This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
New 60-task benchmark and reproducible scripts: Tura groups deterministic repository work—environment checks, patches, builds, tests, lint and media inspection—into reusable macros. Macro Direct passed 39/60 tasks in 969 rounds versus Codex CLI Medium at 38/60 in 3,140 rounds. Adding backward reasoning reached 48/60. Open source, with the dataset, logs and methodology published.
Hi Product Hunt — I maintain Tura. This update is about evidence, not just a token-saving claim. We ran the same 60 long-horizon tasks across Macro Direct, Macro + backward reasoning, Codex CLI Medium and High, counting failures, retries, total rounds and observed tokens. The result that surprised me: Direct nearly matched Medium's pass rate (39 vs 38) with 969 vs 3,140 rounds, while backward reasoning raised the pass count to 48 but cost more. Repo and benchmark scripts are public. I'd especially value feedback on whether cost per successful task is the right denominator.
Love how the README leads with the benchmark link instead of hype - putting reproducible evidence front and center is a rare move in this space.
honestly been wanting a coding agent that actually reads the repo before touching it, so tura scratching that itch. the open source angle is a big plus too.
The benchmark page is honestly a nice touch, basically showing your work instead of just waving around vague claims about token savings. Love that it's local and open source too.
About Tura on Product Hunt
“Macro execution for fewer coding-agent turns”
Tura was submitted on Product Hunt and earned 0 upvotes and 7 comments, placing #151 on the daily leaderboard. New 60-task benchmark and reproducible scripts: Tura groups deterministic repository work—environment checks, patches, builds, tests, lint and media inspection—into reusable macros. Macro Direct passed 39/60 tasks in 969 rounds versus Codex CLI Medium at 38/60 in 3,140 rounds. Adding backward reasoning reached 48/60. Open source, with the dataset, logs and methodology published.
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