brainstorm
AI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.
git clone --depth 1 https://github.com/codeaholicguy/ai-devkit /tmp/brainstorm && cp -r /tmp/brainstorm/skills/brainstorm ~/.claude/skills/brainstormSKILL.md
# Brainstorm Run a compact diverge-to-converge loop. ## Workflow 1. Frame: goal, constraints, audience, success criteria, assumptions. 2. Baseline: state the simplest honest solution first. Every option must beat it; the baseline stays a candidate. 3. Diverge: distinct options across practical, high-leverage, and unusual angles. 4. Challenge: weak assumptions, failure modes, tradeoffs, rejections. Always: reject speculative generality (each abstraction, layer, flag, and data copy needs a current caller) and verify load-bearing "needed" claims in the consuming code, not doc assertions. 5. Compare: only relevant criteria, plus deletion cost (how easily the option can be removed later). Ties go to the smaller option. 6. Converge: strongest 3 picks with rationale and a next step. Self-review first: for each new constant, object, layer, and flag ask "why do we need this?" Cut answers that are only messaging or future-proofing. ## Formats Use Quick by default. Use Deep only for ambiguous or high-stakes decisions. Ask at most one clarifying question only if missing context would materially change the brainstorm; otherwise state assumptions and proceed. - Quick: clusters, challenges, 3 picks. - Deep: assumptions, clusters, evaluation table, recommendation. - Naming: tone groups, fit, ambiguity, pronunciation. - Technical: approaches, tradeoffs, risks, validation. - Content: angles, hooks, audiences, outlines. Avoid filler, near-duplicates, generic best practices, premature recommendations, and scope without a current caller. If asked for more ideas, explore a new axis before listing variants.
AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Execute a feature plan task by task.
AI DevKit · Scaffold feature documentation from requirements through planning.
AI DevKit · Store reusable guidance in the knowledge memory service.
AI DevKit · Review feature design for completeness.
AI DevKit · Review feature requirements for completeness.
AI DevKit · Update planning docs to reflect implementation progress.