/goal

An autonomous research paper reproduction agent for Grok Build.

Description

/goal is an iterative agentic workflow for Grok Build that reproduces research papers from scratch. It accepts an arXiv link or PDF, extracts methodology and target metrics, and runs an autonomous loop of implementation, testing, and reflection until results match the original paper, delivering a runnable repo and detailed report.

Descriptions, tags, and model credits may be AI-generated or inferred from public sources and can be incomplete or wrong. Learn more.

Details

Why this is interesting: A sophisticated autonomous agentic workflow that handles complex planning, execution, and iterative self-correction…
Attributed to: @tetsuoai
Built with: Grok 4.7
Tags: #autonomous-agent #research #reproducibility #grok-build

Discovered: X
First posted: X · Oct 4, 2026
Listed: Added 1h ago
Build: Strong
Models: Moderate

Prompt

/goal Reproduce the results of the paper below and do not stop until the metrics match.

Paper: paste the arXiv link or attach the PDF.
Target: the specific result to reproduce, for example the headline accuracy on the benchmark and split the paper reports.

Plan first. Read the paper and extract the method, architecture, datasets, training and evaluation setup, hyperparameters, and the exact number you are aiming for. Write that target number at the top of report. md before you write any code.

Implement the method cleanly. Build an evaluation harness that computes the same metric on the same benchmark and split the paper uses. Wire that harness into a hook so it re-grades on every change and you always have a live number to chase.

Loop with memory. After each run, compare your number to the target. When there is a gap, write one specific hypothesis for the cause in report. md, whether data prep, tokenization, a hyperparameter, the eval protocol, or seeds, then test that single hypothesis and rerun. Never repeat a hypothesis that already failed. Every attempt builds on the last.

Generate your own sanity checks beyond the paper to catch silent bugs in data loading and metric computation. A number that looks right for the wrong reason is the failure mode to hunt.

Done means your metric lands within a stated tolerance of the target on a clean rerun. If a gap remains after real effort, do not fudge it. Document the most likely causes with the evidence you gathered.

Deliver a runnable repo, report. md comparing target versus achieved with every hyperparameter, and the full attempt log.

Source

Explore

Agents / Skills

/goal

An autonomous research paper reproduction agent for Grok Build.

bytetsuo

Description

Descriptions, tags, and model credits may be AI-generated or inferred from public sources and can be incomplete or wrong. Learn more.

Details

Why this is interesting: A sophisticated autonomous agentic workflow that handles complex planning, execution, and iterative self-correction…
Attributed to: @tetsuoai
Built with: Grok 4.7
Tags: #autonomous-agent #research #reproducibility #grok-build

Discovered: X
First posted: X · Oct 4, 2026
Listed: Added 1h ago
Build: Strong
Models: Moderate

Prompt

/goal Reproduce the results of the paper below and do not stop until the metrics match.

Paper: paste the arXiv link or attach the PDF.
Target: the specific result to reproduce, for example the headline accuracy on the benchmark and split the paper reports.

Generate your own sanity checks beyond the paper to catch silent bugs in data loading and metric computation. A number that looks right for the wrong reason is the failure mode to hunt.

Deliver a runnable repo, report. md comparing target versus achieved with every hyperparameter, and the full attempt log.

Source

/goal

Description

How it grew

/goal

Description

How it grew