RRepoGEO

REPOGEO REPORT · LITE

Giskard-AI/giskard-oss

Default branch main · commit d14b4517 · scanned 5/20/2026, 4:41:27 PM

GitHub: 5,361 stars · 457 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 Giskard-AI/giskard-oss, 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 H1 to specify category and open-source nature

    Why:

    CURRENT
    <h1 align="center" weight='300' >Evals, Red Teaming and Test Generation for Agentic Systems</h1>
    COPY-PASTE FIX
    <h1 align="center" weight='300' >Giskard OSS: Open-Source Evaluation & Red Teaming Library for LLM Agents</h1>
  • mediumreadme#2
    Add a 'Key Features' section to the README

    Why:

    COPY-PASTE FIX
    ## Key Features

*   **Dynamic, multi-turn testing of AI agents:** Evaluate complex agentic systems across multiple interactions.
*   **Enhanced RAG evaluation capabilities:** Thoroughly test Retrieval-Augmented Generation systems.
*   **Powerful AI vulnerability scanner:** Proactively detect and debug a wide range of vulnerabilities (e.g., bias, robustness, performance, security) in LLMs and agents.
  • lowreadme#3
    Add a 'Why Giskard OSS?' section to the README

    Why:

    COPY-PASTE FIX
    ## Why Giskard OSS?

Giskard OSS provides a comprehensive, open-source platform for proactively detecting and debugging a wide range of vulnerabilities (e.g., bias, robustness, performance, security) in ML models, including LLMs and agentic systems, before they are deployed to production.

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 Giskard-AI/giskard-oss
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. Giskard · recommended 1×
  3. LLM Guard · recommended 1×
  4. OWASP LLM Top 10 · recommended 1×
  5. Adversarial GLUE (AdvGLUE) · recommended 1×
  • CATEGORY QUERY
    How can I effectively evaluate and red team my LLM agents for security vulnerabilities?
    you: not recommended
    AI recommended (in order):
    1. Giskard
    2. LLM Guard
    3. OWASP LLM Top 10
    4. Adversarial GLUE (AdvGLUE)
    5. LangChain
    6. PromptInject

    AI recommended 6 alternatives but never named Giskard-AI/giskard-oss. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools exist for dynamic multi-turn testing and RAG evaluation of AI agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain

    AI recommended 1 alternative but never named Giskard-AI/giskard-oss. 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 Giskard-AI/giskard-oss?
    pass
    AI named Giskard-AI/giskard-oss explicitly

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

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

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

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Giskard-AI/giskard-oss — 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
Giskard-AI/giskard-oss — RepoGEO report