REPOGEO REPORT · LITE

potpie-ai/potpie

Default branch main · commit 8c2d2437 · scanned 6/24/2026, 7:22:59 AM

GitHub: 5,469 stars · 636 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 potpie-ai/potpie, 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's opening paragraph to clearly state its category

Why:

CURRENT

Potpie turns your entire codebase into a **knowledge grapha structural index of every file, class, and function, capturing all their relationships and what each part of the code does in context of everything else. AI agents built on this graph can reason about your code with the precision of someone who wrote it - from debugging to feature development.

COPY-PASTE FIX

Potpie is an AI agent framework that transforms your codebase into a rich knowledge graph, enabling AI agents to understand, reason about, and develop features within large codebases with human-like precision.

highabout#2

Update the repository description to be more explicit about its function

Why:

CURRENT

Spec-driven development for large codebases

COPY-PASTE FIX

An AI agent framework that builds a knowledge graph of your codebase, enabling AI agents to understand, reason about, and develop features in large codebases.

mediumtopics#3

Add more specific topics related to AI for codebases

Why:

CURRENT

agents, ai-agents, ai-agents-framework, artificial-intelligence, developer-tools, devtools, generative-ai, knowledge-graph, rag

COPY-PASTE FIX

agents, ai-agents, ai-agents-framework, artificial-intelligence, developer-tools, devtools, generative-ai, knowledge-graph, rag, code-analysis, code-intelligence, ai-for-code, codebase-ai, developer-ai-agents

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 potpie-ai/potpie

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Cursor

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Cursor · recommended 1×
GitHub Copilot Chat · recommended 1×
OpenAI's GPT-4 · recommended 1×
Aider · recommended 1×
CodiumAI · recommended 1×

CATEGORY QUERY
How can I use AI agents to understand and develop features in a large codebase?
you: not recommended
AI recommended (in order):
1. Cursor
2. GitHub Copilot Chat
3. OpenAI's GPT-4
4. Aider
5. CodiumAI
6. SWE-agent
7. Codeium
AI recommended 7 alternatives but never named potpie-ai/potpie. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools build a knowledge graph from my codebase for AI-driven development?
you: not recommended
AI recommended (in order):
1. CodeQL (github/codeql)
2. Understand
3. LSIF
4. lsif-go (sourcegraph/lsif-go)
5. lsif-tsc (sourcegraph/lsif-tsc)
6. lsif-clang (sourcegraph/lsif-clang)
7. Neo4j (neo4j/neo4j)
8. ArangoDB (arangodb/arangodb)
9. OpenGrok (oracle/opengrok)
10. Kythe (kythe/kythe)
11. Sourcegraph (sourcegraph/sourcegraph)
AI recommended 11 alternatives but never named potpie-ai/potpie. 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 potpie-ai/potpie?
pass
AI named potpie-ai/potpie explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts potpie-ai/potpie in production, what risks or prerequisites should they evaluate first?
pass
AI named potpie-ai/potpie 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 potpie-ai/potpie solve, and who is the primary audience?
pass
AI named potpie-ai/potpie explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/potpie-ai/potpie.svg)](https://repogeo.com/en/r/potpie-ai/potpie)

HTML

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

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potpie-ai/potpie — 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