Agent-Skills.md

Agent Skills: Brainstorm Solutions

Generate multiple viable solution options after research is complete, before converging on a single approach. Use when you need to explore the solution space, ask clarifying questions, and produce 3-5 distinct options to consider.

UncategorizedID: kasperjunge/agent-resources/brainstorm-solutions

Repository

kasperjunge/agent-resources
kasperjungeLicense: MIT
39730

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pnpm dlx add-skill https://github.com/kasperjunge/agent-resources/tree/HEAD/.opencode/skill/brainstorm-solutions

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.opencode/skill/brainstorm-solutions/SKILL.md

Skill Metadata

Name
brainstorm-solutions
Description
Generate multiple viable solution options after research is complete, before converging on a single approach. Use when you need to explore the solution space, ask clarifying questions, and produce 3-5 distinct options to consider.

Brainstorm Solutions

Explore the solution space broadly before committing to a single path.

Position in Workflow

Step 2 of development workflow:

  1. /research - Understand problem and constraints
  2. /brainstorm-solutions - Explore solution space (THIS)
  3. /design-solution - Converge on a single solution
  4. Plan, code, review, ship

Core Principle

Breadth first. Generate multiple distinct options before evaluating or ranking them.

Input

Default: Use research findings from the current conversation.

If argument provided:

  • File path: Read the file for research context
  • GitHub issue: Fetch with gh issue view $ARG --comments

Workflow

1. Gather Context

  • Summarize the problem, constraints, and goals from research.
  • Identify existing architecture patterns and similar implementations.

2. Ask Clarifying Questions

Ask only what improves solution quality:

  • Business goals and priorities
  • User workflows and usage patterns
  • Performance or scalability requirements
  • Extensibility or future roadmap considerations
  • Hard constraints (timeline, compatibility, cost)

3. Generate Options

Generate at least 3-5 distinct approaches across dimensions:

| Dimension | Examples | |-----------|----------| | Architectural approach | Event-driven vs request-response, monolith vs service | | Implementation strategy | Extend existing module vs new module, refactor vs add | | Library/tool choice | Redis vs in-memory, REST vs GraphQL | | Feature design | Wizard flow vs single form, eager vs lazy loading |

Avoid anchoring on the first idea. Expand, then refine.

4. First Principles Check

For each option, challenge assumptions:

  • Do we need this?
  • Are requirements correct?
  • Are existing patterns optimal?
  • What is the simplest viable solution?
  • What would we regret in 6 months?

Output Format

## Solution Brainstorm

### Context Summary
[Brief restatement of problem and key constraints]

### Clarifying Questions
[Questions about strategy, usage, or requirements - if any]

---

### Options

#### Option 1: [Name]
[Description]

#### Option 2: [Name]
[Description]

#### Option 3: [Name]
[Description]

[Add Option 4/5 if useful]

---

### Notes
[Any assumptions or risks that should be validated before choosing]

### Next Step
Ready to converge on a single solution. Run `/design-solution`.

Common Mistakes

| Mistake | Fix | |---------|-----| | Anchoring on first idea | Generate 3-5 options BEFORE evaluating any | | Shallow codebase exploration | Read related files and patterns first | | Assuming requirements | Ask clarifying questions early | | Skipping first principles | Apply first principles to each option | | Rushing to recommendation | Save evaluation for design-solution |

What NOT to Do

  • Do NOT present only one option
  • Do NOT recommend a solution yet
  • Do NOT skip clarifying questions when uncertainty exists
  • Do NOT ignore existing codebase patterns