
策引 - 系统化投资分析平台 | 策略回测与组合管理工具
创建模拟投资组合,进行策略回测和AI市场分析。
策引 — 全球市场技术分析工具,可以创建多个市场的模拟组合并做深度回测分析。同时正在开发 AI Agent 功能,可帮助用户使用大模型自动生成基于不同交易策略的模拟组合。
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创建模拟投资组合,进行策略回测和AI市场分析。
策引 — 全球市场技术分析工具,可以创建多个市场的模拟组合并做深度回测分析。同时正在开发 AI Agent 功能,可帮助用户使用大模型自动生成基于不同交易策略的模拟组合。

用英文描述加密交易策略来回测它们。
@torquant · X
building Torquant. you build and backtest trading/investment strategies using only natural languange

使用Python或可视化块构建交易机器人,在真实数据上回测,并在排行榜上竞争。
@CodeBullapp · X
Building CodeBull. A platform where you build trading bots with Python or visual blocks, backtest them on real-world market data, and compete against other users’ strategies. Zero risk. Just learn trading by building.

Repolog 扫描网站的 SEO、性能、安全和 AI 就绪情况。
petersas · HN
We gave our website-audit tool an MCP server so agents can fix issues

为AI应用提供MCP服务器、REST API和行级安全的后端服务平台。
u/bob__io · Reddit
What we learned from trying to turn vibe-coded prototypes into production SaaS applications Founder here. While developing MCPBackend, we noticed a major difference between generating a convincing application demo and building a maintainable SaaS product. AI coding tools are increasingly capable of generating interfaces, routes and even initial application logic. But a production application still needs: a reliable data model authentication and authorization backend validation

自动QA智能体测试网页和移动应用,发现流程和漏洞,重放测试场景。
@AbdullahYusufY · X
Here is ours We are developing autonomous QA agents feel free to check it out.

比较AI模型在多个领域的基准评估成绩和排行榜。
davidtsong · HN
Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities

为现代团队自动化负载测试,无需复杂设置或手动脚本编写。
@GorodkovVi85373 · X
- load testing made easy even without enginnering team. Faster, cheaper, distributional

AEE 是一个开源控制平面,对 AI 代理的每个操作进行授权、监控和验证。
eli-labz · GitHub
Agent-Execution-Partnership Agent Execution Partnership AEE is an open-source control plane that ensures every AI agent action is authorized before it runs, observable while it runs, and verifiable after it completes.

让AI模型通过3D动画展现香蕉植物的完整生命周期来比较性能。
fran-mora · HN
I gave 5 AI coding agents one prompt: grow a banana plant through its whole life in three.js: sprout, leaves, flower, fruit, rot, then pups that restart the loop. It's deceptively simple and yet very hard to get right from procedural code: you have to write working three.js and understand how the plant is actually built; how it hangs, ages and decays. Get the biology wrong and the code renders something weird. These are agents, not bare models (Claude Code and Codex for now). They can use tools, including playwright to check their work and improve it.

通过AI简历筛选和结构化面试进行技术候选人招聘。
@__singhritwik · X

在 leaderboard 上按官方基准对比 AI 大模型的性能排名
fcten · V2EX
做了一个大模型 leaderboard 网站 最近一个月 CodeX 疯狂送重置,token 根本用不完,顺手做点东西。 地址:[知行录]( https://leaderboard.cn/) 排行依据主要为模型官方基准测试成绩。非主观排名。 数据会持续更新。如果有点用,欢迎各位 v 友收藏~