Structure and schema
Detects empty or truncated answers and validates JSON or YAML formats.
A system for evaluating, scoring and verifying what LLMs produce: mechanical checks first, then an LLM judge, with a gate that regenerates until the answer passes.
Detects empty or truncated answers and validates JSON or YAML formats.
Checks code blocks for syntax errors, unclosed fences and TODO placeholders, with Ruff-based linting.
Verifies that every [SOURCE N] points to a real, non-empty document and that retrieval was relevant.
An LLM looks for contradictions and gaps. If the score fails, the gate regenerates with the findings.
Every finding rolls up into one verdict: a score from 0.0 to 1.0 and a status of passed, warning or failed.
A continuous streaming chat with the LLM.
Captures complete logs for every call: generator prompt, judge prompt and temperature.
--continue feeds the model with past conversational history.
Evaluate a written .md document against defined criteria.
Simulate verification from a question and a local knowledge base (chunks.json).
Retry up to N rounds with the findings until a passing score or the limit is reached.
Trade speed for assurance per task.
| Profile | Parameters | Use case |
|---|---|---|
| Latency | annotate / auto-judge | Real-time responses, live chat |
| Balanced default | gate · T 0.7 · 2 rounds | General purpose, standard usage |
| Quality | gate · T 0.95 · 3 rounds · 2nd judge | Mission-critical, maximum reliability |