parallel-investigator

Investigate these two topics in parallel using separate Explore subagents:

• Topic 1: $0
• Topic 2: $1

Instructions

1. Spawn two Explore subagents simultaneously — one per topic. Give each a self-contained research prompt that includes:

   • The specific topic to investigate
   • Instructions to search broadly (Grep, Glob) before reading files deeply
   • Instructions to produce a structured report: key files, how it works, notable patterns

   Do not run the subagents sequentially. Start both at the same time.

2. Wait for both subagents to return their results.

3. Combine the findings into a single comparison report with these sections:

   Topic 1 findings — summary of what the first subagent found

   Topic 2 findings — summary of what the second subagent found

   Similarities — patterns, libraries, approaches, or design decisions shared between the two topics

   Differences — how they diverge: in scale, in architecture, in data model, in error handling, or in how they are tested

   Recommendation — if the user is trying to make a decision (e.g., which approach to follow, which subsystem to extend), give a direct recommendation with reasoning. If the topics are purely informational (e.g., understanding two independent systems), omit this section.

Note on architecture

This skill does not use context: fork — it runs inline in your main conversation. This is intentional: a forked skill cannot spawn additional subagents, so any skill that needs to orchestrate multiple workers must run in the main context and delegate the worker tasks from there. The main conversation is the orchestrator; the Explore subagents are the workers.