「pet」の検索結果

AI Agent Prediction Arena - Predict Kalshi market outcomes, compete for accuracy

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。

YouTube SERP Scout for agents. Search top-ranking videos, channels, and trends for content research and competitor 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。

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。

Web search with full page content extraction. Use this skill whenever the user asks to search the web, find articles, research a topic, look something up, find recent news, discover sources, or says "search for", "find me", "look up", "what are people saying about", or "find articles about". Returns real search results with optional full-page markdown — not just snippets. Provides capabilities beyond Claude's built-in WebSearch.

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。

Turns client wins into structured case studies in multiple formats. Gathers before/after metrics, structures as Problem-Solution-Results, and outputs landing page copy, one-pager, social snippets, and email insert.

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。

Weekly churn risk detection across active client accounts. Scans for signals like decreased engagement, missed meetings, delayed payments, and competitor mentions. Scores risk 1-10 and outputs prioritized alert list.

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。

Evaluates current go-to-market positioning versus the market. Analyzes website, content, pricing, ICP alignment, and competitive landscape to identify gaps, opportunities, and produce a GTM health report.

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。

Monthly strategic review playbook. Chains pipeline-review + campaign-analyzer + win-loss-analyzer + gtm-analyzer. Outputs executive summary with KPIs, channel ROI, competitive shifts, and strategic 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。

Generate SEO-informed content briefs with competitive positioning

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。

Find keyword gaps, SERP opportunities, and low-competition high-intent keywords

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。

Find broken links, competitor backlinks, and link building outreach targets

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 validated JSON-LD structured data markup for any page type

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。

Generates platform-native social media posts for LinkedIn, X/Twitter, Instagram, and Reddit. Supports thought leadership, case study snippets, hot takes, engagement questions, carousel outlines, and threads.

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 running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

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。

Structure persuasive speeches and formal arguments in forensic, legal, policy, and competitive debate styles. Use when the user needs to prepare talks, opening or closing arguments, policy pitches, public explanations, debate speeches, or mentions 'forensic speech', 'formal argument', 'persuasive speech structure', 'debate speech', 'opening statement', 'closing argument'. Turns structured claims into audience-tuned persuasive delivery.

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, fill, and assemble PDF documents at scale. Handles legal forms, contracts, invoices, certificates. Supports form filling (pdf-lib), template rendering (Puppeteer, LaTeX), digital signatures (DocuSign), and document assembly. Use for legal tech, HR automation, invoice generation. Activate on "PDF generation", "form filling", "document automation", "digital signatures". NOT for simple PDF viewing, basic file conversion, or OCR text extraction.

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。

Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

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。

Professional CV and resume builder transforming career narratives into ATS-optimized, multi-format resumes. Integrates with career-biographer for data and competitive-cartographer for positioning. Generates PDF, DOCX, LaTeX, JSON Resume, HTML, and Markdown. Activate on 'resume', 'CV', 'ATS optimization', 'job application'. NOT for cover letters, portfolio websites (use web-design-expert), LinkedIn optimization, or interview 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。

Matches natural language task descriptions to appropriate skills using semantic similarity, ranks candidates by fit and performance history, and maintains the skill catalog. Use when assigning skills to DAG nodes, searching for the right skill for a task, ranking competing skills, or browsing the skill catalog. Activate on "find skill", "match skill", "which skill", "skill for this task", "skill catalog", "rank skills", "best skill". NOT for executing DAGs (use dag-runtime), creating skills (use skill-architect), or grading skills (use skill-grader).

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 DAG incidents with a precise top event, timeline, competing hypotheses, barriers, propagation, and bounded recovery. NOT for automated root-cause classification, trace collection, or performance 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。

Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.

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。