
AI Social Media Post Generator - Plan, Design, Write & Publish | Chrombyte
生成品牌社交媒体帖子、标题和图像,可直接发布到 Instagram、Facebook 和 LinkedIn。
@chrombyte · X
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23 projects

生成品牌社交媒体帖子、标题和图像,可直接发布到 Instagram、Facebook 和 LinkedIn。
@chrombyte · X

InfluenceGrid 评分你的社交内容,追踪竞争对手,推荐下一步发布策略。
@InfluenceGridIQ · X


用CompetitorSearch描述竞争对手,获得实时网络搜索的并排分析和档案。
@Wagner__kent · X
Good day Gainframe, built CompetitorSearch — describe your competitors, get a live web-searched side-by-side breakdown + full dossier on each. Selling it outright (Mistral+Tavily+Vercel, 156 visits/19 searches/10 users). Happy to walk you through it.

分析文本以识别 10 种有毒和 7 种健康的沟通模式。
@WEreFrame · X
Underrated...well I wouldn't say that because I'm just starting, but overlooked maybe. The impact on humanity will be noticed across the globe. Stop reacting. Start reFraming.

发现各平台热门内容创意,用你的风格转化为原创作品。
@davidtostscale · X

每周自动追踪竞争对手的定价、功能和消息变化。
@Caden1Fenn · X
Intel Brief — tracks what your competitors change (pricing, features, positioning) and delivers it to your inbox weekly. Built for indie SaaS founders.

检查论文中的AI写作和抄袭,在提交到Turnitin前自查。
PaperCheck — 论文提交前自查工具,提供 Turnitin 查重 + AI 写作检测报告,帮助学生在正式提交前发现问题

为会议前的参与者生成有来源的研究简报。
@dhanushkenkiri · X
Building If you ever wanted to know about someone online this is your go to place. Also, let's connect!

记录交易、追踪权益曲线和性能的交易日志应用。
@NimraWeb3 · X
So I vibe coded my own with Lovable TradeBook. Log trades w/ session, killzone, model, grade, R:R + screenshots, track multiple accounts, get a real dashboard (equity curve, win streaks, pair/session breakdowns). Demo: GitHub:

管理学术会议:提交和审阅论文、处理日程安排和注册。
@harryjwang · X
I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age