Exposing Hypermedia Information Graphs to LLMs#359
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- Restore Korzybski quote and trail race metaphor - Restore extended Claude thinking log evidence - Restore curiosity-driven evaluation insight - Restore guidance architecture intro paragraph - Expand summary paragraph with key techniques - Add llms.txt comparison (Stripe, Claude Code) - Align examples to CVE/security domain - Merge vector search section into Background 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Show that workflows are formal enough for mechanical translation: - Add `list` command output showing enumerable workflows - Add generated bash script demonstrating precise translation - Script shows curl/jq-based HAL navigation with error handling 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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We are in the process of replacing our existing
releases-index.jsondocument with a hypermedia graph, per #358. This spec defines an approach and testing methodology for efficiently exposing the graph to LLMs. The results are positive and illuminating. It turns out that initial design goals of the graph per already well-aligned with the LLM cost model. Additional opportunities for alignment were discovered through the testing process and became part of the proposed model.This is the intended user experience:
Note: This works with claude.ai, ChatGPT, and direct API use. Works best with claude.ai. You can try that actual prompt or one like it.
Prototype LLM entrypoints for graph:
llms.txtis to some degree the standard model as an LLM on-ramp to a custom system. A JSON variant was developed as an alternative to requiring markdown. The addition of a second entrypoint isn't competition between the formats, but an interest in motivating an LLM to use JSON as both data and guidance router. The spec goes into much more detail on the role ofllms.jsonand how it relates toindex.jsonas the core data entrypoint to the graph.