RRepoGEO

REPOGEO REPORT · LITE

Memento-Teams/Memento-Skills

Default branch main · commit 07b530ed · scanned 5/13/2026, 4:27:21 PM

GitHub: 1,372 stars · 154 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 Memento-Teams/Memento-Skills, 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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    llm-agents, agent-design, self-improving-agents, deployment-time-learning, generative-ai, artificial-intelligence, machine-learning, agent-framework
  • highabout#2
    Clarify the 'About' description to correct AI's core misunderstanding

    Why:

    CURRENT
    Memento-Skills: Let Agents Design Agents
    COPY-PASTE FIX
    Memento-Skills is a framework for building self-improving AI agents that can autonomously learn, rewrite, and evolve their own skills during deployment, enabling continual adaptation without retraining.
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file to the repository root, specifying the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).

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 Memento-Teams/Memento-Skills
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 1×
  2. DLR-RM/stable-baselines3 · recommended 1×
  3. openai/gym · recommended 1×
  4. Farama-Foundation/Gymnasium · recommended 1×
  5. deepmind/acme · recommended 1×
  • CATEGORY QUERY
    How can I build AI agents that can autonomously learn and improve their capabilities?
    you: not recommended
    AI recommended (in order):
    1. RLlib (ray-project/ray)
    2. Stable Baselines3 (DLR-RM/stable-baselines3)
    3. OpenAI Gym (openai/gym)
    4. Farama Foundation Gymnasium (Farama-Foundation/Gymnasium)
    5. Acme (deepmind/acme)
    6. PyTorch Lightning (Lightning-AI/lightning)
    7. TF-Agents (tensorflow/agents)
    8. AlphaZero
    9. MuZero

    AI recommended 9 alternatives but never named Memento-Teams/Memento-Skills. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What framework allows large language model agents to acquire new skills during runtime?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. MetaGPT
    5. CrewAI
    6. Haystack

    AI recommended 6 alternatives but never named Memento-Teams/Memento-Skills. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • 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 Memento-Teams/Memento-Skills?
    pass
    AI named Memento-Teams/Memento-Skills explicitly

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

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

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

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Memento-Teams/Memento-Skills — 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