RRepoGEO

REPOGEO REPORT · LITE

Iamshankhadeep/ccseva

Default branch main · commit 22dde9db · scanned 6/3/2026, 10:46:56 PM

GitHub: 793 stars · 42 forks

AI VISIBILITY SCORE
35 /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
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 Iamshankhadeep/ccseva, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    macos, menu-bar-app, claude, ai-usage-tracker, llm-monitoring, token-usage, cost-tracking, electron
  • highreadme#2
    Reposition the README's opening sentence for clarity

    Why:

    CURRENT
    A beautiful macOS menu bar app for tracking your Claude Code usage in real-time.
    COPY-PASTE FIX
    CCSeva is a real-time macOS menu bar application designed specifically for developers and users to monitor their Claude AI token usage, costs, and usage patterns.
  • mediumreadme#3
    Add a 'Why CCSeva?' section to differentiate from competitors

    Why:

    COPY-PASTE FIX
    ## Why CCSeva?
    
    Unlike generic system monitors or complex LLM backend platforms, CCSeva focuses specifically on providing a user-friendly, real-time macOS menu bar experience for tracking your personal Claude AI usage. It's designed for individual developers and users who need immediate, at-a-glance insights into their token consumption and costs, directly from their desktop.

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 Iamshankhadeep/ccseva
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Token Monitor
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Token Monitor · recommended 1×
  2. AI Cost Tracker · recommended 1×
  3. Stats · recommended 1×
  4. iStats Menus · recommended 1×
  5. BitBar · recommended 1×
  • CATEGORY QUERY
    What are good macOS menu bar apps for monitoring AI token usage and costs?
    you: not recommended
    AI recommended (in order):
    1. Token Monitor
    2. AI Cost Tracker
    3. Stats
    4. iStats Menus
    5. BitBar
    6. xbar
    7. SwiftBar

    AI recommended 7 alternatives but never named Iamshankhadeep/ccseva. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I track LLM token consumption, daily costs, and usage trends on my Mac?
    you: not recommended
    AI recommended (in order):
    1. Langfuse (langfuse/langfuse)
    2. OpenAI API Usage Dashboard
    3. LiteLLM (BerriAI/litellm)
    4. Helicone (helicone/helicone)
    5. SQLite
    6. CSV
    7. Pandas (pandas-dev/pandas)
    8. Matplotlib (matplotlib/matplotlib)
    9. PromptLayer (PromptLayer/promptlayer)

    AI recommended 9 alternatives but never named Iamshankhadeep/ccseva. 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 Iamshankhadeep/ccseva?
    pass
    AI named Iamshankhadeep/ccseva explicitly

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

  • If a team adopts Iamshankhadeep/ccseva in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Iamshankhadeep/ccseva 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 Iamshankhadeep/ccseva solve, and who is the primary audience?
    pass
    AI named Iamshankhadeep/ccseva 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 Iamshankhadeep/ccseva. 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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MARKDOWN (README)
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Iamshankhadeep/ccseva — 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
Iamshankhadeep/ccseva — RepoGEO report