RRepoGEO

REPOGEO REPORT · LITE

fendouai/CodexSaver

Default branch main · commit fe44dc10 · scanned 6/10/2026, 10:46:54 PM

GitHub: 590 stars · 43 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 fendouai/CodexSaver, 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
  • highabout#1
    Update repository description

    Why:

    CURRENT
    Make Codex cheaper without making it dumber with DeepSeek.
    COPY-PASTE FIX
    An intelligent router for OpenAI Codex and other LLMs, optimizing API costs by delegating routine tasks to cheaper models like DeepSeek without sacrificing quality.
  • highlicense#2
    Add a LICENSE file and mention it in the README

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen license text. Add a line to the README, e.g., 'This project is licensed under the [License Name] License - see the LICENSE file for details.'
  • mediumtopics#3
    Expand repository topics

    Why:

    CURRENT
    codex, deepseek
    COPY-PASTE FIX
    llm-routing, cost-optimization, api-management, generative-ai, deepseek, openai-codex

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 fendouai/CodexSaver
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-3.5 Turbo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-3.5 Turbo · recommended 1×
  2. Anthropic Claude 3 Haiku · recommended 1×
  3. Google Gemini 1.5 Flash · recommended 1×
  4. Llama 3 8B · recommended 1×
  5. Mistral 7B · recommended 1×
  • CATEGORY QUERY
    How can I reduce the cost of large language model API calls for routine tasks?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-3.5 Turbo
    2. Anthropic Claude 3 Haiku
    3. Google Gemini 1.5 Flash
    4. Llama 3 8B
    5. Mistral 7B
    6. AWS SageMaker
    7. Google Cloud Vertex AI
    8. Hugging Face Inference Endpoints
    9. Azure OpenAI Service
    10. Cohere Command R+

    AI recommended 10 alternatives but never named fendouai/CodexSaver. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool to intelligently route coding tasks to different AI models for cost optimization.
    you: not recommended
    AI recommended (in order):
    1. langchain (langchain-ai/langchain)
    2. llamaindex (run-llama/llama_index)
    3. Microsoft Azure AI Studio
    4. OpenAI Assistants API
    5. Hugging Face Transformers Agents (huggingface/transformers)
    6. AWS API Gateway
    7. NGINX (nginx/nginx)

    AI recommended 7 alternatives but never named fendouai/CodexSaver. 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 fendouai/CodexSaver?
    pass
    AI named fendouai/CodexSaver explicitly

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

  • If a team adopts fendouai/CodexSaver in production, what risks or prerequisites should they evaluate first?
    pass
    AI named fendouai/CodexSaver 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 fendouai/CodexSaver solve, and who is the primary audience?
    pass
    AI named fendouai/CodexSaver 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 fendouai/CodexSaver. 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)
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HTML
<a href="https://repogeo.com/en/r/fendouai/CodexSaver"><img src="https://repogeo.com/badge/fendouai/CodexSaver.svg" alt="RepoGEO" /></a>
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fendouai/CodexSaver — 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