RRepoGEO

REPOGEO REPORT · LITE

nateherkai/token-dashboard

Default branch main · commit 53756505 · scanned 6/15/2026, 8:23:02 PM

GitHub: 586 stars · 156 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 nateherkai/token-dashboard, 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 the repository

    Why:

    COPY-PASTE FIX
    claude, token-usage, llm-analytics, cost-optimization, local-first, privacy-focused, dashboard, python
  • highreadme#2
    Clarify the README's opening statement to emphasize 'Claude Code' and its purpose

    Why:

    CURRENT
    # Token Dashboard

A local dashboard that reads the JSONL transcripts Claude Code writes to `~/.claude/projects/` and turns them into per-prompt cost analytics, tool/file heatmaps, subagent attribution, cache analytics, project comparisons, and a rule-based tips engine.
    COPY-PASTE FIX
    # Claude Code Token Dashboard

A **local, privacy-focused dashboard** for analyzing your **Claude Code token usage and costs**. It reads raw JSONL transcripts from `~/.claude/projects/` to provide per-prompt cost analytics, tool/file heatmaps, subagent attribution, cache analytics, project comparisons, and a rule-based tips engine.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/nateherkai/token-dashboard

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 nateherkai/token-dashboard
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. LangSmith · recommended 1×
  3. openai/openai-python · recommended 1×
  4. SQLite · recommended 1×
  5. pandas-dev/pandas · recommended 1×
  • CATEGORY QUERY
    How can I analyze my AI assistant token usage and identify cost hotspots locally?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LangSmith
    3. OpenAI Python Library (openai/openai-python)
    4. SQLite
    5. Pandas (pandas-dev/pandas)
    6. Matplotlib (matplotlib/matplotlib)
    7. Seaborn (mwaskom/seaborn)
    8. LiteLLM (BerriAI/litellm)
    9. PromptLayer (PromptLayer/promptlayer-python)
    10. tiktoken (openai/tiktoken)
    11. OpenCost (opencost/opencost)
    12. Flask app (pallets/flask)
    13. Plotly Dash (plotly/dash)

    AI recommended 13 alternatives but never named nateherkai/token-dashboard. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for visualizing large language model token consumption and optimizing AI prompt expenses?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI Playground
    3. Helicone.ai
    4. LiteLLM
    5. Weights & Biases (W&B Prompts)
    6. PromptLayer
    7. Prometheus
    8. Grafana

    AI recommended 8 alternatives but never named nateherkai/token-dashboard. 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 nateherkai/token-dashboard?
    pass
    AI named nateherkai/token-dashboard explicitly

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

  • If a team adopts nateherkai/token-dashboard in production, what risks or prerequisites should they evaluate first?
    pass
    AI named nateherkai/token-dashboard 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 nateherkai/token-dashboard solve, and who is the primary audience?
    pass
    AI did not name nateherkai/token-dashboard — 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?

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  • Brand-free category queries5 vs 2 in Lite
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