RRepoGEO

REPOGEO REPORT · LITE

514-labs/moosestack

Default branch main · commit 22c6b148 · scanned 5/30/2026, 9:16:34 AM

GitHub: 581 stars · 32 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 514-labs/moosestack, 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 the README's opening sentence to emphasize 'AI agent harness'

    Why:

    CURRENT
    **The developer agent harness for ClickHouse** — MooseStack gives your AI coding agents the interfaces, context, code, and skills to build and ship applications on popular OSS realtime analytical infrastructure: safely, efficiently, and effectively.
    COPY-PASTE FIX
    MooseStack is an **AI agent harness** for building analytics into your app on top of ClickHouse, Redpanda, and other high-performance analytical infrastructure. It gives your AI coding agents the interfaces, context, code, and skills to build and ship applications on popular OSS realtime analytical infrastructure: safely, efficiently, and effectively.
  • mediumtopics#2
    Add more specific topics related to AI agents and real-time analytics

    Why:

    CURRENT
    analytics, data, dataengineering, deployment, framework, insights, metrics, python, rust, typescript
    COPY-PASTE FIX
    analytics, data, dataengineering, deployment, framework, insights, metrics, python, rust, typescript, ai-agents, llm-agents, generative-ai, realtime-analytics, clickhouse, redpanda
  • lowreadme#3
    Add a 'Comparison' section to clarify what MooseStack is and isn't

    Why:

    COPY-PASTE FIX
    ## Comparison

MooseStack is not a full-stack web framework like Next.js or Flask; instead, it's a specialized layer for AI agents to interact with analytical infrastructure. It complements general AI coding agents by providing specific skills for real-time data tasks, rather than replacing them. Unlike raw data platforms such as ClickHouse or Redpanda, MooseStack provides the agent harness to *build on top of* these systems, not to replace them.

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 514-labs/moosestack
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Apache Flink
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Apache Flink · recommended 1×
  2. Apache Kafka · recommended 1×
  3. Confluent Platform · recommended 1×
  4. Databricks · recommended 1×
  5. Delta Lake · recommended 1×
  • CATEGORY QUERY
    How to enable AI agents to build real-time analytics applications?
    you: not recommended
    AI recommended (in order):
    1. Apache Flink
    2. Apache Kafka
    3. Confluent Platform
    4. Databricks
    5. Delta Lake
    6. Spark Streaming
    7. Google Cloud Dataflow
    8. Apache Beam
    9. Redis
    10. LangChain
    11. LlamaIndex

    AI recommended 11 alternatives but never named 514-labs/moosestack. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Python framework for building real-time analytics on high-performance data streams?
    you: not recommended
    AI recommended (in order):
    1. Apache Flink (apache/flink)
    2. Apache Spark (apache/spark)
    3. Faust (robinhood/faust)
    4. Confluent ksqlDB (confluentinc/ksql)
    5. Ray (ray-project/ray)
    6. Streamz (python-streamz/streamz)

    AI recommended 6 alternatives but never named 514-labs/moosestack. 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 514-labs/moosestack?
    pass
    AI named 514-labs/moosestack explicitly

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

  • If a team adopts 514-labs/moosestack in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 514-labs/moosestack 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 514-labs/moosestack solve, and who is the primary audience?
    pass
    AI named 514-labs/moosestack explicitly

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

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514-labs/moosestack — RepoGEO report