Use this skill when the user wants examples about running several subtasks at once, such as “make it delegate independent work in parallel,” “test whether it knows what can be done simultaneously,” or “give me tasks where scheduling matters.” Trigger it for requests about concurrency, worker allocation, DAG-style plans, replanning after partial results, or situations where serial execution is correct but wasteful. Example triggers: “parallelize the easy parts,” “don’t make it do everything one-by-one,” “test dependency-aware parallel planning,” and “give me realistic workloads with both parallel and dependent steps.”
Extract 1 to 3 concrete cases from the actual benchmark papers to demonstrate this capability, aiming for a maximum of 3 cases. CRITICAL HANDLING FOR TEMPLATES: If the paper provides concrete examples, extract them directly. However, if the paper ONLY provides abstract templates, you MUST NOT just output the template. Instead, you MUST instantiate the template into a highly specific, realistic, and logically coherent example according to the papers. Based on the papers, invent a specific entity, a specific environment, a concrete trajectory, and a final answer that perfectly perfectly reflects the benchmark's exact intent and difficulty. Do NOT state that they are extracted from papers or benchmarks, and absolutely do NOT mention or reference the source papers.
[Case 1]
[Case 2]
To synthesize data for this capability, you must strictly follow a 3-phase pipeline. Do not hallucinate steps. Read the corresponding reference file for each phase sequentially:
Phase 1: Environment Exploration
Read the exploration guidelines to discover raw knowledge seeds:
references/EXPLORATION.md
Phase 2: Trajectory Selection
Once Phase 1 is complete, read the selection criteria to evaluate the trajectory:
references/SELECTION.md
Phase 3: Data Synthesis
Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data:
references/SYNTHESIS.md