RRepoGEO

REPOGEO REPORT · LITE

DenisSergeevitch/agents-best-practices

Default branch main · commit 10ab22a0 · scanned 5/25/2026, 2:23:43 PM

GitHub: 1,062 stars · 96 forks

AI VISIBILITY SCORE
28 /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
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 DenisSergeevitch/agents-best-practices, 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 README's core value proposition to clarify it's a design guide, not a framework

    Why:

    CURRENT
    # agents-best-practices

> "The model proposes actions; the harness validates, authorizes, executes, records, and returns observations."

**A provider-neutral Agent Skill for designing, generating MVP blueprints for, auditing, refactoring, and explaining agentic harnesses.**
    COPY-PASTE FIX
    # agents-best-practices

> "The model proposes actions; the harness validates, authorizes, executes, records, and returns observations."

**A curated collection of provider-neutral best practices, design patterns, and principles for architecting, auditing, and refactoring robust AI agent harnesses. This repository provides conceptual guidance and blueprints, not a runtime framework or library.**
  • mediumreadme#2
    Add a 'What this is NOT' section to explicitly differentiate from frameworks

    Why:

    COPY-PASTE FIX
    ## What this is NOT

This repository is **not** an AI agent framework (like LangChain, LlamaIndex, or Haystack), nor is it a runtime library or API wrapper. It does not provide code for executing agents directly. Instead, it offers conceptual models, design patterns, and architectural guidance to help you *build* and *audit* such frameworks and agents effectively.
  • lowabout#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/DenisSergeevitch/agents-best-practices

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 DenisSergeevitch/agents-best-practices
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. Haystack (deepset AI) · recommended 1×
  4. OpenAI Assistants API · recommended 1×
  5. LiteLLM · recommended 1×
  • CATEGORY QUERY
    How to design robust, provider-agnostic AI agent workflows and best practices?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack (deepset AI)
    4. OpenAI Assistants API
    5. LiteLLM
    6. Pydantic
    7. tenacity
    8. python-dotenv
    9. ConfigParser
    10. PyYAML

    AI recommended 10 alternatives but never named DenisSergeevitch/agents-best-practices. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for building and auditing AI agent control harnesses?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. Tenstorrent's AI Inference Stack
    5. OpenAI API
    6. Redis
    7. PostgreSQL
    8. MongoDB
    9. OpenAI Function Calling
    10. Pydantic (pydantic/pydantic)
    11. LangSmith
    12. Weights & Biases (W&B)
    13. Datadog
    14. Grafana (grafana/grafana)
    15. Prometheus (prometheus/prometheus)
    16. OpenTelemetry
    17. Pytest (pytest-dev/pytest)
    18. Selenium (SeleniumHQ/selenium)
    19. Playwright (microsoft/playwright)
    20. Gradio (gradio-app/gradio)
    21. Streamlit (streamlit/streamlit)
    22. Label Studio (heartexlabs/label-studio)
    23. IBM AI Fairness 360 (AIF360) (Trusted-AI/AIF360)
    24. Google's What-If Tool (WIT) (pair-code/what-if-tool)
    25. Fairlearn (fairlearn/fairlearn)
    26. OWASP Top 10 for LLM Applications
    27. Snyk
    28. Trivy (aquasecurity/trivy)
    29. Git
    30. GitHub
    31. GitLab
    32. DVC (Data Version Control) (iterative/dvc)
    33. MLflow (mlflow/mlflow)

    AI recommended 33 alternatives but never named DenisSergeevitch/agents-best-practices. 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 DenisSergeevitch/agents-best-practices?
    pass
    AI named DenisSergeevitch/agents-best-practices explicitly

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

  • If a team adopts DenisSergeevitch/agents-best-practices in production, what risks or prerequisites should they evaluate first?
    pass
    AI named DenisSergeevitch/agents-best-practices 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 DenisSergeevitch/agents-best-practices solve, and who is the primary audience?
    pass
    AI did not name DenisSergeevitch/agents-best-practices — 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite