Skill Claude CodeCodex
Use when adding a new subpackage under back/core/, back/objects/, or agents/ — e.g. a new graph DB engine, W3C parser, industry importer, reasoning module, or domain class. Enforces the checklist defined in .cursor/07-project-conventions.mdc.
Skill Claude CodeCodex
Use when the user adds, changes, or refactors an LLM agent under src/agents/ — or anything that goes through Foundation Model API or an MLflow-traced LLM call. Mandatory under CNS §3.5 and .cursor/12-ai-feature-lifecycle.mdc. Walks the SPEC → dataset → eval-harness → impl → re-eval sequence.
Skill Claude CodeCodex
Use after any code change (feature, fix, refactor, review fixup) to update /changelogs/YYYY-MM-DD.log and run the test suite. Mandatory post-change routine — see .cursorrules.
Skill Claude CodeCodex
Use when the user asks for a code review, asks to "review the code", or requests review of a feature/PR/branch. Runs the OntoBricks review checklist defined in .cursorrules.
Skill Claude CodeCodex
Use when the user asks to deploy, ship, release, or push OntoBricks to Databricks. Wraps the Databricks Asset Bundle deploy for the FastAPI app and the MCP server, with the bootstrap-perms safety net described in README.md.
Skill Claude CodeCodex
Use when the user asks to "refactor", restructure, clean up, simplify, deduplicate, extract, or reorganize code. Enforces the Martin Fowler discipline defined in src/.codingrules.md and .cursor/08-testing-and-deployment.mdc.
Cursor rule Cursor
You are an expert in Python, FastAPI, Jinja2, Databricks SDK, Databricks REST APIs, RDF/OWL/SPARQL/SHACL standards, graph databases, and graph viewer engineering.
Cursor rule Cursor
OntoBricks is a Python FastAPI web application designed to run as a Databricks App. It provides ontology management, graph viewer engineering, and metadata governance tools on top of Databricks Unity Catalog.
Cursor rule Cursor
Transforms Databricks Unity Catalog tables into a materialized knowledge graph, with ontology design and reasoning exposed as tools via MCP.
Cursor rule Cursor
The codebase is split into five top-level packages under src/.
Cursor rule Cursor
Cursor rule "Code Style and Structure" from databrickslabs/ontobricks, covering code style and structure and code smells and preferred refactorings.
Cursor rule Cursor
Backend.
Cursor rule Cursor
Cursor rule "Project Conventions" from databrickslabs/ontobricks, covering project conventions, subpackage patterns (reference), adding a new subpackage checklist, init.py conventions (detailed) and merge safety (feature branch → develop).
Cursor rule Cursor
Cursor rule "Testing and Deployment" from databrickslabs/ontobricks, covering testing and deployment, documentation rules and working style for refactoring.
Cursor rule Cursor
The Databricks Apps deploy runs uv run --frozen and installs verbatim from uv.lock. Two failure modes have broken deploys before, so treat the lockfile as a release artifact.
Cursor rule Cursor
All application errors go through the centralized hierarchy in back/core/errors/. A global exception handler in shared/fastapi/main.createapp() translates them into a uniform ErrorResponse JSON body.
Cursor rule Cursor
This file documents the actual design conventions in the codebase, not aspirations. The two structural rules ("no inline CSS/JS in templates", "shared assets under front/static/") live in 05-code-style-and-structure.mdc § Frontend (HTML/CSS/JS). This file covers visual language, components, naming and asset wiring.
Cursor rule Cursor
This rule is the gate that closes the 5-agents-zero-eval gap. The companion path of least resistance is .claude/skills/ai-feature/SKILL.md.
Cursor rule Cursor
This repository uses modular Cursor rules with scoped .mdc files (YAML frontmatter for name/priority/scope). See .cursor/.
Instructions file CodexOpenCode
AGENTS.md instructions for databrickslabs/ontobricks: Pointer file for AI coding agents (Codex, Gemini CLI, OpenAI Agents, etc.).
Instructions file
Claude Code instructions for databrickslabs/ontobricks, covering claude.md — operating contract for ontobricks, imported canonical rules, claude-only additions, skills (auto-invoked by description) and databricks-related work.
Agent
The assistant MUST proactively avoid the following pitfalls when creating or modifying any ontology. Check each applicable rule before proposing or applying changes, and warn the user if a requested change would introduce one of these pitfalls.