An advanced static analysis linter engineered to prevent logical contradictions, circular reference loops, and structural code/markdown failures within custom behavioral rule files deployed to OpenAI's autonomous agents (Dots).
As OpenAI Dots run 24/7 in cloud environments with persistent memory, corrupted rules or paradoxical commands can cause execution loops, data leaks, or complete agent freeze states. This toolkit ensures code stability before production deployment.
- 🔍 Contradiction Matrix Detection: Flags logical locks (e.g., instructing the agent to "Always use public scopes" and "Keep everything private" within the same runtime context).
- 🔄 Circular Dependency Identification: Utilizes graph theory computation to parse and catch infinite reference loops across multi-line prompt rules.
- 📦 Token & Variable Verification: Analyzes unclosed tags and corrupted bracket structure (
{{variable}}).
git clone https://github.com
cd dot-rule-validator
pip install -r requirements.txtTo run a deep analysis linting check on your OpenAI Dot rule files, execute the following script target:
python dot_validator.py examples/invalid_rules.txtFeel free to open an issue or submit a Pull Request to enrich the keywords dictionary inside the logical contradiction semantic matrix matrix.