RRepoGEO

REPOGEO REPORT · LITE

krafton-ai/KIRA

Default branch main · commit 652dacbf · scanned 6/2/2026, 7:12:00 PM

GitHub: 887 stars · 108 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 krafton-ai/KIRA, 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
  • highabout#1
    Update the repository description

    Why:

    CURRENT
    KIRA
    COPY-PASTE FIX
    An agent harness for LLMs that boosts frontier model performance on Terminal-Bench with native tool calling, multimodal support, and execution optimization.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-agents, agent-framework, multimodal-llm, tool-calling, llm-optimization, terminal-bench, ai-agents, frontier-models
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://github.com/krafton-ai/KIRA#readme

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 krafton-ai/KIRA
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. OpenAI Assistants API · recommended 2×
  4. Haystack · recommended 2×
  5. Microsoft Semantic Kernel · recommended 1×
  • CATEGORY QUERY
    How to improve large language model agent performance with native tool calling and multimodal support?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. Google Gemini API
    5. OpenAI Assistants API
    6. Haystack

    AI recommended 6 alternatives but never named krafton-ai/KIRA. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best frameworks for optimizing LLM agent execution and completion verification?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LangSmith
    3. LlamaIndex
    4. AutoGen
    5. Haystack
    6. CrewAI
    7. Marvin
    8. OpenAI Assistants API

    AI recommended 8 alternatives but never named krafton-ai/KIRA. 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 krafton-ai/KIRA?
    pass
    AI named krafton-ai/KIRA explicitly

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

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

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

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MARKDOWN (README)
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krafton-ai/KIRA — 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