REPOGEO REPORT · LITE

ucbepic/docetl

Default branch main · commit 953d0b3f · scanned 6/18/2026, 9:32:18 AM

GitHub: 3,836 stars · 409 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ucbepic/docetl, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition the README H1 and introductory paragraph to specify category

Why:

CURRENT

# DocETL: Declarative & Agentic Map-Reduce
...
## What is DocETL
DocETL helps you process large collections of data (structured and unstructured) with LLMs.

COPY-PASTE FIX

# DocETL: Agentic LLM-Powered ETL for Unstructured Data
...
## What is DocETL
DocETL is an open-source, agentic framework for Intelligent Document Processing (IDP) and LLM-powered ETL, transforming large, unstructured document collections into queryable tables and knowledge bases for AI applications.

mediumabout#2

Enhance the 'About' description for specificity

Why:

CURRENT

A system for agentic LLM-powered data processing and ETL

COPY-PASTE FIX

An open-source, agentic framework for Intelligent Document Processing (IDP) and LLM-powered ETL, transforming unstructured documents into queryable tables and knowledge bases for AI applications like RAG.

mediumtopics#3

Add specific topics for Intelligent Document Processing

Why:

CURRENT

agents, data, data-pipelines, document-analysis, document-processing, elt, etl, llm, python, semantic-data, unstructured-data, unstructured-data-analysis, workflow

COPY-PASTE FIX

agents, data, data-pipelines, document-analysis, document-processing, elt, etl, llm, python, semantic-data, unstructured-data, unstructured-data-analysis, workflow, intelligent-document-processing, idp

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface ucbepic/docetl

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 1×
run-llama/llama_index · recommended 1×
deepset-ai/haystack · recommended 1×
Significant-Gravitas/AutoGPT · recommended 1×
yoheinakajima/babyagi · recommended 1×

CATEGORY QUERY
How to build agentic LLM pipelines for processing large unstructured datasets efficiently?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. LlamaIndex (run-llama/llama_index)
3. Haystack (deepset-ai/haystack)
4. AutoGPT (Significant-Gravitas/AutoGPT)
5. BabyAGI (yoheinakajima/babyagi)
6. DSPy (stanfordnlp/dspy)
7. Microsoft Semantic Kernel (microsoft/semantic-kernel)
AI recommended 7 alternatives but never named ucbepic/docetl. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools help extract and transform unstructured text data into queryable tables using LLMs?
you: not recommended
AI recommended (in order):
1. LlamaIndex
2. LangChain
3. OpenAI Functions
4. Haystack
5. Microsoft Semantic Kernel
6. Unstructured.io
AI recommended 6 alternatives but never named ucbepic/docetl. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of ucbepic/docetl?
pass
AI named ucbepic/docetl explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts ucbepic/docetl in production, what risks or prerequisites should they evaluate first?
pass
AI named ucbepic/docetl explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo ucbepic/docetl solve, and who is the primary audience?
pass
AI named ucbepic/docetl explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of ucbepic/docetl. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/ucbepic/docetl.svg)](https://repogeo.com/en/r/ucbepic/docetl)

HTML

<a href="https://repogeo.com/en/r/ucbepic/docetl"><img src="https://repogeo.com/badge/ucbepic/docetl.svg" alt="RepoGEO" /></a>

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite