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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
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Different Dimensions of the Scorecard
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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
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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
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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
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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.
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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