Small businesses often write their own landing pages, prices and emails, and have nobody to show them to first. A real focus group costs a lot and takes weeks, so most skip testing. This kit offers a cheap, fast first pass instead.

You describe a decision and supply customer evidence. The kit builds a panel of customer composites, each with a long, sourced dossier. Each persona reads your draft alone, in its own context, so they can't influence each other. You get their separate reactions, a synthesis that keeps the disagreements, and a score using weights you approve. It can also write three rewrites and retest them.

The README is frank that these are composites, not real customers, and the output is directional evidence only. It asks you to log predictions and later real outcomes so you can calibrate how far to trust the panel. Its cost and time comparison with focus groups is labeled an unmeasured estimate.

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Semrush and Ahrefs charge monthly fees for large suites that many people only partly use. OpenSEO is a smaller, focused alternative. It pulls its data from DataForSEO, and you pay that provider directly for what you use rather than paying a subscription.

You can run it yourself with Docker on your own machine, or on Cloudflare for team or internet-facing use. There is also a hosted version at $10/month. The README says the hosted service adds a 28% markup on DataForSEO requests, so self-hosting costs slightly less.

It also exposes an MCP server, so AI agents such as Claude Code, OpenClaw and Hermes can read your SEO data directly. Agent skills are reusable workflows that guide the agent through SEO tasks. You can write your own skills or fork the code to change the tool.

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Checking many stocks every day means reading prices, charts and news by hand. This project automates that. You list the tickers you follow. Each day it pulls market data and news, asks an LLM to read them, and writes a report for each stock.

Each report has a conclusion, a score, a trend read, suggested buy and sell levels, risk warnings and catalysts. A summary goes to WeChat Work, Feishu, Telegram, Discord, Slack or email. It can also write a market-wide recap. Free data sources (AkShare, Baostock, YFinance) work with no setup, though the README says they can be unreliable. It suggests token-based sources for steadier data.

You can fork the repo and let GitHub Actions run it on a schedule, run it locally or in Docker, or use the built-in web workspace. The workspace adds report history, backtesting, portfolio tracking and a chat page for follow-up questions using built-in strategies. The README says it is for study and research, not investment advice.

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Posting to many social networks by hand is slow, and hosted schedulers often charge per channel, post or team member. Postiz lets you plan posts on a calendar, publish them to channels such as Instagram, LinkedIn, X, TikTok, YouTube, Reddit, Bluesky and Mastodon, and look at how they performed.

It is a TypeScript monorepo: a Next.js front end, a NestJS back end, Prisma with PostgreSQL by default, Temporal for workflows, and Redis. You can run the open-source edition on your own server, or use the paid Postiz Cloud. The README says both have the same core features, and the self-hosted one has no limits on channels, posts or team members.

The main trade-off is setup. When you self-host, you create your own developer apps on each social platform and wait for their approval, which the README says can take weeks for Meta, YouTube and TikTok. Postiz also offers a public API, an MCP server and a CLI, plus n8n and Make.com integrations and a Node SDK, so agents and automations can schedule posts too.

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