# Agent Framework Scorecard (Explained)

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# Score Interpretation

  • 4.5 - 5.0: Industry Leading
  • 4.0 - 4.4: Production Ready
  • 3.5 - 3.9: Mature
  • 3.0 - 3.4: Developing
  • 2.0 - 2.9: Basic
  • Below 2.0: Early Stage

# Different Dimensions of the Scorecard

# 1. Learning Experience

  • Documentation Quality (1-5)

    • Comprehensiveness
    • Up-to-date content
    • Code examples and tutorials
  • Learning Curve (1-5)

    • Time to basic proficiency - How easy is it to get started with the framework and understand the core concepts?
    • Complexity of concepts
    • Available learning resources
  • Developer Tools (1-5)

    • IDE support
    • Debugging capabilities
    • Testing frameworks

# 2. Architecture & Design

  • Deployability (1-5)

How easy is it to deploy the framework in a distributed environment, different cloud providers (Azure, GCP, and AWS) and scale its performance?

  • Scalability (1-5)
    • Handling of concurrent agents
    • Resource management
    • Performance under load
    • Consider the support for asynchronous messaging.
  • Flexibility (1-5)
    • Ability to handle different types of tasks
    • Customization options
    • Integration capabilities

# 3. Capabilities & Features

  • Core Agent Features (1-5)
    • Planning and reasoning
    • Memory management
      • Look at the ability to monitor trends in the number of calls and latency, and the ability to view traces from the application.
      • Consider if it is easy to avoid memory overflow.
      • Look at options for memory, such as short-term and RAG on memory.
    • Decision-making capabilities
  • Tool Integration (1-5)
    • Built-in tools
    • Ease of adding new tools
    • Consider the ease of using both closed-source and open-source models.
    • Consider the level of support for different tools, or whether a 'proxy' server is needed to integrate.
    • See whether the framework supports remote tool execution.
    • API integrations
  • Important Features (1-5)
    • Streaming: Does the framework support streaming of tokens or messages?
    • Human-in-the-Loop: How well does it support human intervention?
    • Languages: What programming languages does it support?
    • Low-Code Tools: Does it offer a low-code interface for creating agents?
  • Language Model Support (1-5)
    • Number of supported LLMs
    • Ease of switching between models
    • Implementation quality

# 4. Production Readiness

  • Stability (1-5)

    • Production track record
    • Bug frequency
    • Update reliability
  • Security (1-5)

    • Authentication & authorization
    • Data protection
    • Security best practices
  • Monitoring & Observability (1-5)

    • Logging capabilities
    • Performance metrics
      • Look at the ability to monitor trends in the number of calls and latency, and the ability to view traces from the application.
    • Debugging tools
    • Time Travel: Can you go back in time after a task is completed to see how the agent behaved?
    • Look for the ability to monitor tokens used, latency, and error rates.

# 5. Community & Support

  • Community Size (1-5)
    • GitHub stars/forks
    • Active contributors
    • Community engagement
    • Market place for Agents
  • Support Quality (1-5)
    • Issue response time
    • Commercial support options
    • Community help availability
  • Ecosystem (1-5)
    • Third-party plugins
    • Integration examples
    • Community resources

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