RRepoGEO

REPOGEO REPORT · LITE

jmuncor/tokentap

Default branch main · commit 10c8838e · scanned 6/6/2026, 11:16:52 AM

GitHub: 796 stars · 37 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 jmuncor/tokentap, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify Tokentap's core function in the README's opening statement

    Why:

    CURRENT
    tokentap tracks token usage for LLM CLI tools with a live terminal dashboard.
    COPY-PASTE FIX
    Tokentap is a real-time terminal dashboard that intercepts LLM API traffic to visualize token usage, track costs, and debug prompts across your AI development sessions.
  • mediumabout#2
    Emphasize API traffic interception and real-time dashboard in the 'About' description

    Why:

    CURRENT
    Intercept LLM API traffic and visualize token usage in a real-time terminal dashboard. Track costs, debug prompts, and monitor context window usage across your AI development sessions.
    COPY-PASTE FIX
    Intercepts LLM API traffic to provide a real-time terminal dashboard for visualizing token usage, tracking costs, debugging prompts, and monitoring context windows across AI development sessions.

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 jmuncor/tokentap
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. Textualize/rich · recommended 1×
  3. curses · recommended 1×
  4. opencost/opencost · recommended 1×
  5. BerriAI/litellm · recommended 1×
  • CATEGORY QUERY
    How to get a real-time terminal dashboard for LLM token usage and API costs?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. rich (Textualize/rich)
    3. curses
    4. OpenCost (opencost/opencost)
    5. LiteLLM (BerriAI/litellm)
    6. Prometheus (prometheus/prometheus)
    7. Grafana (grafana/grafana)
    8. promtail (grafana/loki)
    9. cAdvisor (google/cadvisor)
    10. termshark (gcla/termshark)
    11. tshark
    12. LangSmith (langchain-ai/langsmith)

    AI recommended 12 alternatives but never named jmuncor/tokentap. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tool helps debug LLM prompts and monitor context window usage via API traffic?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LangSmith
    3. OpenAI Evals (openai/evals)
    4. Helicone (helicone-ai/helicone)
    5. Lunary.ai (lunary-ai/lunary)
    6. Weights & Biases Prompts (wandb/wandb)
    7. Portkey.ai (Portkey-AI/gateway)
    8. Vellum

    AI recommended 8 alternatives but never named jmuncor/tokentap. 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 jmuncor/tokentap?
    pass
    AI named jmuncor/tokentap explicitly

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

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

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

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite