AI-powered search & scraping | 16x more affordable API, built for devs and AI agents Explore at https://xitter.cf/t.co/L3W1RHE1Js | SN22 on Bittensor

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Joined January 2025
Small Python scripts, each one a real job your agent can do. For developers, marketers and analysts. Each one uses the Desearch API and links to its source. One a day for the next few weeks. Link on LinkedIn.
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Honest question for builders: when your agent gives you an answer, do you open its sources?
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One agent task: "What has been published about open source AI agent frameworks since September 1?" One Desearch web search call with a start date and page text. Every result came back inside the date range, with the full page text. #searchAPI
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Give Desearch crawl a URL it can't fetch and it now tells you plainly that the URL is invalid. Less guessing when your agent hits a bad link. #searchAPI
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The replies under a post often say more than the post itself. Here's how to pull replies to any public X post as structured JSON with one call 🧵
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Add context with GET /twitter/post for the original post and GET /twitter/post/retweeters for who reposted it.
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Full walkthrough with curl and a Python reply digest:
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Builder tip: one Desearch web search call can ask for page text and a publish-date window together. Fresh pages, full text, one request. #searchAPI
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Most web agents run the same loop: find pages, then read them. With Desearch that is two GET calls. Here's the whole pattern 🧵
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Every billable response carries X-Desearch-Cost-Usd and X-Desearch-Usage-Count headers, so your agent can log what each search and each page cost.
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Full walkthrough with curl and a Python tool that returns page text next to its source URL:
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Need results from a specific window? Set a start and end date on Desearch web search and keep results inside that publish range. #searchAPI
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Want an agent or dashboard to follow an Instagram hashtag? You need three calls: find the accounts, pull the posts, read the comments. All public data, all JSON 🧵
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Bonus: count the hashtags across results and you see which neighboring tags your audience uses. It's an easy way to widen a monitor.
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Full guide with curl and a Python script that runs the whole flow:
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