RRepoGEO

REPOGEO REPORT · LITE

traceloop/openllmetry

Default branch main · commit fc33f1c1 · scanned 6/20/2026, 5:56:07 AM

GitHub: 7,211 stars · 1,004 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
67 /100
Needs work
Category recall
1 / 2
Avg rank #3.0 when recommended
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 traceloop/openllmetry, 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
    Strengthen README's immediate value proposition for GenAI monitoring

    Why:

    CURRENT
    The current README structure places badges and links before the core value proposition.
    COPY-PASTE FIX
    Add the following sentence immediately after the main title/H1: "OpenLLMetry provides the essential open-source tools to track, analyze, and optimize the performance and behavior of your GenAI applications, ensuring reliability and efficiency in production."
  • mediumtopics#2
    Refine topics for GenAI monitoring

    Why:

    CURRENT
    artifical-intelligence, datascience, generative-ai, good-first-issue, good-first-issues, help-wanted, llm, llmops, metrics, ml, model-monitoring, monitoring, observability, open-source, open-telemetry, opentelemetry, opentelemetry-python, python
    COPY-PASTE FIX
    Add `genai-monitoring`, `llm-monitoring`, `ai-observability` to the existing topics.
  • lowcomparison#3
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a section titled 'Why OpenLLMetry? / Comparison' that explains its unique value proposition, especially compared to proprietary LLM monitoring tools and generic OpenTelemetry solutions, emphasizing its open-source, vendor-agnostic, LLM-specific instrumentation.

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
1 / 2
50% of queries surface traceloop/openllmetry
Avg rank
#3.0
Lower is better. #1 = top recommendation.
Share of voice
5%
Of all named tools, what % are you?
Top rival
Grafana
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Grafana · recommended 2×
  2. Prometheus · recommended 2×
  3. Arize AI · recommended 1×
  4. LangSmith · recommended 1×
  5. Weights & Biases Prompts · recommended 1×
  • CATEGORY QUERY
    How can I monitor the performance and behavior of my generative AI applications?
    you: not recommended
    AI recommended (in order):
    1. Arize AI
    2. LangSmith
    3. Weights & Biases Prompts
    4. WhyLabs
    5. whylogs (whylabs/whylogs)
    6. OpenReplay
    7. Grafana
    8. Prometheus
    9. Datadog
    10. New Relic

    AI recommended 10 alternatives but never named traceloop/openllmetry. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools provide OpenTelemetry-based observability for large language models?
    you: #3
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenLLMetry ← you
    4. OpenTelemetry Python SDK
    5. Prometheus
    6. Grafana
    7. Jaeger
    8. Zipkin
    9. SigNoz
    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 traceloop/openllmetry?
    pass
    AI named traceloop/openllmetry explicitly

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

  • If a team adopts traceloop/openllmetry in production, what risks or prerequisites should they evaluate first?
    pass
    AI named traceloop/openllmetry 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 traceloop/openllmetry solve, and who is the primary audience?
    pass
    AI named traceloop/openllmetry explicitly

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

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traceloop/openllmetry — 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