RRepoGEO

REPOGEO REPORT · LITE

patoles/agent-flow

Default branch main · commit 59ccf4e3 · scanned 6/13/2026, 2:16:39 AM

GitHub: 968 stars · 108 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 patoles/agent-flow, 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 H1 and opening sentence to emphasize visual debugging for AI agents

    Why:

    CURRENT
    # Agent Flow

Real-time visualization of Claude Code and Codex agent orchestration. Watch your agents think, branch, and coordinate as they work.
    COPY-PASTE FIX
    # Agent Flow: Real-time Visual Debugger for AI Agent Orchestration

Agent Flow provides real-time visualization of Claude Code and Codex agent orchestration, allowing you to visually debug and understand how your agents think, branch, and coordinate as they work.
  • mediumtopics#2
    Add more specific topics related to AI agent debugging and observability

    Why:

    CURRENT
    agent-visualization, ai-agents, claude-code, developer-tools, llm, vscode-extension
    COPY-PASTE FIX
    agent-visualization, ai-agents, claude-code, developer-tools, llm-debugging, agent-observability, real-time-monitoring, vscode-extension
  • lowreadme#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Agent Flow is a specialized visual debugger for AI agent orchestration, distinct from general-purpose LLM frameworks or distributed tracing tools. While tools like LangSmith, OpenTelemetry, or Weights & Biases offer broad observability for LLMs and applications, Agent Flow focuses specifically on providing a real-time, interactive graphical view of agent decision-making, tool calls, and branching logic. It complements these broader systems by offering deep, visual insight into the internal workings of individual agent runs, rather than overall system performance or generic trace collection.

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 patoles/agent-flow
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain Plus (LangSmith)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain Plus (LangSmith) · recommended 1×
  2. OpenTelemetry · recommended 1×
  3. Jaeger · recommended 1×
  4. Honeycomb · recommended 1×
  5. WandB Prompts (Weights & Biases) · recommended 1×
  • CATEGORY QUERY
    What are good tools for tracing and debugging LLM agent orchestration?
    you: not recommended
    AI recommended (in order):
    1. LangChain Plus (LangSmith)
    2. OpenTelemetry
    3. Jaeger
    4. Honeycomb
    5. WandB Prompts (Weights & Biases)
    6. LlamaIndex Observability
    7. Arize AI
    8. TruLens
    9. ELK Stack
    10. Elasticsearch
    11. Logstash
    12. Kibana

    AI recommended 12 alternatives but never named patoles/agent-flow. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I visually debug and understand the real-time execution of my AI agent workflows?
    you: not recommended
    AI recommended (in order):
    1. LangSmith
    2. LangChain Playground
    3. OpenAI Playground
    4. Weights & Biases
    5. Humanloop
    6. Steamship
    7. Plotly Dash
    8. Streamlit

    AI recommended 8 alternatives but never named patoles/agent-flow. 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 patoles/agent-flow?
    pass
    AI named patoles/agent-flow explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite