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Replying to @IvanDataanalyst
autoapply at cart. no field, no exit.
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Replying to @CpA3A0wOsB68728
Claude设计技能三件套(Taste Skill Impeccable Emil Kowalski)完整配置 & Prompt模板 一键安装三件套(Claude Code / Cursor / Codex 通用)在项目根目录终端运行下面3条命令(一次搞定): bash # 1. Emil Kowalski(动画 动效 设计工程) npx skills add emilkowalski/skill # 2. Impeccable(23条设计指令 排版/间距/颜色/布局词汇) npx skills add pbakaus/impeccable # 3. Taste Skill(反slop 高级审美品味) npx skills add Leonxlnx/taste-skill 安装完重启Claude Code(或Cursor),输入 / 就能看到 /impeccable、/taste、Emil相关指令。2. 核心Prompt模板(直接复制喂给Claude Code) markdown 你现在同时加载了以下三件顶级设计技能,请严格按顺序使用: 1. Taste Skill(Leonxlnx/taste-skill)→ 负责整体审美品味,彻底消除AI通用slop(避免紫色渐变、Inter字体、圆角豆腐块、过度对称等) 2. Impeccable(pbakaus/impeccable)→ 负责设计词汇和精确执行(用 /polish /critique /audit 等指令打磨) 3. Emil Kowalski Skill(emilkowalski/skill)→ 负责动画、缓动、微交互和动效物理感 【工作流程要求】 1. 先用 Taste Skill 分析当前设计,指出所有slop并给出高级审美改进方向 2. 再用 Impeccable 执行精确设计指令(typography、spacing、color、layout、vertical rhythm等) 3. 最后用 Emil Kowalski 添加流畅、自然、有物理感的动画和交互 输出时必须: - 先给出「Taste Review」总结(哪里slop、为什么) - 再给出完整优化后的代码 - 最后给出「Polish Checklist」(已应用Impeccable Emil的点) 现在开始,根据以下需求生成/优化界面: [在这里粘贴你的需求或现有代码] 快速配置JSON(项目级 .claude/config.json 示例)如果你用的是Claude Code项目模式,可以在项目根目录新建 .claude/config.json(可选,增强效果): json `` { "skills": { "enabled": [ "emilkowalski/skill", "pbakaus/impeccable", "Leonxlnx/taste-skill" ], "autoApply": true }, "defaultCommands": [ "/taste review", "/impeccable polish", "/emil animate" ], "designPrinciples": "high-end, intentional, human-first, no generic AI aesthetics" } 使用建议: 安装后直接在Claude Code里输入 /impeccable polish 或 /taste review 就能秒用 推荐工作流:先用Taste Skill定调 → Impeccable打磨 → Emil Kowalski加灵魂 这套组合能把AI生成的界面从「明显AI味」直接变成「Dribbble质感」
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We can likely add that and AVWAP as indicators so they autoapply to each chart you bring up
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Local-first job hunt agent with Kuzu for the profile graph and Lance for semantic match — that's a stack I'd actually trust with my resume 🙌 Human-in-the-loop instead of blind autoapply is the right call.
I’m open sourcing JustHireMe 🚀 A local-first Agentic AI desktop app I’ve been building to make job searching more intelligent, transparent, and user-controlled. GitHub: github.com/vasu-devs/justhir… The current job search process is broken. Candidates spend hours scrolling through: stale job posts irrelevant roles spammy listings senior-only positions repeated listings across platforms jobs with almost no useful context And most AI job tools either scrape too broadly, rank opportunities like a black box, or try to automate applications without giving the user enough control. I wanted to build something different. JustHireMe is designed as a personal job intelligence workbench. Instead of blindly applying everywhere, it helps users discover better opportunities, evaluate them against their real profile, and generate tailored application materials while keeping sensitive career data local. What it can do: Ingest resume/profile data Build a local professional profile graph Discover job leads from multiple sources Filter out low-quality or irrelevant postings Score roles based on explainable fit Match jobs using graph vector search Generate tailored resumes Generate cover letters Draft cold emails Draft LinkedIn outreach messages Track leads in a local CRM-style pipeline Keep the user in control through a human-in-the-loop workflow The main principle behind the project is: More signal. More explanation. More local control. Less blind automation. The tech stack: Tauri for the desktop shell React TypeScript for the frontend Python FastAPI for the backend sidecar SQLite for local lead tracking KuzuDB for graph-based profile modeling LanceDB for vector search and semantic matching Playwright for experimental browser automation One of the biggest goals is privacy. Your resume, career history, generated documents, job leads, application notes, and API keys should not have to live on someone else’s server by default. JustHireMe is built around a local-first architecture so users can keep ownership of their data while still benefiting from modern AI workflows. Another major goal is explainability. I don’t want an AI system that just says: “This job is a good match.” I want it to explain: which skills matched which projects support the application what gaps exist why a role was filtered out why a role deserves attention what to highlight in the resume or cover letter That matters because job search is not just a productivity problem. It is personal. It affects confidence. It affects opportunity. It affects people’s careers. The project is currently in alpha, but the foundation is in place. I’m looking for contributors interested in: Agentic AI AI agents workflow automation job source adapters web scraping ranking algorithms GraphRAG vector databases semantic search resume parsing document generation local-first software privacy-first AI UI/UX testing and documentation If you’re a developer, designer, AI engineer, student, or someone who has felt the pain of modern job searching, I’d love your feedback, ideas, issues, PRs, or even just a star ⭐ Repo: github.com/vasu-devs/justhir… Let’s build a better, more transparent job search system together. #OpenSource #AgenticAI #AIAgents #RAG #GraphRAG #Python #FastAPI #ReactJS #TypeScript #Tauri #VectorDatabases #JobSearch #CareerTech #Automation #PrivacyFirst
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🎉 We launched our job hunting AI autoapply startup on product hunt today! Here's what inspired @kylefcords and I to build this tool to give job hunters superpowers:
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Replying to @bruvimtired @LidlGB
gf and i are more likely to reverse engineer the app to autoapply the coupons extract the card than to actually use it
