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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.

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Dépôt
codeaholicguy/ai-devkit
Dernière activité de la source
22 août 2026 à 15:05
Langue détectée de SKILL.md
anglais
Étoiles
1 644
Forks
256

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SKILL.md
Instructions source · Aperçu en lecture seule
name
brainstorm
description
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.
# 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.
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