Eval directory
Evals for OpenAI
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for OpenAI AI products.
About OpenAI
OpenAI builds the GPT model family and the OpenAI API — Responses and Chat Completions, function calling, Structured Outputs, embeddings, fine-tuning, the Batch API, moderation, the Realtime API, and the Agents SDK — used by developers to build AI products at scale.
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 OpenAI
8 packs ready to run.
Batch Api
Evaluates OpenAI's Batch API across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Embeddings And Retrieval
Answer RelevanceEvaluates OpenAI's Embeddings & Retrieval across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Fine Tuning
Evaluates OpenAI's Fine-tuning across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Function Calling And Tool Orchestration
Evaluates OpenAI's Function Calling & Tool Orchestration across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Moderation And Safety
Evaluates OpenAI's Moderation & Safety across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Realtime Api And Reasoning Models
Evaluates OpenAI's Realtime API & Reasoning Models across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Responses And Chat Completions
Evaluates OpenAI's Responses & Chat Completions across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Structured Outputs And Json Schema
Evaluates OpenAI's Structured Outputs & JSON Schema across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Foundation Model & API eval coverage.
Why eval OpenAI AI
OpenAI'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 OpenAI 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 OpenAI's public product surface and runnable in Corsac with your own data.