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tracelint
Lint your agent's trace — catch bugs your evals miss
A deterministic linter for agent runs — reads the execution trace and flags structural bugs (ignored errors, schema violations, loops) with evidence. No LLM judge.
Hey Product Hunt 👋 I'm Ashwin, maker of tracelint.
This started with a failure mode that kept nagging at me: an agent calls charge_card, the tool comes back with a failure, and the agent just… keeps going and tells the customer their order shipped. The final answer reads perfectly — so the eval suite passes, the LLM-judge nods, and the bug ships anyway. The chat summary looks fine while the run was already wrong.
tracelint checks the run, not the summary. It reads the agent's execution trace — what it actually did — and flags structural defects deterministically: ignored tool errors, schema-violating calls, hallucinated arguments, loops, duplicate side effects (the double-charge). Each finding points at the exact trace lines and returns a CI exit code. No second model ever judges it — for this class of bug a judge is the wrong tool; the defect is decidable by looking at the trace.
The principle that emerged while building it: abstain rather than guess. Only structurally-provable defects fail CI; heuristic signals stay advisory, shown with their evidence; and it always discloses what it couldn't check — so a clean report is honestly clean, not just empty.
It reads OpenTelemetry/OpenInference, LangSmith, Langfuse, and OpenAI traces, and there's a keyless demo to try it in ~1 minute.
Genuine ask: if you build agents, send me one real trace and I'll run tracelint on it and tell you what it finds. I want to know what it catches — and where it falls short.
About tracelint on Product Hunt
“Lint your agent's trace — catch bugs your evals miss”
tracelint was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #160 on the daily leaderboard. A deterministic linter for agent runs — reads the execution trace and flags structural bugs (ignored errors, schema violations, loops) with evidence. No LLM judge.
On the analytics side, tracelint competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how tracelint performed against the three products that launched closest to it on the same day.
Who hunted tracelint?
tracelint was hunted by Ashwin Ugale. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of tracelint including community comment highlights and product details, visit the product overview.
Ashwin Ugale