「multiple」の検索結果

Create realistic play-by-play commentary. Multiple announcer styles: traditional, hyped, analytical, homer. Color commentary included.

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。

CHAIN multiple existing skills into custom multi-step workflows. Programmable skill combinations with automatic handoffs. Create composite skills from building blocks with conditional logic.

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。

Pulls financial statement numbers for US public companies straight from SEC EDGAR's free official XBRL APIs (companyfacts, companyconcept, frames, submissions) into a cited table. Every value carries its accession number, form, fiscal period, filed date, XBRL tag and a link to the filing, and the tool handles fiscal-year ends, quarterly vs YTD vs TTM, derived Q4, restatements and units. Use this whenever the user wants 10-K numbers or 10-Q numbers, says "pull financials for", asks for public company revenue, net income, EPS, cash, debt or capex, wants comps or a competitor side-by-side, a credit check, prospect research, or model inputs, or mentions SEC filings or EDGAR, even if they never say XBRL. Free and primary-source, no paid data terminal needed. Do not use it for private companies, stock prices or valuation multiples.

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。

Aggregate prospect intelligence from multiple sources including news, social media, company websites, and financial 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。

Generates monthly/quarterly investor updates. Takes KPIs, milestones, challenges, financials. Writes professional investor-update.md with highlights, metrics dashboard, product updates, team news, financial summary, upcoming milestones, asks. Multiple tones from seed-stage casual to Series B formal. Use when founders need to communicate progress to investors.

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。

Convert game stats and highlights into engaging recaps. Multiple styles: Twitter thread, Instagram carousel, blog post, newsletter.

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。

Maintain project state across MULTIPLE conversations over days/weeks. Track tasks, decisions, blockers, resources. Auto-update when project mentioned. Generate status reports and proactive reminders.

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。

Assemble 2-3 complementary experts to collaboratively analyze anything. Experts work together to explore topics from multiple expert angles.

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 key concepts from any content and create spaced-repetition flashcards. Multiple formats: Anki-compatible, printable PDFs, interactive web.

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。

Merges, appends, joins, and deduplicates multiple CSV, TSV, and Excel files (including multi-sheet workbooks) with pandas - mapping mismatched column names to one schema, normalizing keys, resolving conflicting values, tracking which file each row came from, and verifying the row math. Use when the user wants to combine spreadsheets or exports, stack monthly files, consolidate contact or lead lists, VLOOKUP-style join two sheets on an ID or email, or dedupe records across sources, even if they only say "put these together" or "clean up these lists into one".

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 color palettes from images, websites, or designs. Identifies dominant colors, generates complementary schemes, and exports in multiple formats (HEX, RGB, HSL, Tailwind, CSS variables). Use when users need color schemes from images, brand colors, or design system palettes.

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 full consulting proposals from a brief. Input client name, problem description, and rough scope. Outputs proposal.md with executive summary, problem statement, proposed approach, timeline, team, pricing tiers, and terms. Researches client company for personalization. Multiple pricing models. Professional formatting matching consulting standards.

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 and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact 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。

Merges, dedupes, ranks, and formats research findings into a report. Use after research agents return results from multiple channels to produce a ranked 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。

Runs multi-source research across GitHub, HN, Reddit, arXiv, and Semantic Scholar. Use when surveying a technical topic across multiple channels.

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。

Registers external services with health checks, central config, and unified execution. Use when integrating multiple external services needing coordination.

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。

Presents adaptive codebase challenge questions with multiple-choice and trace exercises. Use when testing contributor knowledge of the codebase.

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 turning a single topic into a full content plan with multiple angles, formats, and a publishing calendar. Triggers on "content plan", "content calendar", "snowball method", "turn one topic into many posts", "content multiplication", "30 days of content", "content from one idea".

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。

Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.

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。

Guides building a multi-jurisdiction privacy compliance matrix for organisations operating across multiple countries. Covers common requirements identification, jurisdiction-specific deltas, gap analysis, and harmonised control frameworks. Keywords: multi-jurisdiction, compliance matrix, harmonised controls, gap analysis, jurisdiction 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。

Implementing cookie compliance across multiple jurisdictions including EU ePrivacy Directive, UK PECR, US California CCPA/CPRA opt-out model, and Brazil LGPD. Provides a requirements matrix and geolocation-based implementation approach.

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。

Manages coordinated breach notification across multiple legal jurisdictions including EU member states (72-hour GDPR deadline), US state breach notification laws (varying timelines from 30 to 90 days), and other international regimes. Covers conflict resolution when notification timelines differ, lead supervisory authority determination, and parallel notification execution. Keywords: multi-jurisdiction, cross-border breach, notification coordination, GDPR, US state laws, international breach notification.

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。

Scrape leads from multiple platforms using Apify Actors.

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。

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.

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。