RRepoGEO

REPOGEO REPORT · LITE

dillionverma/llm.report

Default branch main · commit 343b8ee7 · scanned 5/17/2026, 4:07:33 PM

GitHub: 1,019 stars · 89 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
33 /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
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 dillionverma/llm.report, 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
    Reframe the 'unmaintained' notice to highlight project value for new contributors

    Why:

    CURRENT
    > [!CAUTION]
> Attention: llm.report is no longer actively maintained. This project was unable to find a sustainable business model, and the founders have moved on to other projects. If you are interested in maintaining or further developing this project, message me on twitter
    COPY-PASTE FIX
    > [!CAUTION]
> Attention: llm.report is no longer actively maintained. This project was unable to find a sustainable business model, and the founders have moved on to other projects. If you are interested in maintaining or further developing this project, message me on twitter.

Despite its current maintenance status, llm.report remains a fully functional, open-source platform for OpenAI API logging, cost analysis, and prompt improvement, ideal for those looking to fork or contribute.
  • mediumreadme#2
    Add 'comprehensive' and 'self-hostable' to the README's introductory sentence

    Why:

    CURRENT
    llm.report is an open-source logging and analytics platform for OpenAI: Log your ChatGPT API requests, analyze costs, and improve your prompts.
    COPY-PASTE FIX
    llm.report is a comprehensive, open-source, and self-hostable logging and analytics platform for OpenAI: Log your ChatGPT API requests, analyze costs, and improve your prompts.
  • lowtopics#3
    Add more specific topics related to LLM observability and cost management

    Why:

    CURRENT
    aiops, gpt-3, gpt-4, llm, llmops, mlops, nextjs, nodejs, open-source, openai, react, shadcn-ui, typescript
    COPY-PASTE FIX
    aiops, gpt-3, gpt-4, llm, llmops, mlops, nextjs, nodejs, open-source, openai, react, shadcn-ui, typescript, llm-observability, llm-monitoring, cost-management, prompt-engineering, api-analytics

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 dillionverma/llm.report
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Dashboard
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Dashboard · recommended 1×
  2. Helicone · recommended 1×
  3. Langfuse · recommended 1×
  4. OpenCost · recommended 1×
  5. Datadog · recommended 1×
  • CATEGORY QUERY
    How can I monitor and analyze my OpenAI API usage and associated costs?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Dashboard
    2. Helicone
    3. Langfuse
    4. OpenCost
    5. Datadog
    6. Splunk
    7. ELK Stack

    AI recommended 7 alternatives but never named dillionverma/llm.report. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an open-source platform to log and improve my LLM prompt performance.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. OpenLLMetry (openllmetry/openllmetry)
    3. LLMonitor (LLMonitor/llmonitor)
    4. Helicone (Helicone/helicone)
    5. Weights & Biases (W&B) Prompts (wandb/wandb)
    6. MLflow (mlflow/mlflow)
    7. LiteLLM (BerriAI/litellm)

    AI recommended 7 alternatives but never named dillionverma/llm.report. 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 dillionverma/llm.report?
    pass
    AI did not name dillionverma/llm.report — 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 dillionverma/llm.report in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dillionverma/llm.report 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 dillionverma/llm.report solve, and who is the primary audience?
    pass
    AI named dillionverma/llm.report 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 dillionverma/llm.report. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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dillionverma/llm.report — 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