RRepoGEO

REPOGEO REPORT · LITE

Helicone/helicone

Default branch main · commit 4df16a30 · scanned 6/24/2026, 2:32:02 AM

GitHub: 5,854 stars · 608 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
65 /100
Needs work
Category recall
1 / 2
Avg rank #4.0 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 Helicone/helicone, 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 the repository description to include "AI Gateway" functionality

    Why:

    CURRENT
    🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
    COPY-PASTE FIX
    🧊 Open source LLM observability platform and AI Gateway. Monitor, evaluate, experiment, and route LLM requests with intelligent fallbacks. YC W23 🍓
  • mediumtopics#2
    Add specific topics related to LLM routing and API gateway functionality

    Why:

    CURRENT
    agent-monitoring, analytics, evaluation, gpt, langchain, large-language-models, llama-index, llm, llm-cost, llm-evaluation, llm-observability, llmops, monitoring, open-source, openai, playground, prompt-engineering, prompt-management, ycombinator
    COPY-PASTE FIX
    agent-monitoring, analytics, evaluation, gpt, langchain, large-language-models, llama-index, llm, llm-cost, llm-evaluation, llm-observability, llmops, monitoring, open-source, openai, playground, prompt-engineering, prompt-management, ycombinator, llm-gateway, api-gateway, llm-routing, model-routing, intelligent-routing, automatic-fallbacks
  • mediumreadme#3
    Add a concise introductory sentence to the README after the main heading

    Why:

    COPY-PASTE FIX
    Helicone provides a comprehensive open-source solution for AI engineers, combining robust LLM observability with a powerful AI Gateway for intelligent routing and model management.

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 Helicone/helicone
Avg rank
#4.0
Lower is better. #1 = top recommendation.
Share of voice
6%
Of all named tools, what % are you?
Top rival
LangChain Plus (now LangSmith)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain Plus (now LangSmith) · recommended 1×
  2. Arize AI · recommended 1×
  3. Weights & Biases (W&B Prompts) · recommended 1×
  4. openai/evals · recommended 1×
  5. OpenAI's usage dashboard · recommended 1×
  • CATEGORY QUERY
    How can I monitor LLM costs, latency, and performance for my AI applications?
    you: #4
    AI recommended (in order):
    1. LangChain Plus (now LangSmith)
    2. Arize AI
    3. Weights & Biases (W&B Prompts)
    4. Helicone ← you
    5. OpenAI Evals (openai/evals)
    6. OpenAI's usage dashboard
    7. Anthropic's console
    8. Prometheus (prometheus/prometheus)
    9. Grafana (grafana/grafana)
    Show full AI answer
  • CATEGORY QUERY
    What tools offer intelligent routing and automatic fallbacks for diverse large language models?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Evals
    2. LiteLLM
    3. LangChain
    4. Vellum
    5. Portkey.ai
    6. Helicone.ai
    7. NGINX
    8. AWS API Gateway
    9. AWS Lambda

    AI recommended 9 alternatives but never named Helicone/helicone. 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 Helicone/helicone?
    pass
    AI named Helicone/helicone explicitly

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

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

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

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Helicone/helicone — 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