RRepoGEO

REPOGEO REPORT · LITE

langchain-ai/openevals

Default branch main · commit e8cf345b · scanned 5/9/2026, 4:12:02 PM

GitHub: 1,047 stars · 95 forks

AI VISIBILITY SCORE
28 /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
2 / 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 langchain-ai/openevals, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    llm-evaluation, llm-testing, generative-ai, langchain, python, typescript, ai-testing, evaluation-framework, prompt-engineering
  • highreadme#2
    Reposition the README H1 and opening paragraph

    Why:

    CURRENT
    # ⚖️ OpenEvals

Much like tests in traditional software, evals are an important part of bringing LLM applications to production. The goal of this package is to help provide a starting point for you to write evals for your LLM applications, from which you can write more custom evals specific to your application.
    COPY-PASTE FIX
    # ⚖️ OpenEvals: Readymade Evaluators for LangChain LLM Applications

OpenEvals provides a collection of ready-to-use evaluators, designed to simplify testing and quality assurance for your Large Language Model (LLM) applications built with LangChain. Much like tests in traditional software, these evaluators are crucial for bringing LLM applications to production, offering a starting point for robust evaluation.
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://python.langchain.com/docs/guides/evaluation/openevals/

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 langchain-ai/openevals
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Argilla
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Argilla · recommended 1×
  2. Surge AI · recommended 1×
  3. Scale AI · recommended 1×
  4. ROUGE · recommended 1×
  5. BLEU · recommended 1×
  • CATEGORY QUERY
    How can I effectively evaluate the quality and performance of my LLM applications?
    you: not recommended
    AI recommended (in order):
    1. Argilla
    2. Surge AI
    3. Scale AI
    4. ROUGE
    5. BLEU
    6. METEOR
    7. BERTScore
    8. LangChain Evaluation
    9. DeepEval
    10. Ragas
    11. MLflow
    12. Giskard
    13. Robustness Gym
    14. Prometheus
    15. Grafana
    16. Datadog
    17. OpenTelemetry
    18. UserTesting
    19. Optimizely
    20. Google Optimize
    21. Split.io
    22. LaunchDarkly

    AI recommended 22 alternatives but never named langchain-ai/openevals. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools are available for automating evaluation of large language model outputs?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Ragas (explodinggradients/ragas)
    3. DeepEval (confident-ai/deepeval)
    4. Arize AI (Phoenix) (Arize-AI/phoenix)
    5. Weights & Biases (W&B Prompts)
    6. Humanloop
    7. OpenAI Evals (openai/evals)

    AI recommended 7 alternatives but never named langchain-ai/openevals. 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 langchain-ai/openevals?
    pass
    AI did not name langchain-ai/openevals — likely talking about a different project

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

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

Subscribe to Pro for deep diagnoses

langchain-ai/openevals — 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