AI Developer Tool / Agent framework
A reference implementation for intent-execution separation in LLM agents. The project uses a typed intent layer (SIF) over domain vocabularies, with a deterministic execution layer and demo domains for legal and veterinary workflows.
The page clearly describes an AI-related developer project with a concrete agent pattern, visible architecture, stack, and demo domains. It gives enough evidence for a public listing and appears useful to AI builders exploring constrained agent execution and ontology-driven workflows.
The crawl cuts off before the README finishes, so the page does not fully show setup details, example flows, or the complete REST surface. It is also not yet clear how much of the experimental approach is production-ready versus research-oriented.
Last evaluated 22 days ago. Current rank #848. Down 1 spot in the rankings.
Runtime safety net for LLM agents that detects runaway token growth, classifies failure patterns, and suggests fixes without extra LLM calls. The project includes a Rust core, Python SDK, examples, benchmarks, and benchmark claims across multiple models and runs.
OpenWorkers is a thesis-focused research assistant that searches literature, verifies citations, critiques ideas, and produces structured research support without writing the prose for the student.
Local-first federated search for AI agents that queries transcripts, files, a knowledge graph, a vector store, and the web, then merges results with trust-weighted ranking.
An AI-powered pipeline that turns diarized podcasts or interviews into YouTube-ready videos with semantic B-roll, burned-in subtitles, optional TTS voice replacement, and YouTube publishing.
