RRepoGEO

REPOGEO REPORT · LITE

HKUDS/FastCode

Default branch main · commit 590e49ba · scanned 5/17/2026, 7:31:37 AM

GitHub: 2,162 stars · 255 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
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 HKUDS/FastCode, 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
    Refine the repository's "About" description

    Why:

    CURRENT
    FastCode: Accelerating and Streamlining Your Code Understanding
    COPY-PASTE FIX
    FastCode: A token-efficient framework for comprehensive static code analysis and understanding across large-scale codebases.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    code-analysis, static-analysis, code-comprehension, software-architecture, large-scale-codebases, llm-powered, code-understanding
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Add a LICENSE file to the repository root, choosing an appropriate open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that aligns with your project's goals and allows for clear usage terms.

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 HKUDS/FastCode
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SonarQube
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SonarQube · recommended 2×
  2. CodeQL · recommended 1×
  3. Semgrep · recommended 1×
  4. Coverity · recommended 1×
  5. Kiuwan · recommended 1×
  • CATEGORY QUERY
    Looking for a faster, more cost-effective tool for large-scale code understanding and analysis.
    you: not recommended
    AI recommended (in order):
    1. CodeQL
    2. SonarQube
    3. Semgrep
    4. Coverity
    5. Kiuwan
    6. Pylint
    7. ESLint
    8. Checkstyle

    AI recommended 8 alternatives but never named HKUDS/FastCode. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a highly accurate and efficient solution for comprehensive code comprehension across complex software projects.
    you: not recommended
    AI recommended (in order):
    1. Understand.ai
    2. Lattix LDM
    3. Source Insight
    4. CodeSonar
    5. Klocwork
    6. SonarQube
    7. JetBrains IDEs

    AI recommended 7 alternatives but never named HKUDS/FastCode. 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 HKUDS/FastCode?
    pass
    AI named HKUDS/FastCode explicitly

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

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

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

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HKUDS/FastCode — 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