The user switched to Hermes Agent for local LLM development due to its superior per-model tool parsi

i keep coming back to hermes agent. i've tested openclaw (bloat), opencode, claude code on local models. every time i switch away to try something new i end up back on hermes agent within a day.

it got to the point where i stopped switching and started writing pull requests instead. 3 PRs merged by tek all same day. and i'm already planning the next one. something useful for all of us.

the reason is simple. hermes agent has per-model tool call parsers, when your local model outputs a tool call the parser knows the exact format for that model. other harnesses use generic parsing that breaks on half the local models out there.

plus it auto detects your inference server. llama.cpp, vllm, lmstudio, any openai compatible endpoint, just drop the url and it resolves everything through /v1/models. zero manual config. one of my PRs. another one cleaned up telegram image handling for small models, so you can send and receive images through the hermes agent telegram bridge without wiring anything yourself.

my DMs are full of builders who switched once and never touched the other harnesses again. if your model works on another harness, it flies on hermes. and if your model feels dumb or broken, it's probably not the model.

switch the harness before you blame the weights.