RRepoGEO

REPOGEO REPORT · LITE

cinar/indicator

Default branch master · commit 079135d0 · scanned 5/24/2026, 5:26:33 PM

GitHub: 1,098 stars · 179 forks

AI VISIBILITY SCORE
63 /100
Needs work
Category recall
1 / 2
Avg rank #3.0 when recommended
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 cinar/indicator, 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 and clarify the README's introduction for Go technical analysis and backtesting

    Why:

    CURRENT
    Indicator Go
Indicator is a Golang module that provides an extensive set of technical analysis indicators, strategies, and a framework for backtesting with real-time strategy execution.
> An extensive technical analysis library for algorithmic trading - 80+ indicators, backtesting framework, and AI integration via MCP.
    COPY-PASTE FIX
    ## Indicator Go: A comprehensive, pure Golang framework for technical analysis and algorithmic trading
Indicator is a powerful, pure Golang module that provides an extensive set of technical analysis indicators, customizable strategies, and a robust backtesting engine with real-time execution capabilities. It features 80+ indicators and AI integration via MCP.
  • mediumhomepage#2
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/cinar/indicator
  • mediumreadme#3
    Explicitly highlight support for developing custom indicators

    Why:

    CURRENT
    Configurable Indicators and Strategies: All indicators and strategies were designed to be fully configurable with no preset values.
    COPY-PASTE FIX
    The library also supports the development of custom indicators and strategies, with all components designed to be fully configurable without preset values. This allows for high flexibility in developing unique trading logic.

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
1 / 2
50% of queries surface cinar/indicator
Avg rank
#3.0
Lower is better. #1 = top recommendation.
Share of voice
9%
Of all named tools, what % are you?
Top rival
ta-lib/go-talib
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ta-lib/go-talib · recommended 1×
  2. markcheno/go-talib · recommended 1×
  3. alpacahq/alpaca-trade-api-go · recommended 1×
  4. go-numb/go-trade-indicators · recommended 1×
  5. go-numb/go-trade-bot · recommended 1×
  • CATEGORY QUERY
    What are the best Go libraries for technical analysis indicators and algorithmic trading?
    you: #3
    AI recommended (in order):
    1. ta-lib/go-talib (ta-lib/go-talib)
    2. markcheno/go-talib (markcheno/go-talib)
    3. cinar/indicator (cinar/indicator) ← you
    4. alpacahq/alpaca-trade-api-go (alpacahq/alpaca-trade-api-go)
    5. go-numb/go-trade-indicators (go-numb/go-trade-indicators)
    6. go-numb/go-trade-bot (go-numb/go-trade-bot)
    7. go-numb/go-exchanges (go-numb/go-exchanges)
    Show full AI answer
  • CATEGORY QUERY
    Looking for a Go framework to backtest trading strategies and develop custom indicators.
    you: not recommended
    AI recommended (in order):
    1. QuantConnect Lean
    2. GoQuant
    3. GoTA
    4. ta-lib (github.com/markcheno/go-talib)

    AI recommended 4 alternatives but never named cinar/indicator. 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 cinar/indicator?
    pass
    AI named cinar/indicator explicitly

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

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite