RRepoGEO

REPOGEO REPORT · LITE

scabench-org/hound

Default branch main · commit c2989018 · scanned 6/8/2026, 1:08:26 PM

GitHub: 776 stars · 149 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 scabench-org/hound, 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
    Strengthen README's opening to emphasize AI auditing and knowledge graphs

    Why:

    CURRENT
    <p align="center"><strong>Autonomous agents for code security auditing</strong></p>
    COPY-PASTE FIX
    <p align="center"><strong>Autonomous AI auditor for deep code security analysis using adaptive knowledge graphs</strong></p>
  • mediumlicense#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add a section or a line in the README, e.g., '## License This project is licensed under [specify license(s) here, e.g., a custom license, or a combination of X and Y]. See the [LICENSE.txt](LICENSE.txt) file for details.'

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 scabench-org/hound
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
returntocorp/semgrep
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. returntocorp/semgrep · recommended 2×
  2. github/codeql · recommended 2×
  3. Snyk Code · recommended 1×
  4. Checkmarx SAST · recommended 1×
  5. Veracode Static Analysis · recommended 1×
  • CATEGORY QUERY
    Looking for an AI-powered tool to automate deep security audits of my codebase.
    you: not recommended
    AI recommended (in order):
    1. Snyk Code
    2. Checkmarx SAST
    3. Veracode Static Analysis
    4. SonarQube
    5. SonarCloud
    6. SonarLint
    7. Semgrep (returntocorp/semgrep)
    8. Semgrep AppSec Platform
    9. CodeQL (github/codeql)
    10. GitHub Advanced Security

    AI recommended 10 alternatives but never named scabench-org/hound. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I perform language-agnostic code security analysis using knowledge graphs?
    you: not recommended
    AI recommended (in order):
    1. Joern (joernio/joern)
    2. Neo4j (neo4j/neo4j)
    3. ArangoDB (arangodb/arangodb)
    4. CodeQL (github/codeql)
    5. Grakn (graknlabs/grakn)
    6. TypeDB (vaticle/typedb)
    7. Soufflé (souffle-lang/souffle)
    8. LogicBlox
    9. Amazon Neptune
    10. PyTorch Geometric (pyg-team/pytorch_geometric)
    11. Deep Graph Library (DGL) (dmlc/dgl)
    12. Semgrep (returntocorp/semgrep)

    AI recommended 12 alternatives but never named scabench-org/hound. 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 scabench-org/hound?
    pass
    AI named scabench-org/hound explicitly

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

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

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

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scabench-org/hound — 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