Eval directory
Evals for OpenRouter
7 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for OpenRouter AI products.
About OpenRouter
OpenRouter is a unified LLM routing layer that gives developers access to hundreds of models through a single OpenAI-compatible API. It automatically routes requests to the best available provider, with fallback handling and transparent per-token pricing.
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
7/7 packs
Scoring metrics
0/7 packs
Judge rubrics
7/7 packs
Use-case maps
0/7 packs
Pack context
7/7 packs
Available eval packs for OpenRouter
7 packs ready to run.
Byok Isolation Usage Provenance
Evaluates OpenRouter's BYOK Isolation & Usage Provenance across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Model Catalog Alias Stability
Evaluates OpenRouter's Model Catalog & Alias Stability across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Parameter Parity Capability Routing
Evaluates OpenRouter's Parameter Parity & Capability Routing across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Privacy Data Policy Routing
PII LeakageEvaluates OpenRouter's Privacy & Data-Policy Routing across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Provider Fallback Outage Routing
Evaluates OpenRouter's Provider Fallback & Outage Routing across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Router Metadata Observability
Evaluates OpenRouter's Router Metadata & Observability across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Usage Accounting Cost Attribution
Evaluates OpenRouter's Usage Accounting & Cost Attribution across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's LLM routing and aggregation eval coverage.
Why eval OpenRouter AI
OpenRouter'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 OpenRouter 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 OpenRouter's public product surface and runnable in Corsac with your own data.