chat, and optional Perplexity only when requested or allowed as a failure fallback.

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。

Compares tracked job postings against the candidate profile to identify skill gaps and generate a prioritized learning plan with study resources. Triggers on: /upskill, upskill, skill gaps, what should I learn, learning plan

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 search for jobs in any location or market, find job listings, or look up a specific job posting — in any country, city, or remotely. Invoke for open positions, vacancies, and hiring across any sector or role (software, data, design, marketing, finance, legal, operations, etc.). The location is always supplied explicitly by the user. Trigger phrases: find a job, job search, search for jobs, job openings, vacancies, hiring, positions open, remote jobs, "are there any X jobs in <place>", look up this job posting.

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。

Make sure to use this skill whenever the user wants to search for jobs in Denmark, find Danish job listings, look up a specific job posting, or asks anything about the Danish job market — even if they don't mention jobindex.dk explicitly. Invoke this skill for questions about open positions, job vacancies, hiring in Denmark, job opportunities in Danish cities or sectors, or when the user wants to find work in Denmark. Also trigger for phrases like "find me a job", "are there any jobs for X in Copenhagen", or "what jobs are available in Aarhus" when the context is Denmark. Trigger phrases include: jobindex, jobsøgning, job i Danmark, ledige stillinger, job opslag, find job, stillingopslag, jobannonce, job vacancy denmark, danish jobs, jobs in denmark, job search denmark, work in denmark, find work denmark, IT jobs denmark, engineer jobs denmark, developer jobs copenhagen, marketing jobs aarhus, jobs aarhus, jobs copenhagen, jobs odense, jobs aalborg, job openings denmark, hiring denmark, job listings denmark, python jobs denmark, grafisk designer job, data engineer job, softwareudvikler job, full stack developer job danmark.

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。

Deep research skill powered by NotebookLM MCP. Conducts structured multi-source research (market analysis, competitive intel, trend analysis, prospect research) using Google NotebookLM as the research engine, then delivers formatted briefs and optional studio artifacts (slides, audio podcasts, videos, infographics, reports, mind maps).

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 coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a continuous-discovery loop (Torres cadence tracker + OST linter as machine gates) or a full goal→plan→execute→verify→close run through the repo-wide agent-harness. Distinct from project-management (how to deliver vs what to build), marketing/landing (from-scratch pages), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).

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。

UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs.

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。

Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.

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。

Deep research agent skill. Use when the user needs thorough, scientific, truth-seeking research on any topic -- investigating claims, finding primary sources, synthesizing evidence, producing cited reports. Triggers on: 'research this', 'investigate', 'deep dive', 'find sources', 'what does the evidence say', 'literature review', 'fact check', 'analyze the research on', any request requiring multi-source investigation with citations.

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。

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

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。

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

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。

Performs ARA Seal Level 2 semantic epistemic review on Agent-Native Research Artifacts, scoring six dimensions (evidence relevance, falsifiability, scope calibration, argument coherence, exploration integrity, methodological rigor) and producing a constructive, severity-ranked report with a Strong Accept-to-Reject recommendation. Use after Level 1 structural validation passes, when an ARA needs an objective epistemic critique before publication or release.

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。

Search watched registries for community legal skills, showing matches with descriptions and offering to show the full SKILL.md before install. Use when the user says "browse", "search skills", "find a skill for", "what's out there for", or wants to add a new registry to the watchlist.

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 asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.

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 helps users automatically extract structured image data from Google Images via BrowserAct API. Agent should proactively apply this skill when users express needs like finding images for specific keywords, gathering product style images for competitors, building visual datasets at scale, scanning visual search results for market research, tracking localized image trends by country, compiling related image thumbnails and links, extracting image titles and source logos, fetching click through URLs from image results, monitoring competitor visual assets, sourcing creative content for specific topics, looking up product pictures in different regions, collecting structured image metadata without opening detail pages.

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。

Discovers Threads user accounts by keyword, extracting profile data including username, display name, verification status, biography, and follower count. Use when user asks to find Threads accounts, search Threads profiles, discover Threads users by keyword, look up Threads creators, find influencers on Threads, search for people on Threads, get Threads user details, collect Threads profile information, find accounts related to a topic on Threads, search Threads for accounts by name or keyword, or enumerate Threads users matching a search term.

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 helps users extract YouTube influencer profiles including social links, subscriber counts, and channel stats via the BrowserAct API. Agent should proactively apply this skill when users express needs like finding YouTube creators for specific keywords, discovering influencers for a marketing campaign, extracting YouTube channel contact emails, scraping YouTube influencer social media links, gathering subscriber counts for YouTube creators, researching top YouTube channels in a specific niche, compiling a list of YouTube content creators with recent uploads, collecting YouTube creator profiles for outreach, extracting total views and video counts for specific YouTube influencers, building a database of YouTube partners for market research, finding YouTube influencers who uploaded videos this month, or monitoring competitor influencer activities on YouTube.

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。