oqoqo
Build evals and custom benchmarks for real-world tasks
oqoqo lets teams build and run evaluations of AI agents on realistic tasks instead of curated academic benchmarks. Define custom task sets, instructions, rubrics and environments, then run experiments at scale on managed cloud infrastructure against Claude Code, Codex, Cursor, GitHub Copilot and other agents. Results come back as execution trajectories showing tool-call sequences, errors, friction points, token consumption and cost.
What is oqoqo?
oqoqo is a managed platform for building private evaluations and benchmarks that measure how well AI agents can discover and use a product's own surfaces — Skills, MCP servers, CLIs, SDKs, APIs, and docs.
Key features
- Custom task sets, instructions, rubrics, and environments
- Isolated per-task cloud environment with real files, tools, and credentials
- Full execution trajectory captured: tool calls, errors, retries, tokens, and where the agent stopped
- Runs against Claude Code, Codex, Cursor, GitHub Copilot, and other agents
- Comparable results across models and harnesses
- Free tier: 100 runs/month, no card required
Who it's for
- Dev-tool teams that need regression tests when a new agent version ships
- Teams shipping an MCP server, CLI, or SDK who have zero telemetry on how agents actually use it
- Comparing model/agent pairs on domain-specific tasks rather than public leaderboards
When not to use it
Not useful if your product has no programmatic surface for an agent to touch, or if a handful of hand-run traces already answer the question.
FAQ
What does oqoqo capture per task run?
The full execution trajectory — every tool call, error, retry, token spent, and the exact point the agent stopped.
Is there a free tier?
Yes — 100 runs per month with no card required.
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