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benchclaw-stage3-simulator-evidence-compilation

Compile BenchClaw Stage 3 simulation evidence by cleaning data and generating ground truth annotations.

Updated May 7, 2026
Search Tags:#simulation#data processing#benchclaw#ground truth generation#evidence compilation
One-click install
npx skills add https://github.com/EurecaMoment/BenchClaw --skill benchclaw-stage3-simulator-evidence-compilation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: benchclaw-stage3-simulator-evidence-compilation
Source: https://github.com/EurecaMoment/BenchClaw/tree/main/BenchClaw/skills/benchmark-stage3-evidence-compiler/skills/simulator-evidence-compilation
Command: npx skills add https://github.com/EurecaMoment/BenchClaw --skill benchclaw-stage3-simulator-evidence-compilation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires opencode, data-juicer, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the compilation of simulation evidence for BenchClaw Stage 3, streamlining the process of evidence preparation and reducing manual labor.

Core Features & Use Cases

  • Evidence Compilation: Automatically collects and compiles simulation evidence for BenchClaw Stage 3.
  • Data Cleaning: Utilizes Data-Juicer for cleaning simulation data.
  • GT Generation: Generates Ground Truth and annotation records for the simulation data.
  • Use Case: This Skill is ideal for researchers and data scientists who need to automate the evidence preparation phase of BenchClaw Stage 3 for their benchmarking efforts.

Quick Start

To compile evidence for BenchClaw Stage 3, run the 'benchclaw-stage3-simulator-evidence-compilation' skill with the 'stage3_execution_plan' and 'data_16_simulator_collection_bundle' inputs.

Frequently Asked Questions about benchclaw-stage3-simulator-evidence-compilation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate ground truth generation for simulation data?▼

Automate ground truth generation for simulation data by running the evidence compilation skill with your execution plan and simulator collection bundle to automatically clean data and generate annotation records.

What is the best way to compile simulation evidence for embodied AI benchmarking?▼

Compiling simulation evidence for embodied AI benchmarking is best handled by an automated skill that collects simulation data, cleans it, and generates ground truth annotations to streamline evidence preparation.

Do I need Data-Juicer to clean simulation data for benchmarking?▼

Yes, you need Data-Juicer to clean simulation data for benchmarking because this evidence compilation process utilizes it specifically for data processing alongside Opencode's subagent execution model.

How do I prepare simulator data for BenchClaw Stage 3 evidence compilation?▼

Prepare simulator data for BenchClaw Stage 3 evidence compilation by gathering your stage3 execution plan and simulator collection bundle, then running the skill to automatically process and annotate the simulation evidence.

Can I use Opencode subagents for robotics simulation data processing?▼

Yes, you can use Opencode subagents for robotics simulation data processing, as this evidence compilation skill requires Opencode's subagent execution model to automate the cleaning and annotation workflow.

What inputs are required to generate ground truth annotations for simulation data?▼

Generating ground truth annotations for simulation data requires two inputs: a stage3 execution plan and a simulator collection bundle, which together drive the automated cleaning and annotation process.

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