RRepoGEO

REPOGEO REPORT · LITE

mozilla-ai/any-agent

Default branch main · commit 3e248d1c · scanned 5/29/2026, 4:27:12 PM

GitHub: 1,170 stars · 93 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 mozilla-ai/any-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
    Update repository description to emphasize standardization and comparison

    Why:

    CURRENT
    A single interface to use and evaluate different agent frameworks
    COPY-PASTE FIX
    Standardize, run, and compare diverse AI agent frameworks through a single, unified interface.
  • mediumtopics#2
    Add more specific and widely recognized topics

    Why:

    CURRENT
    a2a, agent-evaluation, agents, ai, mcp
    COPY-PASTE FIX
    agent-frameworks, multi-agent-systems, agent-orchestration, ai-agents, agent-evaluation, unified-api, agent-comparison
  • lowreadme#3
    Rephrase the 'IMPORTANT' deprecation notice to lead with utility

    Why:

    CURRENT
    > [!IMPORTANT]
> **`any-agent` is in soft deprecation.** It started as a research project to compare agent frameworks and refine a minimal common surface. That distillation has graduated to its own package: `mozilla-ai-tinyagent` (PyPI: `mozilla-ai-tinyagent`). For new projects we recommend using `tinyagent` directly.
> 
> `any-agent` continues to be published and we'll take security/bug-fix PRs, but no new features are planned. Reach for `any-agent` when you specifically need to **run or evaluate agents across multiple frameworks** (Agno, Google ADK, LangChain, LlamaIndex, OpenAI Agents SDK, smolagents) under one API. If you only need the core agent loop, `mozilla-ai-tinyagent` is the leaner path.
    COPY-PASTE FIX
    > [!IMPORTANT]
> **`any-agent` provides a unified API to run and evaluate agents across multiple frameworks** (Agno, Google ADK, LangChain, LlamaIndex, OpenAI Agents SDK, smolagents). While `any-agent` is in soft deprecation (no new features planned, security/bug-fix PRs accepted), it remains the recommended choice when you specifically need to compare or orchestrate diverse agent implementations. For new projects focused solely on the core agent loop, consider `mozilla-ai-tinyagent`.

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 mozilla-ai/any-agent
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. LlamaIndex · recommended 1×
  3. OpenAI Function Calling / Tool Use · recommended 1×
  4. Haystack · recommended 1×
  5. Pydantic · recommended 1×
  • CATEGORY QUERY
    How can I standardize the API for interacting with various AI agent frameworks?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI Function Calling / Tool Use
    4. Haystack
    5. Pydantic
    6. FastAPI

    AI recommended 6 alternatives but never named mozilla-ai/any-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help compare performance and capabilities of multiple AI agent implementations?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Evals (openai/evals)
    2. LangChain Evaluation (langchain-ai/langchain)
    3. MLflow (mlflow/mlflow)
    4. Weights & Biases (wandb/wandb)
    5. Pandas (pandas-dev/pandas)
    6. Matplotlib (matplotlib/matplotlib)
    7. Seaborn (mwaskom/seaborn)
    8. Ragas (explodinggradients/raga)

    AI recommended 8 alternatives but never named mozilla-ai/any-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
    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 mozilla-ai/any-agent?
    pass
    AI named mozilla-ai/any-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 mozilla-ai/any-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mozilla-ai/any-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 mozilla-ai/any-agent solve, and who is the primary audience?
    pass
    AI named mozilla-ai/any-agent explicitly

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

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