RRepoGEO

REPOGEO REPORT · LITE

MagnivOrg/prompt-layer-library

Default branch master · commit 737bc728 · scanned 6/2/2026, 4:03:20 AM

GitHub: 765 stars · 90 forks

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 MagnivOrg/prompt-layer-library, 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
  • hightopics#1
    Add more specific topics for LLM observability and prompt management

    Why:

    CURRENT
    gpt, machine-learning, openai, prompt, prompt-engineering, python
    COPY-PASTE FIX
    gpt, machine-learning, openai, prompt, prompt-engineering, python, llm-observability, prompt-monitoring, prompt-versioning, llm-tracing, prompt-evaluation, mlops
  • highabout#2
    Update the repository description to reflect the full platform value

    Why:

    CURRENT
    🍰 PromptLayer - Maintain a log of your prompts and OpenAI API requests. Track, debug, and replay old completions.
    COPY-PASTE FIX
    🍰 PromptLayer - The Python client for PromptLayer, a platform to version, test, and monitor every prompt and agent with robust evals, tracing, and regression sets.
  • mediumreadme#3
    Clarify the library's role as the official client for the PromptLayer platform in the README's opening

    Why:

    CURRENT
    This library provides convenient access to the PromptLayer API from applications written in python.
    COPY-PASTE FIX
    This is the official Python client library for PromptLayer, the comprehensive platform designed to help you version, test, and monitor every prompt and agent with robust evals, tracing, and regression sets.

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 MagnivOrg/prompt-layer-library
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PostgreSQL
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PostgreSQL · recommended 2×
  2. langfuse/langfuse · recommended 1×
  3. Helicone · recommended 1×
  4. OpenTelemetry · recommended 1×
  5. jaegertracing/jaeger · recommended 1×
  • CATEGORY QUERY
    How can I log and track all my OpenAI API calls for debugging?
    you: not recommended
    AI recommended (in order):
    1. Langfuse (langfuse/langfuse)
    2. Helicone
    3. OpenTelemetry
    4. Jaeger (jaegertracing/jaeger)
    5. Prometheus (prometheus/prometheus)
    6. Grafana (grafana/grafana)
    7. Logtail
    8. Datadog
    9. Sentry (getsentry/sentry)
    10. PostgreSQL
    11. MongoDB (mongodb/mongo)

    AI recommended 11 alternatives but never named MagnivOrg/prompt-layer-library. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good solutions for versioning and monitoring prompt templates in Python?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. MLflow
    3. Weights & Biases Prompts
    4. DVC
    5. Git
    6. Jinja2
    7. PostgreSQL
    8. SQLite
    9. Streamlit
    10. Dash
    11. pandas
    12. PromptLayer
    13. Vellum

    AI recommended 13 alternatives but never named MagnivOrg/prompt-layer-library. 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 MagnivOrg/prompt-layer-library?
    pass
    AI named MagnivOrg/prompt-layer-library explicitly

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

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

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

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MagnivOrg/prompt-layer-library — 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