Look up Twitter/X profiles - get bio, followers, tweets, and engagement
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Read scrapecreators-api first. Execute every operation below through the runtime it selects: the GooseWorks MCP tool in terminal-free clients, the GooseWorks CLI in a local terminal, or the direct API with the user's own key. Never assume a shell is available.
Get profile information, tweets, and engagement data for any Twitter/X account.
Uses the ScrapeCreators API through its direct GooseWorks proxy.
provider: scrapecreators
method: GET
path: /v1/twitter/profile
query:
handle: openai
provider: scrapecreators
method: GET
path: /v1/twitter/user-tweets
query:
handle: openai
User: "What has OpenAI been posting on X?"
Use the Get User's Tweets operation with handle: openai.
User: "Show me Sam Altman's recent tweets"
Use the Get User's Tweets operation with handle: sama.
User: "What's Anthropic sharing on Twitter?"
Use the Get User's Tweets operation with handle: AnthropicAI.
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Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.
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Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.
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For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.
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The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.
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Checks paid ads against the ad platform's rules (Meta, TikTok, Google, LinkedIn and others) and the brand's category rules: the copy, on-image or on-screen text, pictures and people. Rewrites what can be fixed honestly, adds the disclosures that are needed, and flags anything that needs a human or legal review, with one pass, fixed or flag line per ad and platform. Use alone when you already have the ad text or images and know where they will run; otherwise run the playbook for the job (e.g. make-static-ads, make-content, email-lifecycle).
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Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.
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