AI 智能体1 day ago
Rafter — shared ways of working for your firm
Rafter 让团队将工作流程转化为可复用的 AI 代理和技能，在现有工具中运行。
kristohb · HN
Rafter – an MCP server that shares one team's memory, skills and agents
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Rafter 让团队将工作流程转化为可复用的 AI 代理和技能，在现有工具中运行。
kristohb · HN
Rafter – an MCP server that shares one team's memory, skills and agents
独立验证 AI 生成代码，发现可利用漏洞并提供修补。
@usesecurecode · X
Free Starter is $0 forever. 3 scan credits 1 free Attacker Mode run (20 credits) Real-time SAST Dependency checking Fix previews Signing up is free and gives you scans to try it out. free&utm_content=06_start-free#pricing #vibecoding
安全连接本地MCP服务器到Claude、ChatGPT等远程AI客户端。
eladhefetz · HN
Forth MCP – give any remote AI client access to your local MCP servers
计算LLM微调和推理所需的GPU显存。
@FaiqAdzlan · X
Built a GPU VRAM calculator to try out Claude Code (#cursorfanboy). I wanted it as granular as possible so I based it off of LLMem) which really just covers fine-tuning tbh. Please tear it to shreds: GitHub:
通过调整限流规则看AI提供商如何在需求激增时分配强模型。
eliotho · HN
I built a tool showing how AI providers (should) throttle their models
估算LLM推理所需的显存、延迟、TTFT、TPOT与吞吐量。
popopanda · HN
LLM Inference Calculator – Estimate VRAM, Latency, and Throughput
从支付信号、流量趋势和搜索数据发现 SaaS 和独立开发商业机会。
lisiqi521 · V2EX
做了个独立开发机会雷达：从 Stripe / Creem 等支付与流量信号里找选题 大家好，最近看到不少「帮独立开发者找方向」的产品上线。 我之前调研产品时，积累了一些围绕独立产品的数据：新上线网站、流量变化、自然搜索需求，以及 Stripe 、Creem 、LemonSqueezy 等支付技术栈和公开可观测的支付交互信号。 这些信号当然不等于平台官方交易数据，也不能直接证明一个产品一定赚钱；但和流量、上线时间、跨月走势结合起来看，能帮助判断一个方向是否已经有真实的商业化尝试和增长迹象。 最近把这套调研工具部署到了线上： https://whattobuild.today/ 目前主要可以用来： - 发现新上线的 SaaS 、AI 工具和独立产品 - 查看流量、搜索需求和增长趋势 - 观察 Stripe 、Creem 、LemonSqueezy 等支付相关的公开信号 - 结合多维信号，把项目初步归为 Watch / Build / Skip 它更像是“缩小调研范围”的工具，不是自动选题器。最终要不要做
具有权限内核的AI代理，安全控制Shell访问并记录执行。
kurdman_007 · HN
Talos – An AI agent with a permission kernel between model and shell
对比450+个LLM API定价方案，计算实际月度成本，支持缓存和批处理定价。
u/Greywolff06 · Reddit
I built LLMPrice — a free calculator for comparing LLM API costs across 450+ pricing routes I kept running into the same problem when comparing LLM APIs: the headline token price doesn't always tell you what your actual workload will cost. Caching, batch pricing, reasoning tokens, retries, different endpoints, and OpenRouter routes can change the result quite a bit. So I built LLMPrice.com. You enter your workload once — requests, input/output tokens, caching, retries, etc. — and it com
免费 Chrome 截屏工具，支持自动光标缩放、平移和内置视频编辑。
Ashish106 · HN
Lumiko – Chrome screen recorder with automatic cursor zoom
为 AI 代理跨多个提供商路由网络搜索和数据提取，配备完整的可观测性。
yurikoif · HN
Telem – Route agent web search across providers and inspect the traces
检查您的网站是否已为ChatGPT、Perplexity和Gemini等AI搜索引擎准备就绪。
u/RockettBits · Reddit
I built a tool to check whether my websites are ready to be cited by ChatGPT, Perplexity, Gemini A lot of AI SEO tools seem to work in a similar way. They send your site to an LLM and ask it to generate a score. The result can look convincing, but it is often hard to know what the score is actually based on. I wanted to build something more reproducible with findyouraiscore.com The scoring uses fixed rules based on published research articles around GEO, RAG, citation behavior and sourc