plugins/core/skills/brainstorm-synthesis/SKILL.md
Use when facing hard architectural decisions, multiple valid approaches exist, need diverse perspectives before committing, or want M-of-N synthesis on complex problems
npx skillsauth add technickai/ai-coding-config brainstorm-synthesisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This is the F-thread (fusion) pattern: multiple independent analyses converge into one superior answer. Use it when the decision is hard enough that diverse viewpoints add value. </objective>
<when-to-use> Architectural decisions with multiple valid approaches. Complex problems where no single perspective captures the full picture. High-stakes choices where missing a consideration is costly. Design decisions in /autotask deep mode.Skip for straightforward implementations, well-established patterns, or decisions where one approach is obviously correct. </when-to-use>
<agent-perspectives> Select 3-5 perspectives that illuminate different facets of the problem:Standard perspectives:
Domain-specific perspectives (add based on problem):
Choose perspectives that will genuinely disagree. Similar viewpoints waste the pattern's value. The goal is productive tension that surfaces trade-offs. </agent-perspectives>
<execution> Frame a clear problem statement that includes the decision to be made, relevant constraints, and success criteria.Launch agents in parallel using the Task tool. Each agent receives:
Wait for all agents to complete. Agents work independently without seeing each other's responses.
Synthesize by identifying where agents agree (high-confidence elements), where they disagree (trade-off zones), and which perspective's concerns are most relevant given actual constraints.
Produce a unified recommendation that incorporates the strongest elements from multiple approaches while maintaining coherence. </execution>
<synthesis-patterns> **Consensus elements**: When 3+ agents recommend the same approach for a component, that approach has high confidence. Include it in the final recommendation.Trade-off resolution: When agents disagree, evaluate based on actual project constraints. The pragmatist might win for a prototype; the architect for a core system.
Risk integration: Incorporate security and performance concerns as constraints on the chosen approach rather than alternative approaches.
Complexity calibration: If most agents flag high complexity, the problem may need decomposition before a single solution emerges. </synthesis-patterns>
<output-format> Present the synthesized recommendation:Recommended Approach: Clear description of the unified solution
Why This Approach: Key factors that made this the best choice
Integrated Trade-offs:
Perspectives Incorporated:
Complexity: [Low | Medium | High] with brief justification
Dissenting Views: Any perspective whose core concern wasn't fully addressed, and why the trade-off was acceptable </output-format>
<integration-with-autotask> When called from /autotask in deep mode, brainstorm-synthesis runs during the planning phase for significant architectural decisions.Return a concise recommendation that autotask can incorporate into the plan. The full synthesis rationale goes into the design decisions section of the eventual PR.
Signal when the decision is too close to call - some choices genuinely need human input. Don't force a recommendation when perspectives are evenly split on important factors. </integration-with-autotask>
<key-principles> Diverse perspectives create value. Homogeneous viewpoints waste the pattern.Synthesis beats voting. Don't just pick the most popular approach - integrate the strongest elements from multiple perspectives.
Productive disagreement is the point. When agents agree completely, the problem probably didn't need this pattern.
Know when to escalate. Some decisions genuinely need human judgment. Synthesize what you can, flag what you can't. </key-principles>
research
Use when analyzing YouTube videos, extracting insights from tutorials, researching video content, or learning from talks and presentations
tools
Use when writing prompts, agent instructions, SKILL.md, commands, system prompts, Task tool prompts, prompt engineering, or LLM-to-LLM content
development
Use when writing, reviewing, or refactoring React or Next.js code, optimizing React performance, fixing re-render issues, reducing bundle size, eliminating waterfalls, or improving data fetching patterns
development
Use when debugging bugs, test failures, unexpected behavior, or needing to find root cause before fixing