Who is traceburn for?

traceburn is an open-source project built for AI developers and researchers.

Yes — traceburn is open source under the MIT license and free to use.

What platforms does traceburn run on?

traceburn runs on the command line. It can also be self-hosted.

Is traceburn still maintained?

The GitHub repository shows 10 commits in the last 90 days.

traceburn is developed by TommyTranX.

When did traceburn launch?

traceburn first shipped in 2026.

Is traceburn open source?

Yes — traceburn is open source under the MIT license, developed on GitHub.

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traceburn

Name: traceburn
Author: TommyTranX

PyPIInfrastructure

traceburn is an open-source, local-first tracer and efficiency profiler designed for AI agent workflows. It enables developers to analyze cost and latency using flamegraphs, perform deterministic replay, compare runs, and detect inefficiencies, all stored in a single SQLite file. Ideal for AI developers seeking detailed observability and optimization tools.

Open SourceMITCLISelf-hosted

Visit PyPI

Overview

6 features

In the LLM eval & observability space, traceburn takes a focused approach. It focuses on profiling and analyzing the efficiency and cost of AI agent workflows locally. It is built as an open-source project for AI developers and researchers. The project is open source (MIT). It ships for the command line, and it can be self-hosted.

Behind traceburn is TommyTranX, and it first shipped in 2026. Development happens publicly on GitHub with 10 commits in the last 90 days. Among its 6 catalogued features are cost profiling, latency flamegraphs, and deterministic replay.

Summary written by a language model from the project’s public pages.

Cost profiling
Latency flamegraphs
Deterministic replay
Run diffs
Waste detection
SQLite storage

Built with & integrations

Runs on

CLISelf-hosted

Trust & compliance

License

MIT

Verified signals

HTTPSOpen SourceFree tierGitHubActive maintenance

Indexing history

What PulseGate has recorded for this listing

Indexed8 Jul · 03:52 UTC
traceburn verified against its public source
Source: PulseGate · Open

Frequently asked questions about traceburn

What is traceburn?: Traceburn focuses on profiling and analyzing the efficiency and cost of AI agent workflows locally. It is catalogued under LLM eval & observability on PulseGate.
Who is traceburn for?: traceburn is an open-source project built for AI developers and researchers.
Is traceburn free?: Yes — traceburn is open source under the MIT license and free to use.
What platforms does traceburn run on?: traceburn runs on the command line. It can also be self-hosted.
Is traceburn still maintained?: The GitHub repository shows 10 commits in the last 90 days.
Who makes traceburn?: traceburn is developed by TommyTranX.
When did traceburn launch?: traceburn first shipped in 2026.
Is traceburn open source?: Yes — traceburn is open source under the MIT license, developed on GitHub.

At a glance

Platforms: Cli
Languages: English
Open source: Yes (GitHub)
License: MIT
First seen: 8 Jul 2026
Built for: AI developers and researchers
Model: Open source
Solves: Profiling and analyzing the efficiency and cost of AI agent workflows locally.

Registered as

GitHub: TommyTranX/traceburn
PyPI: traceburn

Developer

TommyTranX

Solo developer

GitHub

Open source

View on GitHub

Stars: 0
Forks: 0
Open issues: 0
Last commit: 8 Jul 2026
Commits 90d: 10
Contributors: 1
Authorship: Solo
Default branch: main

Index record

Identity confidence: Low · 64
Indexed: 8 Jul 2026
Lifecycle: Alive
First seen: Jul 2026
Last seen: 8 Jul 2026

Identity audit (12)

Slug: traceburn-pypi-org
Lifecycle last checked: 8 Aug 2026
Verification state: Indexed for public listing
Listing state: Listed: yes
Index status: Included in index
Latest evidence snapshot: 8 Jul 2026
Timeline basis: Indexed-at chronology (no inferred launch/funding milestones).
Name from: Written by a language model from the project's public pages.
Category from: Assigned by a language model.
Summary from: Written by a language model from public pages.
Languages from: Detected by a language model from page content.
Canonical URL: https://pypi.org/project/traceburn

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