RRepoGEO

REPOGEO REPORT · LITE

microsoft/TaskWeaver

Default branch main · commit d44ddef2 · scanned 5/29/2026, 11:51:30 AM

GitHub: 6,163 stars · 776 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 microsoft/TaskWeaver, 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 H1 to specify the core category

    Why:

    CURRENT
    <h1 align="center">
     TaskWeaver
</h1>
    COPY-PASTE FIX
    <h1 align="center">
     TaskWeaver: A Code-First LLM Agent Framework for Data Analytics
</h1>
  • mediumtopics#2
    Add more specific topics for LLM agent frameworks and orchestration

    Why:

    CURRENT
    agent, ai-agents, code-interpreter, copilot, data-analysis, llm, openai
    COPY-PASTE FIX
    agent, ai-agents, code-interpreter, copilot, data-analysis, llm, openai, llm-agent-framework, ai-orchestration
  • mediumreadme#3
    Emphasize the unique 'code execution history' and 'in-memory data' statefulness for LLM agents

    Why:

    CURRENT
    Unlike many agent frameworks that only track the chat history with LLMs in text, TaskWeaver preserves both the **chat history** and the **code execution history**, including the in-memory data. This feature enhances the *expressiveness* of the agent framework, making it ideal for processing complex data structures like high-dimensional tabular data.
    COPY-PASTE FIX
    Unlike many agent frameworks that only track the chat history with LLMs in text, TaskWeaver uniquely preserves both the **chat history** and the **code execution history**, including the in-memory data. This deep, agent-specific statefulness enhances the *expressiveness* of the LLM agent, making it ideal for processing complex data structures like high-dimensional tabular data across multi-step data analytics tasks.

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 microsoft/TaskWeaver
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. OpenAI GPT-4 · recommended 1×
  3. GPT-3.5 Turbo · recommended 1×
  4. Pandas · recommended 1×
  5. NumPy · recommended 1×
  • CATEGORY QUERY
    How to build an AI agent that plans and executes complex data analytics tasks using code?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI GPT-4
    3. GPT-3.5 Turbo
    4. Pandas
    5. NumPy
    6. Scikit-learn
    7. LlamaIndex
    8. Hugging Face Transformers
    9. StarCoder
    10. CodeLlama
    11. AutoGPT
    12. BabyAGI
    13. OpenAI API
    14. Anthropic Claude
    15. Google Gemini
    16. Jupyter Notebooks
    17. IPython

    AI recommended 17 alternatives but never named microsoft/TaskWeaver. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an agent framework to manage stateful data analysis with code and execution history.
    you: not recommended
    AI recommended (in order):
    1. Metaflow
    2. Prefect
    3. Apache Airflow
    4. Kedro
    5. MLflow

    AI recommended 5 alternatives but never named microsoft/TaskWeaver. 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 microsoft/TaskWeaver?
    pass
    AI named microsoft/TaskWeaver explicitly

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

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

    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 microsoft/TaskWeaver. 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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HTML
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  • Brand-free category queries5 vs 2 in Lite
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