RRepoGEO

REPOGEO REPORT · LITE

junhoyeo/tokscale

Default branch main · commit c08300c0 · scanned 5/17/2026, 7:47:03 PM

GitHub: 2,986 stars · 198 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
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 junhoyeo/tokscale, 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 statement to clarify its niche

    Why:

    CURRENT
    > A high-performance CLI tool and visualization dashboard for tracking token usage and costs across multiple AI coding agents.
    COPY-PASTE FIX
    > **tokscale** is the definitive high-performance CLI tool and visualization dashboard for tracking token usage and optimizing costs specifically for **AI code generation tools** like OpenCode, Claude Code, and Cursor. Gain insights into your LLM consumption with a global leaderboard and 2D/3D contributions graph.
  • mediumtopics#2
    Add category-defining topics

    Why:

    CURRENT
    ai, ai-agents, ampcode, claude, claude-code, clawdbot, codex, cursor, cursor-ide, droid, gemini, gemini-cli, gpt, hermes, moltbot, oh, openclaw, opencode, opentui, token-usage
    COPY-PASTE FIX
    ai-developer-tools, llm-observability, llm-cost-management, code-generation-metrics, token-tracking, cli-tool, rust-cli, data-visualization, leaderboard, contributions-graph
  • mediumcomparison#3
    Add a 'Why tokscale?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ### Why tokscale?
Unlike general AI frameworks (e.g., LangChain) or broad observability platforms (e.g., OpenTelemetry, Prometheus), tokscale is purpose-built for developers and teams using AI code generation tools. We provide granular, real-time token usage tracking and cost insights specifically tailored for your coding workflows, offering a lightweight, cross-platform CLI and intuitive visualization dashboard that general tools do not.

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 junhoyeo/tokscale
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LangSmith · recommended 1×
  3. OpenTelemetry · recommended 1×
  4. Prometheus · recommended 1×
  5. Grafana · recommended 1×
  • CATEGORY QUERY
    How can I monitor and visualize token usage across different AI code generation tools?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LangSmith
    3. OpenTelemetry
    4. Prometheus
    5. Grafana
    6. Datadog
    7. Splunk
    8. Pandas
    9. Matplotlib
    10. Seaborn
    11. Google Cloud Operations
    12. AWS CloudWatch
    13. Azure Monitor

    AI recommended 13 alternatives but never named junhoyeo/tokscale. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What CLI tool helps track AI model token consumption and associated costs cross-platform?
    you: not recommended
    AI recommended (in order):
    1. OpenCost (opencost/opencost)
    2. LangChain (langchain-ai/langchain)
    3. Typer (tiangolo/typer)
    4. Click (pallets/click)
    5. LiteLLM (BerriAI/litellm)
    6. argparse
    7. Commander.js (tj/commander.js)
    8. Yargs (yargs/yargs)
    9. openai (openai/openai-python)
    10. @anthropic-ai/sdk (anthropics/anthropic-sdk-typescript)
    11. Prometheus (prometheus/prometheus)
    12. Grafana (grafana/grafana)
    13. AWS Cost Explorer
    14. Google Cloud Billing Reports
    15. Azure Cost Management

    AI recommended 15 alternatives but never named junhoyeo/tokscale. 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 junhoyeo/tokscale?
    pass
    AI named junhoyeo/tokscale explicitly

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

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

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

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junhoyeo/tokscale — 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