benchclaw-stage2-plan-generation

To generate an execution plan for benchmark data collection, use this Skill to outline data gathering from real images, existing benchmarks, and simulators. It organizes the process by creating a comprehensive plan that ensures parallel execution and manages task dependencies.

Parallel execution in benchmark data collection plans means running multiple data gathering tasks simultaneously across different sources. This Skill manages the scheduling and dependencies required to execute these tasks in parallel, ensuring an organized and efficient data collection process.

Yes, generating a BenchClaw data collection plan requires an Opencode sub-agent and specific SKILL.md configurations. These dependencies are necessary to manage the execution plan generation and handle the parallel processing of real-image, benchmark, and simulator data sources.

Yes, you can manage dependencies for real-image, existing benchmark, and simulator data sources within a single plan. The Skill generates a unified execution plan that coordinates parallel execution and handles the dependencies across all these varied data sources.

The best way to schedule parallel tasks for benchmark data collection is to generate a detailed execution plan using this Skill. It explicitly manages parallel execution and task dependencies, ensuring that data from real images, existing benchmarks, and simulators is collected efficiently without bottlenecks.