What problem does it solve? Complex coding and architecture problems often have multiple plausible approaches with non-obvious trade-offs, and a single-pass answer can miss a better approach. This Skill fans out into N independent solution paths explored in parallel by subagents, then synthesizes a scored recommendation. ## Core Features & Use Cases - Deterministic Signal Matching: Matches problem keywords against a JSON catalog of paradigms, structures, and strategies via Node.js scripts, with an inline fallback when Node is unavailable. - Parallel Subagent Exploration: Spawns 2-4 subagents with slot-filled briefs, enforces anti-overlap via complexity-class and invariant diversity, and validates reports against a JSON schema. - Execution-Backed Scoring: Runs candidate implementations against a shared test set for algorithmic problems, and applies operational scoring plus hybridization checks for architecture problems. - Use Case: Given a sliding-window maximum problem, the Skill selects three genuinely distinct paths (monotonic deque, lazy-deletion heap, block prefix/suffix), executes each against edge and stress cases, and recommends the O(n) deque approach with execution evidence. ## Quick Start Ask the AI to explore and compare multiple solution approaches for your algorithm or system design problem using the engage-exocortex skill.
