RRepoGEO

REPOGEO REPORT · LITE

AgentOps-AI/tokencost

Default branch main · commit e7f7c192 · scanned 5/16/2026, 10:31:56 AM

GitHub: 1,981 stars · 104 forks

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 AgentOps-AI/tokencost, 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
    Reposition the README's opening paragraph to emphasize multi-provider library

    Why:

    CURRENT
    <p align="center">
  <em>Clientside token counting + price estimation for LLM apps and AI agents.</em>
</p>
<p align="center">
    <a href="https://pypi.org/project/tokencost/" target="_blank">
        
        
    </a>
</p>
<p align="center">
<a href="https://twitter.com/agentopsai/">🐦 Twitter</a>
<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
<a href="https://discord.com/invite/FagdcwwXRR">📢 Discord</a>
<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
<a href="https://agentops.ai/?tokencost">🖇️ AgentOps</a>
</p>

# TokenCost
[](https://opensource.org/licenses/MIT) 
[](https://x.com/agentopsai)

Tokencost helps calculate the USD cost of using major Large Language Model (LLMs) APIs by calculating the estimated cost of prompts and completions.
    COPY-PASTE FIX
    <p align="center">
  <em>A simple, programmatic, multi-provider library for clientside token counting and price estimation across 400+ LLMs.</em>
</p>
<p align="center">
    <a href="https://pypi.org/project/tokencost/" target="_blank">
        
        
    </a>
</p>
<p align="center">
<a href="https://twitter.com/agentopsai/">🐦 Twitter</a>
<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
<a href="https://discord.com/invite/FagdcwwXRR">📢 Discord</a>
<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
<a href="https://agentops.ai/?tokencost">🖇️ AgentOps</a>
</p>

# TokenCost
[](https://opensource.org/licenses/MIT) 
[](https://x.com/agentopsai)

Tokencost provides a unified way to calculate the USD cost of using major Large Language Model (LLMs) APIs by estimating the cost of prompts and completions from various providers.
  • hightopics#2
    Expand repository topics to include multi-provider and cost management terms

    Why:

    CURRENT
    analytics, claude, large-language-models, llm, observability, openai, price, price-tracker, token, tokenization
    COPY-PASTE FIX
    analytics, claude, large-language-models, llm, observability, openai, price, price-tracker, token, tokenization, llm-cost-management, multi-llm, api-cost-estimation, token-pricing-library, llm-pricing
  • mediumcomparison#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Why TokenCost? (vs. X, Y, Z)

[Add a section here comparing TokenCost to common alternatives like provider-specific SDKs (e.g., `tiktoken`), broader observability platforms (e.g., Langfuse, Helicone), or manual price lookups. Emphasize its focus on unified, multi-provider cost estimation as a dedicated library.]

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 AgentOps-AI/tokencost
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Langfuse
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Langfuse · recommended 2×
  2. Helicone · recommended 2×
  3. LiteLLM · recommended 2×
  4. OpenAI's `tiktoken` library · recommended 1×
  5. Anthropic's `anthropic` Python SDK · recommended 1×
  • CATEGORY QUERY
    How can I accurately estimate the monetary cost of my large language model API calls?
    you: not recommended
    AI recommended (in order):
    1. OpenAI's `tiktoken` library
    2. Anthropic's `anthropic` Python SDK
    3. Google Cloud Vertex AI SDK
    4. Cohere's `cohere` Python SDK
    5. OpenAI Usage Dashboard
    6. Anthropic Usage Dashboard
    7. Google Cloud Usage Dashboard
    8. Azure Usage Dashboard
    9. Cohere Usage Dashboard
    10. Mistral AI Usage Dashboard
    11. Google Cloud Billing
    12. AWS Cost Explorer
    13. Azure Cost Management
    14. Langfuse
    15. Helicone
    16. LiteLLM
    17. Phoenix (by Arize AI)

    AI recommended 17 alternatives but never named AgentOps-AI/tokencost. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help track token usage and calculate expenses for various LLM providers?
    you: not recommended
    AI recommended (in order):
    1. OpenMeter
    2. Helicone
    3. LiteLLM
    4. Langfuse
    5. Prometheus
    6. Grafana
    7. OpenCost

    AI recommended 7 alternatives but never named AgentOps-AI/tokencost. 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 AgentOps-AI/tokencost?
    pass
    AI did not name AgentOps-AI/tokencost — 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 AgentOps-AI/tokencost in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AgentOps-AI/tokencost 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 AgentOps-AI/tokencost solve, and who is the primary audience?
    pass
    AI named AgentOps-AI/tokencost explicitly

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

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