Agent Skill Tester Sandbox
A no-code playground that lets non-developers test, compare, and rate AI agent skills for cloud tasks like 'audit my S3 buckets' or 'summarize my BigQuery spend' before letting one run against real data.
IT managers and small-team ops leads evaluating AI agents before giving them production access
- Library of pre-built AI agent skills covering common cloud tasks with safety gates
- Sandbox mode that runs any skill against sample data with no real-world side effects
- Side-by-side skill comparison that scores output accuracy, time, and safety
- Trust score that aggregates user ratings and flag any skill that touches destructive actions
Google's release of dozens of cloud agent skills is creating exactly the selection and trust problem this product solves, especially for non-engineer buyers.
Google Cloud study cites 52-60% of organizations deploying agents in 2025 with 39% failing, validating buyer pain; however the specific 'non-developer ops lead' persona evaluating third-party cloud agents is a narrower subset of the broader enterprise agent eval demand.Google Cloud Study Shows AI Agent Deployment Surging in 2025 ↗Top 5 Agent Evaluation Platforms in 2025 ↗
Crowded field: Maxim AI (cross-functional, no-code), Langfuse, Arize, Galileo, Braintrust, plus sandbox infra like E2B/Daytona; Maxim explicitly targets product managers with no-code interfaces, leaving little white space for a similar buyer-evaluation play.Top 5 Agent Evaluation Platforms in 2025 ↗AI Agent Sandboxes Compared ↗
Proven seat+usage pricing in agent eval space (e.g., Maxim AI enterprise tiers, Databricks MLflow), but the target IT manager / small-team ops lead has a smaller budget than the enterprise engineering buyer; cloud sandbox costs also compress margins.Top Agent Evaluation Platforms in 2025: The Definitive Enterprise Guide ↗Databricks MLflow Agent Evaluation Pricing ↗
Agent evaluation is becoming a permanent enterprise discipline as autonomous agents move to production; Google Cloud's marketplace and partner ecosystem signals multi-year infrastructure investment, not hype.Google Cloud AI Agent Marketplace ↗Lessons from 2025 on agents and trust from The Office of the CTO ↗
Non-trivial: requires wrapping many heterogeneous cloud agents, mocking S3/BigQuery environments, and integrating with multiple cloud providers; could leverage existing sandbox infra (E2B/Daytona) but the orchestration layer is still substantial.AI Agent Sandboxes Compared ↗