0

/ 100

GradeF

Real traction, but rough engineering makes it hard for contributors to trust.

Higher than 27% of 5,156 graded repos

Multi-agent systems, memory, planning, reasoning loops

Jupyter Notebook2,7451mo ago

A low grade is a to-do list, not a judgment of your code

Most gaps here are documentation, tests, and setup, not the code itself. Closing your top 3 gaps alone would lift this repo to C (75).

See your top fixes
Now
F
40
Potential
C
75

Top fixes

Highest-impact changes first, ranked by point weight

13 to address
  1. 1
    Tests18pt

    Add automated tests. They prove the code works and give contributors confidence to make changes.

  2. 2
    CI/CD14pt

    If your CI lives elsewhere (a private repo that builds this one) or this project is itself a CI/CD tool, mark this check Not Applicable. Otherwise add a GitHub Actions workflow that runs tests on each push. It takes 15 minutes and reassures contributors their changes won't break things.

  3. 3
    README12pt

    Add more sections (Overview, Install, Usage, Contributing) using ## headings.

  4. 4
    README12pt

    Show a quick-start snippet so contributors can see what using your project looks like.

Working through the fixes? Let every push regrade itself.

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

55

License6pt0

No license detected.

Add a LICENSE file. Without one, nobody can legally use, copy, or contribute to your code.

Contributing guide5pt0

No CONTRIBUTING.md found (−47 pts base + up to −53 pts more for content).

Add a CONTRIBUTING.md telling newcomers how to get involved. Include setup, code style, test, and PR instructions.

README12pt78

README is present.

Install and run instructions9pt90

README documents how to install the project.

Engineering

10

Tests18pt0

No tests detected anywhere in the repository.

Add automated tests. They prove the code works and give contributors confidence to make changes.

CI/CD14pt0

No CI configuration detected in this repository.

If your CI lives elsewhere (a private repo that builds this one) or this project is itself a CI/CD tool, mark this check Not Applicable. Otherwise add a GitHub Actions workflow that runs tests on each push. It takes 15 minutes and reassures contributors their changes won't break things.

Linting and formatting5pt0

No linter or formatter config found.

Add a linter config such as .eslintrc.json, .prettierrc, ruff.toml, or .golangci.yml to enforce consistent code style.

Issue and PR templates6pt0

No issue or PR templates found (−100 pts).

Add .github/ISSUE_TEMPLATE/ with bug_report.md and feature_request.md to guide contributors. It dramatically improves issue quality.

Reproducibility6pt80

Lockfile present (A2A_Simple_Agent/uv.lock). Installs are reproducible.

Project health

94

Housekeeping3pt60

.gitignore present.

Dependency manifest6pt100

Dependency manifest found (A2A_Simple_Agent/pyproject.toml).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • -
    Commits (30d / 90d)
  • 603
    Forks
  • 0
    Releases

Community

  • -
    Community health
  • -
    authors own >50% of commits
  • 2,745
    Watchers

