RRepoGEO

REPOGEO REPORT · LITE

Bhartendu-Kumar/rules_template

Default branch main · commit 221fa536 · scanned 5/23/2026, 7:42:16 PM

GitHub: 1,059 stars · 136 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 Bhartendu-Kumar/rules_template, 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
    Reposition the README H1 and add a clear tagline

    Why:

    CURRENT
    # V2: Updates [Major Token Saving updates]
    COPY-PASTE FIX
    # AI Coding Assistant Rules & Prompts Template

**Comprehensive, token-optimized rules and prompt templates for AI coding assistants like Cursor, RooCode, and CLINE, designed for agile development and software engineering best practices.**
  • highlicense#2
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the content of a standard open-source license, such as MIT License.

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 Bhartendu-Kumar/rules_template
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 · recommended 1×
  2. Anthropic Claude 3 Opus · recommended 1×
  3. Google Gemini Advanced · recommended 1×
  4. GitHub Copilot · recommended 1×
  5. Code Llama · recommended 1×
  • CATEGORY QUERY
    How to improve AI coding assistant output quality using structured prompts and best practices?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. Anthropic Claude 3 Opus
    3. Google Gemini Advanced
    4. GitHub Copilot
    5. Code Llama

    AI recommended 5 alternatives but never named Bhartendu-Kumar/rules_template. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective strategies for optimizing token usage with custom AI coding assistant rules?
    you: not recommended
    AI recommended (in order):
    1. Tree-sitter
    2. ast
    3. go/ast
    4. ts-morph (dsherret/ts-morph)
    5. LSP
    6. Ollama (ollama/ollama)
    7. LM Studio
    8. diff utility
    9. difflib
    10. go-diff
    11. OpenAI API
    12. Anthropic Claude API
    13. OpenAI Fine-tuning
    14. LangChain (langchain-ai/langchain)
    15. LlamaIndex (run-llama/llama_index)
    16. OpenAI text-embedding-ada-002
    17. Hugging Face sentence-transformers/all-MiniLM-L6-v2
    18. Pinecone
    19. Weaviate (weaviate/weaviate)
    20. ChromaDB (chroma-core/chroma)
    21. OpenAI tiktoken library (openai/tiktoken)

    AI recommended 21 alternatives but never named Bhartendu-Kumar/rules_template. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 Bhartendu-Kumar/rules_template?
    pass
    AI named Bhartendu-Kumar/rules_template explicitly

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

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

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

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Bhartendu-Kumar/rules_template — 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