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35,708 results · Page 878 of 992

StopScroll

AI images

StopScroll is an AI thumbnail generation tool for YouTube video covers. Starting from a public YouTube link, video title, or custom prompt, it can generate multiple thumbnail options in different visual directions for creators to preview, compare, and download. Users can either paste a public YouTube URL and let the tool read available metadata, descriptions, chapters, and transcript signals to prepare cover directions, or directly enter cover text, an optional prompt, and upload a subject image. In addition to cover generation, the website also provides auxiliary tools such as YouTube thumbnail resizing, Shorts thumbnail downloading, and 4K highest-resolution thumbnail downloading. StopScroll uses a credit system, where 1 credit corresponds to 1 thumbnail generation. The materials mention two plans at approximately $0.23 per thumbnail and approximately $0.21 per thumbnail. Credits do not expire, and generation history is saved in the account. The official statement explicitly says it does not guarantee click-through rates or specific performance. The first version focuses on generating multiple cover options from a URL, title, or prompt, which can be further edited in tools such as Canva or Photoshop after downloading.

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Storybird

AI writing

Storybird is an online creation platform for writers, offering features such as creative tools, online courses, writing challenges, and reader feedback to help users improve their writing skills. According to its official website introduction, the platform's core positioning is to help users become better writers, improving their writing through course learning, participating in challenges, and receiving reader feedback. Currently, the confirmed information is relatively limited, and detailed explanations regarding its specific AI features, pricing methods, supported languages, target audiences, or platform limitations are not yet available.

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strata-bench

AI agents

STRATA-Bench is a benchmark for AI agents, with the full name Spatial-Temporal Retrieval, Alignment, Transparency & Audit. It targets the task of compiling longitudinal market intelligence (such as rent, labor, crime, wait times, etc.) from fragmented, geographically nested, and temporally incomplete evidence, examining whether agents fabricate data, silently impute missing quarters, or plot data gaps as if they were normal data. The project was built by Mohammad Movahedi, is licensed under Apache-2.0, and requires Python 3.10+. The benchmark includes a sandbox corpus, a grader, and 36 official tasks. The benchmark itself is frozen at v1.0, while tools and documentation are released as v1.1.0. Scoring focuses not on producing flashy dashboards, but on whether the agent discloses, tags, refuses, or models.

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