RRepoGEO

REPOGEO REPORT · LITE

NousResearch/hermes-agent-self-evolution

Default branch main · commit 4693c8f0 · scanned 5/17/2026, 7:37:41 PM

GitHub: 3,304 stars · 356 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 NousResearch/hermes-agent-self-evolution, 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 specific topics to the repository

    Why:

    COPY-PASTE FIX
    llm-agent, self-improvement, evolutionary-algorithms, prompt-optimization, dspy, gepa, ai-agents, code-optimization, agent-framework
  • highlicense#2
    Add an MIT LICENSE file

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root containing the standard MIT License text.
  • mediumreadme#3
    Strengthen README opening with explicit category and differentiator

    Why:

    CURRENT
    **Evolutionary self-improvement for Hermes Agent.**
    COPY-PASTE FIX
    **Hermes Agent Self-Evolution is a specialized framework for autonomous AI agent improvement, using evolutionary search to optimize skills, prompts, and code without GPU training.**

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 NousResearch/hermes-agent-self-evolution
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. OpenAI Evals · recommended 2×
  3. Weights & Biases · recommended 1×
  4. Humanloop · recommended 1×
  5. MLflow · recommended 1×
  • CATEGORY QUERY
    How can I automatically improve my AI agent's performance and prompt effectiveness?
    you: not recommended
    AI recommended (in order):
    1. Weights & Biases
    2. LangChain
    3. OpenAI Evals
    4. Humanloop
    5. MLflow
    6. Guardrails AI
    7. LlamaIndex

    AI recommended 7 alternatives but never named NousResearch/hermes-agent-self-evolution. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for evolutionary optimization of LLM prompts and agent skills without GPU training?
    you: not recommended
    AI recommended (in order):
    1. PromptPerfect
    2. LLMware
    3. LangChain
    4. OpenAI Evals
    5. Ax
    6. Nevergrad

    AI recommended 6 alternatives but never named NousResearch/hermes-agent-self-evolution. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 NousResearch/hermes-agent-self-evolution?
    pass
    AI named NousResearch/hermes-agent-self-evolution explicitly

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

  • If a team adopts NousResearch/hermes-agent-self-evolution in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NousResearch/hermes-agent-self-evolution 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 NousResearch/hermes-agent-self-evolution solve, and who is the primary audience?
    pass
    AI did not name NousResearch/hermes-agent-self-evolution — likely talking about a different project

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

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NousResearch/hermes-agent-self-evolution — 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
NousResearch/hermes-agent-self-evolution — RepoGEO report