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i've been thinking a lot lately about what my ideal programming langauge would be like now in the age of ai. you know any out there that matches this? here's my checklist: a single tool — don't need to install anything but that one tool. hell, even the language extension should be able to install the tool for me. a modern, comprehensive standard library — I want 80% of everything I want to do to be covered by the Std. Its 2026, JSON is everywhere, efficient collections are everywhere, HTTP is everywhere. A standard library should include some support for these. There can always be specialized packages out of it. a standard formatter — no questions, no knobs, just fast, ideally optimized for small diffs. an extensible linter — not just a fast one, i need a linter that i can write new lints for within my code, to help wrangle the increasing pile of slop with automated checks. agents should be able to run `tool fix` and get quick hints about how to fix up the code. ...that supports codemods! — oh yes, i want to help large refactors with little codemods across the codebase. that way agents can refactor more aggressively, faster! `tool fix` should autoapply fixes if possible an extensible LSP — not just a fast one, i need an LSP that allows packages to register new commands, and new refactors, and new hints. Something that can be tailored to the thing I'm building with ease. ...that's runnable from a CLI — and I'd like all of these capabilities to be exposed via a CLI for agents to use. Just give me `tool lsp rename-symbol ...` so agents can call it to make codebase-wide refactors procedural macros — i want to be able to make simple APIs that are verbose and descriptive and efficient, and wrap 'em up in little macros that are delightful to use. I have a feeling agents will do nightmares with this but I'm willing to give it a shot. a simple package model — i want a package model that feels intuitive and pragmatic. doesn't need to be super powerful, just give me a whole package as the unit of work. Give me common commands like `add` and `search` so the agents can find what they need quickly and get it into the project. an open package registry — i want a package registry with strong conventions about package shape, how to build it, how to generate docs, but a low-bar for publishing. Github-login might just be enough. a fast build system — i want a build system that is fast, ideally with some form of content-addressable cache that can be easily saved/shared/generationally-gc'd to make multiple agents benefit from compiled artifacts. good types™️ — (aka hindley-milner types) i know i know this is a big filter, but it's hard to give up ocaml/rust-style types once you grok the value. I'm sure I'm missing something but if you know any language that hits all these ^ let me know!
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So let me get this straigt, AI writes job posts, Candidates use AI to autoapply with AI written resumes, AI reviews the resumes, Some unlucky folks get interviewed by an AI. Full circle if you ask me.
The job market is in a bad state. Recruiters are flooded with AI-generated resumes. Countless job postings exist only to harvest data. Applicants are getting attacked by scammers (been there). People are disconnected. We need a safer space for real professional communication.
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66% ATS pass. “Selected” instantly. Not luck. Not volume. Just better optimization. Applic AI is showing what happens when resumes are built for how hiring actually works. #applicai #autoapply #ATSwins
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Scaling your job search is no longer optional, it’s strategic.
Imagine sending up to 500 tailored applications daily, without burnout. This is what Applic ai efficiency looks like. #FutureOfWork #autoapply #CareerStrategy
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personalized internet scrape for jobs autoapply is very useful imo
We’ve raised $4.1M to let AI find the right job for everyone. So today, we’re launching TAL. 3 years and 1M users on Grapevine taught us this: The internet today works for companies. Not for talent. Job boards, applications, resumes, ats. The system was built to help companies process people. But people are not pipelines. You are not a resume. You are not an application. You are not a candidate. You are talent. TAL is your talent agent.
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I automated job applications with Accomplish AutoApply Pro finds jobs applies for me while I sip coffee Built for the hackathon @accomplish_ai @wemakedevs Demo👇
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Replying to @tankots
In a world where AI can basically autoapply, it's increasingly harder to distinguish candidates. This list goes a long way, nj
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I’ve been running dart fix autoapply as a hook after response. Twice so far out of bazillion runs it happened to apply completely incorrect fixes to files CC did not even touch, that actually created 100 error lints. There must be something that make it occasionally unstable.
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HR when they see Darlyn’s name pop up again 👀 Kirro has helped him get 72 interviews in 7 months. #kirroai #interviews #autoapply
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Tired of losing track of your applications? Kirro keeps everything in one dashboard so you can stay organized, follow up easily, and focus on landing your next role. 👉 Try it now at kirro.ai #kirro #jobsearch #autoapply #careerassistant
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Apply for multiple jobs at a go without the autoapply extension. Try now and get 5 free credits. lightforth.website/app/signu…
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There’s the dream job and the energy it takes to find it. Kirro bridges that gap by matching and applying for roles that fit, while you focus on what’s next. Save time. Land interviews. Win faster. 👉 kirro.ai #kirro #jobautomation #autoapply #interview #job
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With lightfforth, you would land your next job without stress. Experience automated job application using lightforth today. signup and enjoy free cv review, interview prep and autoapply. lightforth.website/app/ai_
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Day 17 of building in public the AI agent that applies to jobs I wish I had in college. Added feature for user to pick the password that the autoapply agent uses when creating accounts on career sites when applyng on the user's behalf.
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