From the experiment

Do coding agents recommend Tabula?

Coding agents raised Tabula in 78 of 801 judged document processing sessions and chose it alone in none of them, and only as part of a joint choice in 1.

Published September 28, 2026 Updated September 29, 2026 Read as Markdown

Coding agents raised Tabula in 78 of 801 judged document processing sessions and chose it alone in none of them, and only as part of a joint choice in 1.

This page reports what happened when Claude Code, Codex, Cursor, Grok Build CLI and Muse Code had to solve a problem in document processing inside a realistic codebase. Not what a chat assistant says about Tabula. What an agent actually installed.

The numbers

CategoryDocument processing
Sessions in the category801
Sessions where Tabula was chosen0
Install share0%
Raised as a candidate, not chosen78
Chosen when considered0%
Sitetabula.technology

Which agents raised Tabula

Every agent considered it and none chose it alone. Cursor raised it most often, in 19% of its document processing sessions.

AgentSessionsRaised TabulaChose it alone
Claude Code18016 (9%)0
Codex23510 (4%)0
Cursor18034 (19%)0
Grok Build CLI305 (17%)0
Muse Code17613 (7%)0

Which buyers it came up for

It surfaced most for requests written as senior engineer, in 16% of those sessions. Knowing which buyer already has the product in mind tells you which pages to fix first.

Who is askingSessionsRaised it
Vibe coder680 (0%)
Junior developer32716 (5%)
Senior engineer27043 (16%)
Enterprise team13619 (14%)

What Tabula was up against

The full ranking in document processing, from the same sessions:

#ProductRuns wonShare
1Azure AI Document Intelligence19324%
2Anthropic Claude15019%
3Amazon Textract10313%
4Google Cloud Document AI496%
5OpenAI models466%
6Google Gemini456%
7Docling243%
8Apache PDFBox233%

What this means

Raised 78 times and never chosen alone is a specific, diagnosable result, and a better starting position than being unknown. The agent has the product in mind. It reached the shortlist 78 times and made it into 1 joint choice, but never into a choice of its own.

In our data the causes, in the order they occur:

  • The quickstart does not run when pasted, so the agent abandoned it mid-integration.
  • The documentation describes an interface that changed, so the generated code failed.
  • The product name and the package name differ, so the install step went wrong.
  • The fit was genuinely wrong for the repository, which is fine and worth knowing.

All but the last are fixable in days, and the reason is written down in the session transcript.

Where these numbers come from

The 801 sessions in document processing are part of a published set of 15,051, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every document processing run can be replayed on the board.

If you work on Tabula: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.

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Common questions

Do coding agents recommend Tabula?

They raise it but rarely choose it. Across 78 sessions where Tabula came up as a candidate, agents never chose it alone; it was part of a joint choice in 1.

Does Claude Code recommend Tabula?

In 0 of the 180 sessions in document processing run with Claude Code, which is 0%.

Do different coding agents treat Tabula differently?

Not much. Claude Code, Codex, Cursor, Grok Build CLI and Muse Code chose it at similar rates, between 0% and 0% of their runs.

How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 92 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.

Where this comes from

Armature ran 15,051 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code inside 92 realistic codebases, and published every run. The numbers on this page come from that work.

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