Responsiveness

  • 55d 15h
    Median issue response
  • 106d 18h
    Median PR merge time
  • 8
    Open issues
Repository files115 root entries
  • A2A_Simple_Agent
    Good: Lockfile present (A2A_Simple_Agent/uv.lock). Installs are reproducible.
    Good: Environment pinned via A2A_Simple_Agent/.python-version.
    Good: Dependency manifest found (A2A_Simple_Agent/pyproject.toml).
  • Adversarial Attacks
  • Agent Communication Protocol
  • Agentic AI Codes
  • Agentic AI Memory
  • Agentic Workflows
  • AI Agents Codes
  • Computer Vision
  • Data Analysis
  • Data Science
  • Databases
  • Deep Learning
  • Distributed Systems
  • Federated Learning
  • GPT-5
  • LLM Evaluation
  • LLM Projects
  • MCP Codes
  • MiniMax
  • Mirascope
  • ML Project Codes
  • MLFlow for LLM Evaluation
  • NLP
  • OAuth 2.1 for MCP Servers
  • Prompt Optimization
  • Quantum Computing
  • RAG
  • Reinforcement learning
  • Robotics
  • Scientific Computing
  • Security
  • SHAP-IQ
  • Voice AI
  • .DS_Store
    Issue: Build artifacts or local files may be committed (.DS_Store) (−40 pts).Fix: Remove them and add to .gitignore.
  • .gitignore
    Good: .gitignore present.
  • A_Coding_Guide_to_ACP_Systems_Marktechpost.ipynb
  • advanced_ai_agent_hugging_face_marktechpost.py
  • Advanced_AI_Evaluator_Enterprise_Grade_Framework_Marktechpost.ipynb
  • advanced_async_python_sdk_tutorial_Marktechpost.ipynb
  • advanced_dspy_qa_Marktechpost.ipynb
  • advanced_google_adk_multi_agent_tutorial_Marktechpost.ipynb
  • advanced_langgraph_multi_agent_pipeline_Marktechpost.ipynb
  • Advanced_PEER_MultiAgent_Tutorial_Marktechpost.ipynb
  • advanced_pubmed_research_assistant_tutorial_Marktechpost.ipynb
  • advanced_serpapi_tutorial_Marktechpost.ipynb
  • agent_orchestration_with_mistral_agents_api.py
  • agent2agent_collaboration_Marktechpost.ipynb
  • AI Agents and Agentic AI
  • async_config_tutorial_Marktechpost.ipynb
  • AutoGen_SemanticKernel_Gemini_Flash_MultiAgent_Tutorial_Marktechpost.ipynb
  • AutoGen_TeamTool_RoundRobin_Marktechpost.ipynb
  • beeai_multi_agent_workflow_Marktechpost.ipynb
  • BioCypher_Agent_Tutorial_Marktechpost.ipynb
  • cipher_memory_agent_Marktechpost.ipynb
  • Cognee_Agent_Tutorial_with_HuggingFace_Integration_Marktechpost.ipynb
  • Competitive_Analysis_with_ScrapeGraph_Gemini_Marktechpost.ipynb
  • Context_Aware_Assistant_MCP_Gemini_LangChain_LangGraph_Marktechpost.ipynb
  • CrewAI_Gemini_Workflow_Marktechpost.ipynb
  • custom_mcp_tools_integration_with_fastmcp_marktechpost.py
  • Custom_Tool_For_AI_Agent_Marktechpost.ipynb
  • Customizable_MultiTool_AI_Agent_with_Claude_Marktechpost (1).ipynb
  • dagster_advanced_pipeline_Marktechpost.ipynb
  • daytona_secure_ai_code_execution_tutorial_Marktechpost.ipynb
  • emi_agent.py
  • Enhanced_BrightData_Gemini_Scraper_Tutorial_Marktechpost.ipynb
  • gemini_agent_network_Marktechpost.ipynb
  • gemini_autogen_multiagent_framework_Marktechpost.ipynb
  • Gemini_Pandas_Agent_Marktechpost.ipynb
  • Getting_Started_with_Mistral_Agents_API.ipynb
  • graph_agent_framework_with_gemini_Marktechpost.ipynb
  • GraphAIAgent_LangGraph_Gemini_Workflow_Marktechpost.ipynb
  • griffe_ai_code_analyzer_Marktechpost.ipynb
  • guide_to_building_an_end_to_end_speech_enhancement_and_recognition_pipeline_with_speechbrain.py
  • how to enable function calling in Mistral Agents.py
  • inflation_agent.py
  • Jina_LangChain_Gemini_AI_Assistant_Marktechpost.ipynb
  • JSON_Prompting.ipynb
  • LangGraph_Gemini_MultiAgent_Research_Team_Marktechpost.ipynb
  • lilac_functional_data_pipeline_Marktechpost.ipynb
  • Live_Python_Execution_and_Validation_Agent_Marktechpost.ipynb
  • Lyzr_Chatbot_Framework_Implementation_Marktechpost.ipynb
  • mcp_gemini_agent_tutorial_Marktechpost.ipynb
  • Mistral_Devstral_Compact_Loading_Marktechpost.ipynb
  • mistral_devstral_compact_loading_marktechpost.py
  • Mistral_Guardrails.ipynb
  • Modin_Powered_DataFrames_Marktechpost.ipynb
  • nebius_llama3_multitool_agent_Marktechpost.ipynb
  • network.ipynb
  • nomic_gemini_multi_agent_ai_Marktechpost.ipynb
  • ollama_langchain_tutorial_marktechpost.py
  • openai_agents_multiagent_research_Marktechpost.ipynb
  • openbb_advanced_portfolio_market_intelligence_Marktechpost.ipynb
  • paperqa2_gemini_research_agent_Marktechpost.ipynb
  • parsl_ai_agent_pipeline_marktechpost.py
  • pipecat_huggingface_implementation_Marktechpost.ipynb
  • polars_sql_analytics_pipeline_Marktechpost.ipynb
  • Presidio.ipynb
  • primisai_nexus_multi_agent_workflow_Marktechpost.ipynb
  • production_ready_custom_ai_agents_workflows_Marktechpost.ipynb
  • prolog_gemini_langgraph_react_agent_Marktechpost.ipynb
  • PyBEL_BioKG_Interactive_Tutorial_Marktechpost.ipynb
  • Pyversity.ipynb
  • README.md
    Good: README is present.
    Issue: README has some structure (−7 pts). 2-3 headings earns partial credit; 4+ earns the full +15 pts.Fix: Add more sections (Overview, Install, Usage, Contributing) using ## headings.
    Good: README includes screenshots or visuals. Great for first impressions.
    Issue: README has no code examples (−15 pts).Fix: Show a quick-start snippet so contributors can see what using your project looks like.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • roboflow_supervision_advanced_tracking_analytics_pipeline_Marktechpost.ipynb
  • sage_ai_agent_gemini_implementation_Marktechpost.ipynb
  • self_hosted_llm_ollama_Marktechpost.ipynb
  • Self_Improving_AI_Agent_with_Gemini_Marktechpost.ipynb
  • Smart_Python_to_R_Converter_with_Gemini_Validation_Marktechpost (2).ipynb
  • smartwebagent_tavily_gemini_webintelligence_marktechpost2.py
  • smolagents_fleet_maintenance_autonomous_agent_Marktechpost.ipynb
  • streamlit_ai_agent_multitool_interface_Marktechpost.ipynb
  • Synthetic_Data_Creation.ipynb
  • tinydev_gemini_implementation_Marktechpost.ipynb
  • UAgents_Gemini_Event_Driven_Tutorial_Marktechpost.ipynb
  • Upstage_Groundedness_Check_Tutorial_Marktechpost.ipynb
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