we’re using “framework” intentionally because it goes beyond argument parsing. crust handles parsing, but also:
type inference across args + flags end to end
compile-time validation (so mistakes fail before runtime)
plugin system with lifecycle hooks (help, version, autocomplete, etc.)
composable modules (prompts, styling, validation, build tooling)
auto-generates agent skills and modules from the CLI definitions
so it sits a layer above a traditional arg parser like yargs or commander, closer to something like oclif, but much lighter and bun-native.
thanks for the catch, what we meant is that we’re not committing to strict stability guarantees yet, so APIs may still change as we iterate toward 1.0.
Thanks for testing this. The Bannon email from June 30, 2019 is in there (HOUSE_OVERSIGHT_029622). Good stress test idea.
Couple things happening:
Semantic search limitation: Less-famous names don't have strong embeddings, so it defaults to general connections rather than specific mentions
Keyword search gap: You're right — raw grep can catch exact names I'm missing
Shareable conversations would definitely make the tool more useful yeah.
I really like the query parameter approach over UUIDs so it would make links human-readable
On the limited dataset: Completely agree - the public files are a fraction of what exists and I should have mentioned that it is not all files but all publicly available ones. But that's exactly why making even this subset searchable matters. The bar right now is people manually ctrl+F-ing through PDFs or relying on secondhand claims. This at least lets anyone verify what is public.
On LLMs vs traditional NLP: I hear you, and I've seen similar issues with LLM hallucination on structured data. That's why the architecture here is hybrid:
- Traditional exact regex/grep search for names, dates, identifiers
- Vector search for semantic queries
- LLM orchestration layer that must cite sources and can't generate answers without grounding
Trump famously told New York Magazine in 2002: "I've known Jeff for 15 years. Terrific guy. He's a lot of fun to be with. It is even said that he likes beautiful women as much as I do, and many of them are on the younger side."
Trump and Epstein were social acquaintances in Palm Beach and New York circles during the 1990s-early 2000s. They socialized together at Mar-a-Lago and other venues
The economics are simple. When an agent guesses, it produces wrong code, failed runs, and wasted time. External context is the biggest source of those mistakes, because IDEs only index what’s in your repo. We are a complement to Cursor, ChatGPT, and Claude, not a replacement.