「content」の検索結果

Neural web search - find similar content, extract pages, and run deep research

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 images with AI - extract text, describe content, detect objects

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。

Fetch and read transcripts from YouTube videos. Use when you need to summarize a video, answer questions about its content, or extract information from it.

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。

Identify programmatic SEO page patterns worth building for your product — vs/ pages, integrations/, for-{industry}/, alternatives-to/, use-cases/ — and design the template structure, data model, and priority order. Outputs a complete pSEO blueprint with URL patterns, title templates, content frameworks, and data sources per variable.

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 website SEO - keywords, content, competitors, and improvement opportunities

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, AI answers, content extraction, and async deep research

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 blog posts via RSS feeds (free, no API key) with Apify fallback for JS-heavy sites. Use when you need to monitor competitor blogs, track industry content, or aggregate blog posts by keyword.

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。

Triages all inbound leads from a given period — demo requests, free trial signups, content downloads, webinar registrations, chatbot conversations. Classifies by urgency, qualifies against ICP, enriches with context, and produces a prioritized action queue with recommended response for each lead. Tool-agnostic — works with any CRM, form tool, or lead 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。

Email campaign/sequence performance review composite. Pulls campaign data (sends, opens, replies, bounces), reads actual email copy and subject lines, analyzes reply content (objections, positive interest, questions), and produces a diagnostic report covering quantitative metrics, copy quality, lead quality, and actionable recommendations. Tool-agnostic — works with Smartlead (MCP), Instantly, Outreach, Lemlist, Apollo, or CSV 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。

Track what key opinion leaders (KOLs) in your space are posting on LinkedIn and Twitter/X. Surfaces trending narratives, high-engagement topics, and early signals of emerging conversations before they peak. Chains linkedin-profile-post-scraper and twitter-mention-tracker. Use when a marketing team wants to ride trends rather than create them from scratch, or when a founder wants to know which topics are resonating with their audience.

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 and search Reddit posts using Apify. Use when you need to find Reddit discussions, track competitor mentions, monitor product feedback, discover pain points, or analyze subreddit content. Supports keyword filtering, time-based searches, and subreddit-specific queries.

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。

Take raw customer inputs — interview transcripts, survey responses, Slack quotes, support tickets, review excerpts — and generate a structured case study draft with problem/solution/result narrative, pull-quotes, metric callouts, and multi-format outputs (full case study, one-pager, social proof snippet, sales deck slide). Pure reasoning skill. Use when a product marketing team has customer signal but no time to write the story.

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。

Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.

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。

Take support ticket clusters, FAQ patterns, product documentation, or feature specs and generate structured help center articles with step-by-step instructions, screenshot placeholders, troubleshooting sections, and related article links. Batch mode generates multiple articles from a ticket export. Pure reasoning skill.

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 leads by scraping engagers from a competitor's top LinkedIn posts. Given one or more company page URLs, scrapes recent posts, ranks by engagement, selects the top N, extracts all reactors and commenters, ICP-classifies, and exports CSV. Use when someone wants to "find leads engaging with competitor content" or "scrape people who interact with [company]'s LinkedIn posts".

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。

Create a custom web dashboard (React + Vite + Express) inside your sandbox to visualize the agent's Turso database. The dashboard is served on port 3847 and the user sees it live in the "App" tab in Gooseworks. Use when the user asks for a dashboard, visualization, chart, metric view, or any custom UI powered by their agent's 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。

End-to-end skill that turns a single reference image into a published Gooseworks style — analyzes the image, drafts the slim style spec, renders a hero example plus 2-3 additional formats via Playwright, writes the `gooseworks-style.json` manifest, and publishes via `npx gooseworks styles publish` so other agents can discover it. Mirrors goose-graphics-create-format but for styles.

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。

Take a new feature or product update and generate the full launch kit: changelog entry, email announcement, LinkedIn post variants, in-app banner text, Twitter/X thread, and internal sales enablement one-pager. Pure reasoning skill that chains product context with audience-specific copy generation. Use when a product marketing team needs to turn a feature spec into launch-ready assets fast.

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。

Set up and run ongoing competitive intelligence monitoring for a client. Tracks competitor content, ads, reviews, social, and product moves.

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 visual branding (colors, typography, layout patterns) from a client's website and generate a style preset compatible with the HTML slides skill and a brand config JSON for the content asset creator. Uses WebFetch to read pages and analyzes CSS/HTML to identify the color palette, font pairings, and aesthetic patterns.

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 a brand kit — the canonical brand context an ad or content pipeline reads (positioning, audience, voice, standing instructions, brand-type, value-props, colors), plus manage the product list and attach product photos. Use when someone says "update my brand kit", "set my brand voice/audience", "add a product to my brand", or hands you a folder of product shots to attach. Platform-agnostic: it teaches the field model, partial-update/clear semantics, override behavior, caps and validation, and the hero-image and product-matching rules — independent of any specific 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。

Comprehensive GTM analysis of any target company. Researches what a company is currently doing across all go-to-market dimensions — content/blog, founder LinkedIn activity, SEO/traffic, hiring signals, social/community presence, customer acquisition channels, podcast appearances, review sites, competitive positioning, and partnerships. Produces a structured report identifying what's working, what's missing, and where white space exists for new strategies. Use before designing GTM strategies for a client or prospect.

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 a company or brand from its website and produce a reusable Brand Core covering products, audience, competitors, positioning, offers, messaging evidence, voice, and visual identity. Use before growth, ad, content, creator, or product work when reliable brand context is missing.

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。

Given the path to a finished content-goose ad-run folder, extract everything that defines that ad — recipe shot list, VO script, characters, voices, world, atom-skills, master mp4 — and emit a `source-sample.json` in the exact shape the `upload-ad-sample` skill writes to the Goose Ads library. Also links every character and voice to the central character library at `<repo-root>/assets/character-library/` (repo-root derived from the run-dir, not a hardcoded path), and if a character isn't in the library yet, adds it first then links. Use when the user wants to remix one of their existing ads — this skill produces the source JSON that the script-rewriting step and `remix-ad` consume.

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。