Evaluate AI behavior with LLM evals
ai-eval-engineersubagentsetup L2★0
OgenticAI/ogentic-audit ↗What it does
Manage workflow processes
Best for
Validating LLM behavior against strict criteria (structure, safety, cost) that string assertions cannot verify.
Inputs
- · CSV file path or content
- · Feature spec or user story
- · User request in natural language
Outputs
- · Structured report (JSON or markdown)
- · Severity scorecard with grades
- · Inline code comments or findings
- · Issue/ticket records
- · Result summary or action performed
Requires
- · Linear API (tickets)
Preconditions
Source files or data accessible; required context loaded
Failure modes
- · Token limit exceeded on large files
- · Input format invalid or unparseable
- · External API rate limit or downtime
Trust signals
- · Includes test suite validation