Hermes Agent · Available since release 0.7.0
Know when your agent breaks before your users do
Connect and register your Hermes agent, benchmark it, and see exactly what is failing: tool-call accuracy, skill coverage, goal completion. Catch regressions, fix what matters, fine-tune what works.
How it works
Connect, benchmark, fix.
BenchGen evaluates the full run of your agent, not just the final answer, and turns it into a score you can compare over time.
01 / CONNECT
Connect and register your agent.
Hermes agents can be connected to BenchGen and registered, so they can be selected and evaluated alongside other models.
02 / BENCHMARK
Run it through digital-twin environments.
Each run is recorded as a State, Action, Tool Response, Outcome and Reward trajectory and scored on five quality dimensions.
03 / FIX
See exactly what is failing.
Failure patterns with concrete examples. Decide which failures need a harness fix, which need a fine-tune, and which to discard.
How Hermes improves
Harness fixes change behaviour. Fine-tuning changes the model.
BenchGen helps you choose.
Start with the cheap, instant layer. Move to weights only when the same failure keeps coming back.
Layer 1: Harness (skills, memory, routing, guardrails)
- ·Works with any model, instant
- ·No GPU required
- ·Fixes prompt-level and tool-use failures
Layer 2: LoRA fine-tuning
- ·Updates weights of open-weight models
- ·Trains on filtered, clean trajectories
- ·Fixes model-level failures
BenchGen: measures both
- ·Scores every run on five dimensions
- ·Shows which failures recur across tasks
- ·Filters out failed runs before training
FAQ
Common questions from Hermes developers
Start evaluating
Your agent is already doing the work.
Start measuring it.
Any OpenAI-compatible endpoint can also be benchmarked directly, without registering an agent.