Show HN: Ktx – Open-source executable context layer for data agents

(github.com)

47 points by lucamrtl7 hours ago

4 comments

  • tarun_anand4 hours ago
    How does this compare with Wren 2.0, OpenVikings etc
    • lucamrtl4 hours ago
      Thanks for the question! Just to complete - OpenVikings is context&#x2F;memory infrastructure for agents. ktx is analytics context for data agents specifically. So they&#x27;re in different categories<p>The way we think about the space: there&#x27;s a &quot;semantic layer&quot; side (Cube, dbt MetricFlow, Wren&#x27;s engine) that compiles correct SQL but is hand-authored. And a &quot;company brain&quot; side (OpenViking, Glean, wikis) that indexes prose but can&#x27;t query data warehouses safely. ktx is built to be both halves at once - a YAML semantic layer and a searchable wiki of business definitions, cross-linked (each wiki page references the metrics it explains) and auto-maintained
    • andreybavt4 hours ago
      Hey, ktx maintainer here! Great question, we actually have quite a bit in common with Wren, they&#x27;re in the same category. The main difference is that with Wren you author the semantic model (write MDL) and it executes SQL through its own Rust engine (similar to Cube as well). ktx instead builds the context for you - ingesting definitions already in dbt, Looker, Metabase, and Notion, auto-detecting joins and fan&#x2F;chasm traps, flagging contradictions. It also builds both : the SL and wiki that accumulates and maintains free-form tribal knowledge (that’s also interlinked with ktx SL)
  • modus-tollens4 hours ago
    How are you measuring the accuracy? Are you running this against any benchmarks?<p>I see this covers a file based approach, was there ever a consideration for a graph based approach?<p>For business context, how do you handle context that evolves over time?
  • MadGodInc1 hour ago
    Interesting approach. Context management for agents is an underexplored area. I&#x27;ve been looking at similar problems - the key challenge is keeping token usage low while giving the agent enough context to be useful. Tiered retrieval (facts first, full text only whenneeded) seems to work well in practice.
    • andreybavt1 hour ago
      Agreed, in addition to this I&#x27;d say it&#x27;s better to spend tokens once while ingesting the sources and storing the canonical reusable definition rather than having agents do the full exploration over and over again
  • qasimkhan072 hours ago
    [dead]