Automatically detects and evaluates LangChain agents and tools with built-in understanding of LangChain patterns.
RAG-focused evaluation patterns and document retrieval validation for LlamaIndex applications.
Native support for Pydantic AI agents with type-safe evaluation execution and validation.
Native OpenAI agent evaluation with built-in understanding of OpenAI's agent conventions.
Google agent framework support with cloud integration capabilities for Gemini models.
Multi-model agent framework support for OpenAI and Anthropic models.
All evaluations run server-side for consistency and scalability, with CLI acting as a coordination layer.
Evaluation configurations stored in `.agentplatform/` folder within your repository, version-controlled alongside your code.
Native GitHub integration with repository selection, branch tracking, and commit monitoring.
Two-tier evaluation system focusing on agent-level behavior and individual tool validation.
Objective scoring of agent response quality, coherence, and helpfulness with threshold visualization.
Semantic drift detection in agent responses with baseline comparison and similarity scoring.
Automated validation of agent return values against expected formats and data types.
Schema validation for structured agent outputs with detailed error reporting and compliance checking.
Multi-run consistency analysis to ensure agent behavior stability across multiple executions.
Main dashboard with system health metrics, real-time activity stream, and sparkline trend visualization.
Environment overview with production, staging, feature branch, and PR environment tracking including agent/prompt counts per environment.
Version-aware agent viewing with commit hash support and performance tracking across deployments.
Prompt detail views with complete version history and commit hash navigation for tracking prompt evolution.
Side-by-side comparison of prompt versions with syntax highlighting for identifying changes between versions.
Tool detail views with version tracking and usage analytics for development tool integration.
Score visualization with thresholds, historical tracking, and detailed result analysis interfaces.
Agent run monitoring with detailed execution logs, configuration metadata, and performance analysis.
Advanced filtering capabilities by status, branch, date range, and performance metrics for run analysis.
PR-specific environment creation and tracking with evaluation results linked to pull request workflows.
Multi-application support with environment-aware switching and status indicators for active, maintenance, and inactive applications.
User permission system with reviewer, developer, and administrator roles for team collaboration.
Framework for defining and running project-specific evaluation criteria beyond built-in tests.
User feedback integration system for collecting and analyzing manual evaluation results.
Comprehensive logging and monitoring of user actions across the platform for audit and analytics.
Flexible system for creating and managing environment variable collections with smart default assignment to Git-based environments and cloning capabilities.
Lightweight command-line tool for running evaluations, authentication, and viewing results from your terminal.
Enhanced automated evaluation comments on GitHub PRs with deployment blocking and detailed regression analysis. Automatically prevent merges when evaluations fail.
Built-in prompt injection and SQL injection testing to validate agent security without additional configuration. Protect against common vulnerabilities automatically.
Compare agent behavior and performance between development, staging, and production environments. Identify environment-specific issues before deployment.
Evaluate uncommitted development code using temporary Git refs without requiring formal commits. Test work-in-progress without cluttering commit history.
Real-time tracking of agent performance, token usage, and cost metrics across deployments. Understand your AI spending at a glance.
Block deployments when evaluations detect regressions in existing agent functionality. Never accidentally deploy a degraded agent again.
Web-based insights and trend tracking for stakeholders and non-technical team members. Share progress with product managers effortlessly.
Compare different agent versions and configurations with statistical significance testing. Make data-driven decisions about agent improvements.
Compare current agent performance against specific Git commits or production branches. Track improvements over time quantitatively.
Cross-platform agent support for Microsoft's Semantic Kernel framework. Evaluate .NET and Python agents seamlessly.
Multi-agent evaluation coordination for CrewAI team-based agent workflows. Test agent collaboration and delegation patterns.
Azure-integrated evaluation for Microsoft's cloud-native agent platform. Leverage Azure infrastructure for scalable testing.
Shared evaluation standards and team coordination tools for larger development organizations. Scale agent development across departments.
Automated security and performance compliance reports for enterprise and regulated environments. Meet audit requirements automatically.
Run specific evaluations using double-colon syntax (e.g., `agents::user_assistant::security`). Target exactly what you want to test.
Single sign-on support for large organizations with existing identity management systems. Seamless authentication for enterprise teams.
On-premises deployment capabilities for organizations with strict data governance requirements. Keep sensitive data within your infrastructure.
Track the percentage of context used in live runs and evaluation runs to optimize agent memory usage and prevent context overflow issues.
Comprehensive audit logging for every agent interaction with selective evaluation capabilities for compliance and debugging purposes.
Automated detection of potential data leaks between users, including jailbreak attempts that could expose unauthorized user information.
Out-of-the-box evaluation for detecting expletives, hate speech, and off-topic jailbreak attempts without requiring unsavory content in your repository.
Custom agentic system that analyzes existing codebases and generates initial evaluation configurations for one-click project setup.
Define evaluation configurations using pure Python instead of TOML for more powerful and dynamic configuration. Enables programmatic eval generation, conditional logic, and better IDE support for Python-first teams.
Export shareable performance reports for agents with evaluation results, metrics, and trends for stakeholder presentations and documentation.