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.