Skip to main content
The Credible App (https://<your-org>.app.credibledata.com) is one way your team can consume published semantic models. In the Credible App, work happens inside a workspace — your personal workspace, or a shared workspace scoped to a set of packages and team members (see Creating a Workspace). Workspace landing page showing chat input, tabs for Chats, Reports, and Models

​
Chat

Type a question in the chat bar at the top of any workspace. The agent parses your question and uses the Credible Context Engine to search your published semantic models — matching phrases to governed entities (dimensions, measures, views) and indexed dimension values via their #(doc) and #(index) annotations — then constructs and executes a trustworthy Malloy query against your data. get_context tool showing phrase parsing and entity matching Each chat is saved in the workspace and visible to all members. Use the Chats tab to find previous conversations.

​
How It Works

  1. get_context — The agent parses your question into semantic phrases and calls get_context to search your published semantic models and indexed dimension values, getting back matched data entities. Match quality depends on the #(doc) descriptions and #(index) annotations in your model.
  2. execute_query — The agent constructs and runs a Malloy query using the matched entities, returning results and visualizations.
This is what makes answers trustworthy — the agent is grounded in governed definitions, not guessing column names or interpreting ambiguous schemas. And how it analyzes — the query patterns and the rigor — comes from Credible’s open-source agent skills: the same skills every Credible surface runs, curated in the open with the world’s data experts.
Published models must be indexed before chat works. Check for a green “Indexed” tag on the package page.

​
See Also

  • Build Data Apps — Build and use interactive dashboards and applications shipped with your packages
  • Build & Publish — Build and publish a model with the agent, then chat with it
  • Context Engine Overview — How phrase-matching and entity retrieval work
  • Connect your Agent — Chat with the same models from Claude, ChatGPT, Gemini, or any MCP client
  • MCP Tools — Technical details on get_context and execute_query for custom agents
  • Credible App Admin — Creating and managing workspaces