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llms.txt files for AI agents before competitors own the discovery layer.

Searchable directory for llms.txt files when general search engines could index these.
AI agent developers and API documentation maintainers
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llms.txt files for AI agents before competitors own the discovery layer.
This is someone treating a CV as structured data rather than a PDF: resume.json, evidence.json, availability.json, agent-card.json and a curated llms.txt are all exposed plus schema.org JSON-LD. Nice touches include GitHub Actions that validate links and push an IndexNow update on every commit — practical engineering to get content noticed by crawlers and agents. It’s a focused, well-implemented experiment, but its usefulness depends on broader adoption or tooling that consumes these bespoke conventions.
Operationalizing biomedical knowledge for drug discovery is a genuinely useful angle.
This is the kind of curated index I wish existed yesterday: agent pages, config format examples, SDK links and two named protocols (MCP/ACP) all collected in one place, plus a weekly-ranked table of models with context-length notes. It feels like real curation rather than linkspam, but the site leans on lists and scores — show the benchmark methodology, reproducible tests or interactive demos and the rankings would become trustable rather than just convenient.
Transparent AI bot posture tracking, but 'what bots touch you' is already solved by uBlock Origin.
llms.txt tree structure lets agents navigate context instead of dumping everything.