I built a free internal linking tool using @typesafeai Jev for classifying and selecting the links.
BYOK or pay $1 to use mine. It works for up to 500 pages and gives you a CSV or JSON to pass to an LLM to implement.
ian.is/tools/internal…
An agent-first SEO and GEO CLI in Rust, with DuckDuckGo and Jev.
APAkash Priyadarshi
32
Kevin Wang
@mxfp4
everyone's making demos with Jev
but nobody is making real products
introducing lurk.so
find and monitor reddit threads to get cited by AI
> FREE
> 4000 reddit threads scanned
> email, discord, slack
only possible to give for free bc of Jev & @getanyapi
Jev dropped the price of SEO/GEO fixes by 90%
Agents that audit and fix a client's SEO/GEO used to cost us ~$250
Here's where the savings come from:
1/ 30x faster reads of Search Console and PostHog/Mixpanel data
2/ 30x faster checks of what ChatGPT searches on Bing
3/ 30x faster modeling of what users ask Gemini and Claude
4/ 30x faster scans of who ChatGPT and Claude cite
5/ 30x faster analysis of the sources behind those citations
6/ 30x faster gap analysis: why they get cited and we don't
7/ 30x faster fixes across 1,000s of pages on large client sites
8/ 30x faster sorting of which page types ChatGPT cites
9/ 20x faster creation of the pages that make ChatGPT pick you
Available in the Ryze AI app and MCP/Claude Connector, link in the 1st comment 👇
Jev killed 7 more SEO/GEO workflows 👇
1/ Assess which competitor pages to copy
-> It scores every competitor page on answer, depth, proof and freshness, then checks its rank in Google and ChatGPT to show which ones are worth copying
2/ Identify which page elements to change to get cited
-> It reads the title, meta, H1, FAQ and schema on every page and returns keep or change for each, with a confidence score
3/ Check if your pages answer what people ask AI
-> It matches real buyer questions to your best page, which shows the questions you have no page for and who AI cites instead
4/ Rate how likely each page is to get cited
-> Every URL gets a citation chance and the first fix to make, like adding a compare table
5/ Sort search terms
-> It asks "is this query from a buyer?" across the full Search Console export, so you write only for terms that convert
6/ Build the internal link map
-> For every page it checks the 15 closest candidates and links only the ones with an honest reason
7/ Verify AI-written pages
-> Each draft goes through 20 yes/no checks, and only the ones that pass reach a human
Available in the Ryze AI app and MCP/Claude Connector, link in the 1st comment 👇
I built a tool that finds App Store keywords by reading the competition, and uses Jev to judge them.
What it actually does:
1. Turns the app's own listing into a handful of search queries, with Jev filtering out the ones nobody would type.
2. Runs those searches on the App Store. Whatever ranks is the candidate pool.
3. Jev judges each candidate: is this really an alternative to the app, or does it just share a word? The lookalikes get dropped.
4. The strongest survivors become the competitor set it mines for keywords.
No competitor list to maintain, nothing hallucinated: competitors are whoever Apple already ranks, minus the ones Jev rules out.