REPOGEO REPORT · LITE

approximatelabs/sketch

Default branch main · commit 7a3a0345 · scanned 5/22/2026, 10:02:53 PM

GitHub: 2,284 stars · 120 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

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 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 approximatelabs/sketch, 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 README H1 to emphasize in-dataframe, interactive AI

Why:

CURRENT

Sketch is an AI code-writing assistant for pandas users that understands the context of your data, greatly improving the relevance of suggestions. Sketch is usable in seconds and doesn't require adding a plugin to your IDE.

COPY-PASTE FIX

Sketch is an AI code-writing assistant that integrates directly into your pandas DataFrames, providing real-time, context-aware code suggestions and data analysis from natural language. Unlike general AI assistants or IDE plugins, Sketch offers an in-memory, interactive experience tailored specifically for pandas users, making data exploration and cleaning faster and more intuitive.

mediumtopics#2

Refine repository topics for better categorization

Why:

CURRENT

ai, codex, copilot, data, data-science, dataframe, datasketch, datasketches, df, ds, gpt3, lambdaprompt, pandas, python, sketches, tabular-data

COPY-PASTE FIX

ai, codex, copilot, data, data-science, dataframe, df, ds, gpt3, lambdaprompt, pandas, python, tabular-data, interactive-data-analysis, dataframe-ai, natural-language-processing-data, data-exploration

lowhomepage#3
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://approximatelabs.github.io/sketch/
```

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 approximatelabs/sketch

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

GitHub Copilot

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

GitHub Copilot · recommended 1×
ChatGPT · recommended 1×
Google Colaboratory · recommended 1×
Tabnine · recommended 1×
jupyterlab/jupyter-ai · recommended 1×

CATEGORY QUERY
How can I get AI assistance for writing pandas code in data analysis workflows?
you: not recommended
AI recommended (in order):
1. GitHub Copilot
2. ChatGPT
3. Google Colaboratory
4. Tabnine
5. Jupyter AI (jupyterlab/jupyter-ai)
6. Ploomber (ploomber/ploomber)
AI recommended 6 alternatives but never named approximatelabs/sketch. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Need a tool to generate Python data cleaning and analysis code from natural language.
you: not recommended
AI recommended (in order):
1. ChatGPT Advanced Data Analysis
2. Google Gemini Advanced
3. Microsoft Copilot
4. DataChat
5. PandasAI (gventuri/pandas-ai)
6. LIDA (microsoft/lida)
AI recommended 6 alternatives but never named approximatelabs/sketch. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
Suggestion:
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 approximatelabs/sketch?
pass
AI named approximatelabs/sketch explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts approximatelabs/sketch in production, what risks or prerequisites should they evaluate first?
pass
AI named approximatelabs/sketch 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 approximatelabs/sketch solve, and who is the primary audience?
pass
AI named approximatelabs/sketch 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 approximatelabs/sketch. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

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

HTML

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

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approximatelabs/sketch — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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