Eval directory
Evals for CrewAI
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for CrewAI AI products.
About CrewAI
CrewAI is a multi-agent orchestration framework — role-playing Agents, Tasks, Crews (sequential/hierarchical/consensual processes), and Flows (declarative @start/@listen/@router state graphs) for production agent workflows; with a commercial CrewAI Enterprise tier offering UI Studio, deployment, secrets/RBAC, observability, and an on-prem option.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
8/8 packs
Scoring metrics
0/8 packs
Judge rubrics
8/8 packs
Use-case maps
0/8 packs
Pack context
8/8 packs
Available eval packs for CrewAI
8 packs ready to run.
Agents Roles And Goals
Evaluates CrewAI's Agents (Roles & Goals) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Crewai Enterprise And Deployment
Evaluates CrewAI's CrewAI Enterprise & Deployment across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Crews And Process Types
Evaluates CrewAI's Crews & Process Types across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Flows
Evaluates CrewAI's Flows across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Memory And Knowledge
Knowledge RetentionEvaluates CrewAI's Memory & Knowledge across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Tasks
Evaluates CrewAI's Tasks across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Tools Builtin And Custom
Evaluates CrewAI's Tools (built-in + custom) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Training And Evaluation
Evaluates CrewAI's Training & Evaluation across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Why eval CrewAI AI
CrewAI's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for CrewAI measures four dimensions teams care about most when deploying ai platform agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against CrewAI's public product surface and runnable in Corsac with your own data.