RRepoGEO

REPOGEO REPORT · LITE

adrida/tracer

Default branch main · commit c89d06c6 · scanned 6/17/2026, 3:57:04 AM

GitHub: 562 stars · 46 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 adrida/tracer, 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 opening to clarify LLM routing focus

    Why:

    CURRENT
    # TRACER

**Trace-Based Adaptive Cost-Efficient Routing**

Most LLM-based classification pipelines use a large language model for every single input.
    COPY-PASTE FIX
    # TRACER: LLM Routing & Cost Optimization

**Trace-Based Adaptive Cost-Efficient Routing**

TRACER is an **LLM routing and cost optimization library** designed to replace 90%+ of your LLM classification calls with a traditional ML model. Unlike code tracing tools, TRACER learns from your LLM's classification *traces* to build a self-improving policy with formal parity guarantees.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-optimization, llm-routing, cost-reduction, machine-learning, classification, ai-ml, python
  • mediumhomepage#3
    Add the official project homepage

    Why:

    COPY-PASTE FIX
    https://tracerml.ai

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 adrida/tracer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. Hugging Face Optimum · recommended 1×
  3. ONNX Runtime · recommended 1×
  4. NVIDIA TensorRT · recommended 1×
  5. OpenVINO · recommended 1×
  • CATEGORY QUERY
    Seeking ways to cut LLM inference costs for classification tasks while maintaining performance.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Optimum
    2. ONNX Runtime
    3. NVIDIA TensorRT
    4. OpenVINO
    5. Hugging Face Transformers
    6. DistilBERT
    7. TinyBERT
    8. MobileBERT
    9. BERT
    10. RoBERTa
    11. PyTorch
    12. TensorFlow
    13. Logistic Regression
    14. XGBoost
    15. OpenAI API
    16. Anthropic API
    17. RoBERTa-base
    18. ELECTRA-small

    AI recommended 18 alternatives but never named adrida/tracer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to efficiently route LLM classification requests to cheaper traditional ML models?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI Function Calling
    3. Anthropic Tools
    4. Hugging Face Transformers
    5. AWS Step Functions
    6. AWS Lambda
    7. SageMaker Endpoints
    8. Google Cloud Vertex AI Pipelines
    9. FastAPI
    10. Microsoft Azure Machine Learning Pipelines
    11. Azure Functions

    AI recommended 11 alternatives but never named adrida/tracer. 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 adrida/tracer?
    pass
    AI named adrida/tracer explicitly

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

  • If a team adopts adrida/tracer in production, what risks or prerequisites should they evaluate first?
    pass
    AI named adrida/tracer 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 adrida/tracer solve, and who is the primary audience?
    pass
    AI named adrida/tracer 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
adrida/tracer — RepoGEO report