I switched from OpenCode to Pi and there was a big improvement in terms of tool calling performance and I find the experience less buggy.
OpenCode has also seemed to have disappeared from https://openrouter.ai/apps/category/coding
OpenCode has also seemed to have disappeared from https://openrouter.ai/apps/category/coding
> a lot of apps run 100% of traffic through openrouter while for us it's a small subset
> but companies we were trying to work with used openrouter as a source of truth on popularity so they thought products that were much smaller were bigger than us
That's not because OpenCode is bad, but because Pi is good. I can say the same about Claude vs pi.
I would love to learn how LSP helps you. I did various basic evals with LSP and I did not find it to improve the agent performance at all. Maybe on newer models this gets better because they are now RLing with LSP in the context, but at least in the past having a commit hook that runs lints and typecheck at the end, is more token efficient than having every edit be injected extra LSP results. You are almost guaranteed to be wasting tokens since partial edits are unlikely going to result in type checks passing.
(Disclaimer: I work on Pi)
It sounds a lot like you are focused on using Pi as a OpenAI/Anthropic wrapper when that isn’t your audience. (Hint: raw token usage is less of a concern).
It's for using lsp to do things like symbol renames. It's cheaper to call an LSP server to do those kind of simple refactors than to spend tokens on the model doing it.
It can also use LSP to build context without having to grep around a ton. You don't have to grep and hten pull lines and make guesses for a function. You just ask the LSP for it.
How helpful all that is is heavily dependent on the quality of the language server so usefulness is varies wildly between languages
Is OpenCode pushing the LLM into doing these refactors via LSP? I found that making these refactors with ast-grep is quite efficient.
> It can also use LSP to build context without having to grep around a ton. You don't have to grep and hten pull lines and make guesses for a function. You just ask the LSP for it.
I guess I was not particularly successful with having the agent actually do that. I think what fff is attempting to do (with fuzzy expansion of slightly inaccurate greps) results in better results to me, but even that is debatable.
To be fair, we do not have evals for this today, but we're generally looking into token efficiency and how likely models are at using tools the right way, and we did not find a ton of evidence of LSP helping, even for finding data.
But I would love to see some sessions from people where they have success with LSP data for either refactoring or looking up, because this would be super useful to better understand out blind spots.
Maybe they haven't been taught to do so or it's not integrated into the system prompt or the tools but all of them only ever use the LSP to read files/symbols.
Every harness I've used will happily just call the edit tool over and over or do a find and replace via sed or programatically call a python/perl script rather than rename a symbol via other means.
Having come from Claude code, I was a bit shocked that both seem to allow edits by default with no confirmation dialog.
One IIRC allows you to enable it in config and the other needs a plugin.
There are confirmation dialogs in OpenCode. You can configure them using the permission config, same as Claude Code. Having said that, as a general rule, none of these harnesses are safe to run on your local file system.
There may be differences based on whether the command is under the directory you're running OpenCode from vs some other directory...
Like the 'top apps' in my private openrouter.ai activity usage is opencode with 55.1M tokens
The bottom of the public apps leaderboard is 'kern agent' with 150 million tokens
if there are 2 other people like me, opencode should be on here somewhere
(edit: user shiggity points out https://github.com/anomalyco/opencode/issues/11926#issuecomm..., they asked to be removed from the ranking)