RRepoGEO

REPOGEO REPORT · LITE

awizemann/scarf

Default branch main · commit 160d0116 · scanned 6/4/2026, 12:52:03 AM

GitHub: 584 stars · 38 forks

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 awizemann/scarf, 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 README's opening to clarify core purpose

    Why:

    CURRENT
    A native macOS companion app for the <a href="https://github.com/hermes-ai/hermes-agent">Hermes AI agent</a>.<br> Full visibility into what Hermes is doing, when, and what it creates.
    COPY-PASTE FIX
    Scarf is a native macOS and iOS application for managing and interacting with the <a href="https://github.com/hermes-ai/hermes-agent">Hermes AI agent</a>. It offers multi-window, multi-server (local + remote over SSH) control, providing comprehensive visibility into agent activities, chat, dashboards, sessions, memory, cron, and more.
  • mediumreadme#2
    Add a prominent "Key Features" section

    Why:

    COPY-PASTE FIX
    Add a new section immediately after the introductory paragraph, titled "## Key Features", listing:
*   Native macOS & iOS application
*   Multi-window, multi-server (local + remote over SSH) management
*   Chat interface for agent interaction
*   Dashboard for real-time monitoring
*   Session management
*   Memory inspection
*   Cron job scheduling
*   MCP (Multi-Agent Control Plane) integration
  • lowtopics#3
    Expand topics with more specific AI agent management terms

    Why:

    CURRENT
    ai-agent, gui, hermes, macos, macos-app, swift, swiftui, terminal
    COPY-PASTE FIX
    ai-agent, gui, hermes, macos, macos-app, swift, swiftui, terminal, ai-agent-management, ai-agent-monitoring, remote-server-management

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 awizemann/scarf
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Loopy
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Loopy · recommended 1×
  2. RunwayML · recommended 1×
  3. LocalAI · recommended 1×
  4. OrbStack · recommended 1×
  5. Raycast · recommended 1×
  • CATEGORY QUERY
    What are good native macOS GUI tools for managing local AI agents?
    you: not recommended
    AI recommended (in order):
    1. Loopy
    2. RunwayML
    3. LocalAI
    4. OrbStack
    5. Raycast

    AI recommended 5 alternatives but never named awizemann/scarf. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I monitor and interact with my AI agent across multiple remote servers?
    you: not recommended
    AI recommended (in order):
    1. Prometheus (prometheus/prometheus)
    2. Grafana (grafana/grafana)
    3. Datadog
    4. New Relic
    5. Elasticsearch (elastic/elasticsearch)
    6. Logstash (elastic/logstash)
    7. Kibana (elastic/kibana)
    8. Beats (elastic/beats)
    9. Ansible (ansible/ansible)
    10. SaltStack (saltstack/salt)
    11. Zabbix (zabbix/zabbix)

    AI recommended 11 alternatives but never named awizemann/scarf. 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 awizemann/scarf?
    pass
    AI named awizemann/scarf explicitly

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

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

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

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awizemann/scarf — 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