Synaplan
기업을 위한 오픈소스 AI 플랫폼
아직 감지된 업데이트가 없습니다. GitHub 릴리스가 나오면 여기에 보입니다.
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기Agent skill for clearer landing pages, conversion and SEO audits, and verified launches.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다.
README 전문 보기 ↗Launch Check is a set of instructions for your coding agent, not a hosted audit service or a one-command CLI. It uses the repository, browser, and connected accounts you give the agent. It separates what it checked from what it could not verify.
Paste this into an agent chat after installation:
$launch-check audit https://whoownswhat.xyz/ for conversion and SEO.
Tell me what is clear, what is confusing, and which fixes matter first.
Check the visible CTAs, mobile layout, technical SEO, sitemap, and footer.
Show evidence and mark anything you could not verify. Do not change the site.
You can also ask it to build, research, implement, or launch. For a full release, name the repository, hosting project, and domain, and explicitly ask it to publish. See the complete usage guide for copyable prompts for every mode.
Copy the whole skills/launch-check folder, including its references and assets, into your agent's skills directory:
Codex: ~/.agents/skills/launch-check/
Claude Code: ~/.claude/skills/launch-check/
Use your agent's skill selection syntax, such as $launch-check in Codex or /launch-check in Claude Code. Then paste one of the prompts above. The skill has no mandatory paid service or runtime dependency. Browser, repository, Search Console, and analytics access are needed only for checks or changes that use them.
Already installed? Say “Update launch-check from GitHub to the newest version” in your coding agent, or run the included updater. It checks the main branch, backs up older installed copies, and updates on --apply.
These are projects from avo42. They show different kinds of pages and products the skill has helped build or check.
| Project | What it does |
|---|---|
| WhoOwnsWhat | Shared ledger for co-founders to split project costs, track asset ownership, and hand things over cleanly. My latest project, still in development. |
| MakeSquishy | Free tool for kids to design, print, and fold paper squishies. |
| PadelTune | Personal padel training plans for strength, mobility, and match prep. |
| ReadNext | Helps pick one book to read next from an overflowing want-to-read shelf. |
| PlateWeek | Turns a food video into recipes and a practical shopping list. |
| Armando | Client management playbook and follow-through for agencies and consultancies. |
| AI Shift Field Guide | Plain-language guide to AI shifts in software, with a checklist for testing product ideas. |
| AI Markets, explained | A practical reading of AI spending, adoption, and where new products may fit. |
The default research path uses accessible, attributable sources. The agent checks intent and the actual search results, then turns promising topics into page briefs. Numeric volume or difficulty appears only when a connected source supplies it. DataForSEO can add live keyword and SERP data, but it is optional and may have its own cost; the skill does not pretend that it is connected by default.
A brief now separates why someone searched from what the leading pages let them do. The agent opens leading organic results, records each URL and rank, and reports the confirmed format mix alongside volume and organic keyword difficulty when those metrics are available. It then recommends a guide, comparison, calculator, tool, or no page based on the evidence and what the product can actually deliver. For example, a query about splitting startup costs might need an explanation and a calculator. If pages cannot be inspected, their formats stay unverified and the recommendation is a hypothesis.
Mock layout only: the pictured formats were invented to show the report shape. A real run must inspect and cite the ranked pages.
For search discovery, the launch workflow checks canonicals, robots.txt, generated sitemaps, and Google/Bing submission when the right accounts are available. IndexNow can notify participating engines about page changes. None of these steps guarantees indexing or ranking.
I have been iterating on the public repo since late September 2026. Suggestions and real-world edge cases are welcome in GitHub Issues.