Show HN: OSS Agent I built topped the TerminalBench on Gemini-3-flash-preview

It's really interesting how much the AI harness seems to matter. Going from 48% via Google's official results to 65% is a huge jump. I feel like I'm constantly seeing results that compare models and rarely seeing results that compare harnesses.

Is there a leaderboard out there comparing harness results using the same models?

Interesting things Dirac does:

1. Uses an optimized version of Hash-Anchored edits for file editing (https://dirac.run/posts/hash-anchors-myers-diff-single-token)

2. Utilizes language's AST to decide what to fetch into context, entirely avoids large code file reads

3. Batches all operations. Does large number of reads/edits simultaneously (you can see a video demo for deepseek-v4-flash here https://www.reddit.com/r/LocalLLaMA/comments/1suhdki/tested_...)

4. Allows the model to execute code to analyze things on the fly, so the model can simply write bash/python/perl script to accomplish things where appropriate

5. A lot of context curation and opportunistic context updates, i.e. put into context anything that you are certain model would ask next

I haven't tried it, but I'm curious why you decided to implement a whole new harness over just writing extensions in pi. From whatever I've done with pi so far, the extension api is quite extensive. Hash anchored edits, for example, can definitely be implemented in pi. Anyhow, thank you for showing us your project and will be checking it out later. Cheers!

If I understand correctly, this is a heavily improved Cline fork? Does that mean features such as plan and act mode are also still there?

Interesting. Would love a comparison to pi.dev (Not Ohmypi)

How does this perform in day to day coding tasks, outside of benchmarks?

Very interesting! I've often thought static analysis could really help agents (I wrote this last summer: https://martinalderson.com/posts/claude-code-static-analysis...), but despite being hyped for LSPs in Claude Code it turned out to be very underwhelming (for many of the reasons that they can be annoying in a "real" IDE, ie static analysis starts firing mid edit and complaining and cached analysis getting stuck).

Curious to know if this has been an issue with your AST approach on larger projects?

The hash line based numbering is very interesting too (though I see on Opus 4.5+ far far fewer editing errors).

I've often thought that even if model progress stopped today, we'd still have _years_ of improvements thru harness iteration.

Stared it. will try it later. one question though, to make it simpler for me, in what tasks does this model shine, how do you improve the score? I already use some skills to cut down CC costs, like caveman, rtk cli and a few others. just want to understand

I keep trying to use dirac-cli with codex and it won't work: Error: Codex API error: Codex API request failed: 400.

Any ideas?

Can't OpenCode reach the same just developing this as a feature or plug-in? Like anchored edit?

I am a bit confused. What languages does it help with? You mention AST manipulation, so I am assuming it's not universally applicable, e.g. to Rust?

how well does it do on frontier models like Opus 4.6?

Sorry I couldn’t really figure out if this was a harness, a fine tuned model, or both. Can we use Qwen with this for example? Is the performance expected to be better in that case?

No CLI? Only VSCode extension?

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