RRepoGEO

REPOGEO REPORT · LITE

0x676e67/ninja

Default branch main · commit 2aa7bdeb · scanned 5/28/2026, 3:57:40 AM

GitHub: 1,689 stars · 290 forks

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 0x676e67/ninja, 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 main heading and opening statement

    Why:

    CURRENT
    # ninja

Reverse engineered `ChatGPT` proxy
    COPY-PASTE FIX
    # ninja: A Reverse-Engineered Proxy for ChatGPT and OpenAI APIs
  • mediumreadme#2
    Add a 'Why Ninja?' section to the README

    Why:

    COPY-PASTE FIX
    ## Why ninja?

`ninja` stands out as a reverse-engineered proxy specifically for ChatGPT and OpenAI APIs, offering features like API key acquisition, email/password authentication, and a very small memory footprint, making it suitable for self-hosted, low-resource environments.
  • lowreadme#3
    Clarify the project's status in the README

    Why:

    CURRENT
    > Project has ended.
    COPY-PASTE FIX
    > Note: This project has ended active development, but remains functional as a reverse-engineered proxy for ChatGPT and OpenAI APIs.

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 0x676e67/ninja
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Proxy (by Pake)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Proxy (by Pake) · recommended 1×
  2. OpenAI-Forward-Proxy (by songquanpeng) · recommended 1×
  3. Nginx with Lua/OpenResty · recommended 1×
  4. Caddy with Caddyfile/Plugins · recommended 1×
  5. Traefik with Middleware · recommended 1×
  • CATEGORY QUERY
    Need a self-hosted solution to proxy AI chat services, handling user authentication.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Proxy (by Pake)
    2. OpenAI-Forward-Proxy (by songquanpeng)
    3. Nginx with Lua/OpenResty
    4. Caddy with Caddyfile/Plugins
    5. Traefik with Middleware
    6. Kong Gateway
    7. Apache APISIX

    AI recommended 7 alternatives but never named 0x676e67/ninja. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a low-resource proxy server for large language model interactions.
    you: not recommended
    AI recommended (in order):
    1. Nginx
    2. Caddy (caddyserver/caddy)
    3. HAProxy
    4. Envoy Proxy (envoyproxy/envoy)
    5. Traefik (traefik/traefik)

    AI recommended 5 alternatives but never named 0x676e67/ninja. 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 0x676e67/ninja?
    pass
    AI named 0x676e67/ninja explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts 0x676e67/ninja in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 0x676e67/ninja 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 0x676e67/ninja solve, and who is the primary audience?
    pass
    AI named 0x676e67/ninja 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 0x676e67/ninja. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/0x676e67/ninja.svg)](https://repogeo.com/en/r/0x676e67/ninja)
HTML
<a href="https://repogeo.com/en/r/0x676e67/ninja"><img src="https://repogeo.com/badge/0x676e67/ninja.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

0x676e67/ninja — 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