RRepoGEO

REPOGEO REPORT · LITE

sightflow-dev/sightflow-desktop-agent

Default branch main · commit 8bbc196a · scanned 6/22/2026, 5:13:32 AM

GitHub: 522 stars · 165 forks

AI VISIBILITY SCORE
23 /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
2 / 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 sightflow-dev/sightflow-desktop-agent, 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
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    An open-source working memory engine that enables AI agents to understand screen content, interact with desktop applications, and automate complex workflows by bridging the gap between LLMs and real-world software.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-agent, desktop-automation, llm-integration, working-memory, screen-understanding, workflow-automation, open-source
  • mediumreadme#3
    Elevate core differentiator statement in README

    Why:

    COPY-PASTE FIX
    Add the following sentence directly after the initial H1/subtitle block and before the video: '> **SightFlow does not replace the LLM. It completes the one layer the LLM cannot reach** — turning screen pixels into structured semantics, and task intent into real operations.'

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 sightflow-dev/sightflow-desktop-agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Microsoft Power Automate Desktop
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Microsoft Power Automate Desktop · recommended 2×
  2. microsoft/playwright · recommended 1×
  3. appium/appium · recommended 1×
  4. asweigart/pyautogui · recommended 1×
  5. UIPath · recommended 1×
  • CATEGORY QUERY
    How to build an AI agent that can understand and interact with desktop applications?
    you: not recommended
    AI recommended (in order):
    1. Playwright (microsoft/playwright)
    2. Appium (appium/appium)
    3. PyAutoGUI (asweigart/pyautogui)
    4. UIPath
    5. Microsoft Power Automate Desktop
    6. SikuliX (RaiMan/SikuliX1)
    7. AutoIt

    AI recommended 7 alternatives but never named sightflow-dev/sightflow-desktop-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help AI models interpret screen content and automate desktop workflows?
    you: not recommended
    AI recommended (in order):
    1. UiPath Studio
    2. Microsoft Power Automate Desktop
    3. Automation Anywhere Enterprise A2019/360
    4. Blue Prism
    5. TagUI
    6. SikuliX

    AI recommended 6 alternatives but never named sightflow-dev/sightflow-desktop-agent. 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 sightflow-dev/sightflow-desktop-agent?
    pass
    AI named sightflow-dev/sightflow-desktop-agent explicitly

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

  • If a team adopts sightflow-dev/sightflow-desktop-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sightflow-dev/sightflow-desktop-agent 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 sightflow-dev/sightflow-desktop-agent solve, and who is the primary audience?
    pass
    AI did not name sightflow-dev/sightflow-desktop-agent — likely talking about a different project

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

Embed your GEO score

Drop this badge into the README of sightflow-dev/sightflow-desktop-agent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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sightflow-dev/sightflow-desktop-agent — 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