la-bench2025

Fetch web content from URLs, extract specific topics using subagents, and save structured summaries as markdown. This skill should be used when other skills or workflows need to retrieve and analyze web documentation. Input is URL(s) and topic names, output is detailed markdown summaries saved to specified paths.

Parse LA-Bench format JSONL files to extract experimental protocol data by ID. This skill should be used when working with LA-Bench datasets to retrieve structured experimental instructions, materials, protocol steps, expected outcomes, and references for a specific experiment entry.

This skill should be used when generating detailed experimental procedures from LA-Bench format JSONL files. It orchestrates multiple subagents to parse input data, fetch reference materials, generate procedures, validate outputs, refine results, and produce final formatted outputs. Triggered by requests to process LA-Bench data or generate experimental protocols from data/public_test.jsonl or data/private_test_input.jsonl files.

Orchestrate the complete LA-Bench experimental procedure generation workflow from JSONL input to validated output. This skill should be used when processing LA-Bench format experimental data to generate and validate detailed experimental procedures. It coordinates parsing, reference fetching, procedure generation, and quality validation with 10-point scoring.

Validate generated experimental procedures against LA-Bench evaluation criteria. This skill orchestrates formal validation (via script) and semantic evaluation (via subagent) to ensure compliance with LA-Bench standards. Use this skill after generating procedures to assess quality before submission.

Orchestrate experimental procedure generation from LA-Bench format input. This skill orchestrates file I/O and delegates procedure generation logic to experiment-procedure-generator subagent. Use this skill when you need to generate step-by-step experimental procedures with quantitative specifications and proper experimental design.

Iteratively refine LA-Bench experimental procedures through validation and regeneration cycles. This skill should be used when improving generated procedures by ID, validating procedure quality against LA-Bench criteria, and managing the refinement loop between procedure-checker and procedure-generator skills. Triggered by requests to refine, improve, or validate LA-Bench procedures in output JSONL files.