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brainstorm_solutions

Generate multiple solution approaches for coding problems with pros and cons analysis to help developers evaluate options and make informed decisions.

Instructions

Generates multiple solution approaches for a problem, with pros/cons for each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
problemYesThe problem to solve
constraintsNoConstraints or requirements
preferencesNoPreferred technologies or approaches

Implementation Reference

  • The core handler function for the 'brainstorm_solutions' tool. It takes problem, constraints, and preferences as input and generates a structured Markdown response outlining three solution approaches (Simple/Direct, Robust/Enterprise, Scalable/Distributed) with pros, cons, and recommendations.
    export function brainstormSolutionsHandler(args: any) {
        const { problem, constraints = [], preferences = [] } = args;
    
        const brainstorm = `# Brainstorm: ${problem}
    
    ## Constraints
    ${constraints.length > 0 ? constraints.map((c: string) => `- ${c}`).join("\n") : "None specified"}
    
    ## Preferences
    ${preferences.length > 0 ? preferences.map((p: string) => `- ${p}`).join("\n") : "None specified"}
    
    ---
    
    ## Solution Approaches
    
    ### Approach 1: Simple/Direct
    **Description**: Straightforward implementation
    **Pros**:
    - Quick to implement
    - Easy to understand
    - Low complexity
    
    **Cons**:
    - May not scale
    - Limited flexibility
    
    **Best for**: MVPs, prototypes, simple cases
    
    ---
    
    ### Approach 2: Robust/Enterprise
    **Description**: Production-ready with full error handling
    **Pros**:
    - Handles edge cases
    - Good error recovery
    - Maintainable
    
    **Cons**:
    - More code
    - Longer development time
    
    **Best for**: Production systems, critical paths
    
    ---
    
    ### Approach 3: Scalable/Distributed
    **Description**: Designed for growth and high load
    **Pros**:
    - Horizontal scaling
    - High availability
    - Future-proof
    
    **Cons**:
    - Complex infrastructure
    - Higher initial cost
    - Operational overhead
    
    **Best for**: High-traffic systems, microservices
    
    ---
    
    ## Recommendation
    Consider starting with Approach 1 and evolving toward Approach 2 as requirements solidify.
    `;
    
        return { content: [{ type: "text", text: brainstorm }] };
    }
  • The Zod schema definition for the 'brainstorm_solutions' tool, defining the input structure: problem (required string), constraints and preferences (optional string arrays).
    export const brainstormSolutionsSchema = {
        name: "brainstorm_solutions",
        description: "Generates multiple solution approaches for a problem, with pros/cons for each.",
        inputSchema: z.object({
            problem: z.string().describe("The problem to solve"),
            constraints: z.array(z.string()).optional().describe("Constraints or requirements"),
            preferences: z.array(z.string()).optional().describe("Preferred technologies or approaches")
        })
    };
  • src/index.ts:83-83 (registration)
    Registration of the 'brainstorm_solutions' tool in the main tool registry Map used by the stdio MCP server.
    ["brainstorm_solutions", { schema: brainstormSolutionsSchema, handler: brainstormSolutionsHandler }],
  • src/server.ts:93-93 (registration)
    Registration of the 'brainstorm_solutions' tool in the HTTP server's tool registry Map.
    ["brainstorm_solutions", { schema: brainstormSolutionsSchema, handler: brainstormSolutionsHandler }],
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output includes 'pros/cons for each', which adds some context beyond basic generation, but fails to describe critical traits like whether this is a read-only operation, if it has side effects, rate limits, or authentication needs. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence: 'Generates multiple solution approaches for a problem, with pros/cons for each.' It is front-loaded with the core purpose and includes the key output detail without any wasted words. Every part of the sentence contributes value, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of generating solution approaches with pros/cons, the description is incomplete. There are no annotations to clarify safety or behavior, no output schema to describe the return format, and no guidance on usage versus siblings. While the purpose is clear, the lack of contextual details makes it inadequate for an agent to fully understand how to integrate this tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, meaning the input schema already documents all parameters ('problem', 'constraints', 'preferences') with descriptions. The tool description adds no additional meaning about parameters beyond what's in the schema, such as examples or usage nuances. According to the rules, with high schema coverage, the baseline is 3 even without param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Generates multiple solution approaches for a problem, with pros/cons for each.' It specifies the verb ('generates'), resource ('solution approaches'), and output format ('pros/cons for each'), which is specific and actionable. However, it doesn't distinguish this from sibling tools like 'compare_approaches' or 'plan_task', which might have overlapping purposes, so it misses full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools like 'compare_approaches', 'plan_task', and 'analyze_architecture', there's no indication of context, prerequisites, or exclusions. This leaves the agent to guess based on tool names alone, which is insufficient for effective selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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