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Zenobia000

VibeCoding System

by Zenobia000

start-clarification

Initiate project clarification by defining the project name and initial description to streamline the development process within the VibeCoding System.

Instructions

Start a project clarification process

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
initialDescriptionNoInitial description of the project
projectNameYesThe name of the project

Implementation Reference

  • Core handler function that creates a project object, saves it to context, and returns the first clarification question.
    async startProjectClarification(projectName: string, initialDescription: string = ""): Promise<{
      question: string;
    }> {
      const projectPath = process.cwd();
      const project = createProjectObject(projectName, initialDescription, projectPath);
      this.saveCurrentProject(project);
    
      const firstQuestion = DEFAULT_CLARIFICATION_QUESTIONS[0];
      return {
        question: firstQuestion,
      };
    }
  • MCP CallToolRequest handler case for 'start-clarification' that parses arguments, calls the core handler, and formats the response.
    case 'start-clarification': {
      const { projectName, initialDescription } = z.object({
        projectName: z.string(),
        initialDescription: z.string().optional()
      }).parse(args);
      
      const result = await contextManager.startProjectClarification(projectName, initialDescription);
      return {
        content: [
          {
            type: 'text',
            text: `🚀 Project clarification started for "${projectName}".\n\nQuestion 1: ${result.question}`
          }
        ]
      };
    }
  • Tool registration in ListTools response, including name, description, and input schema definition.
      name: 'start-clarification',
      description: 'Start a project clarification process',
      inputSchema: {
        type: 'object',
        properties: {
          projectName: {
            type: 'string',
            description: 'The name of the project'
          },
          initialDescription: {
            type: 'string',
            description: 'Initial description of the project'
          }
        },
        required: ['projectName']
      }
    },
  • Input schema for the 'start-clarification' tool defining parameters projectName (required) and initialDescription (optional).
    inputSchema: {
      type: 'object',
      properties: {
        projectName: {
          type: 'string',
          description: 'The name of the project'
        },
        initialDescription: {
          type: 'string',
          description: 'Initial description of the project'
        }
      },
      required: ['projectName']
    }
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. It states 'start a process' but doesn't disclose behavioral traits like whether this initiates a long-running task, requires user authentication, has side effects, or what the expected outcome is. This leaves significant gaps for an agent to understand the tool's 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 with zero waste. It's front-loaded and appropriately sized for the tool's purpose, making it easy to parse quickly.

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 starting a process with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, how the clarification process works, or any behavioral context, leaving the agent with insufficient information for effective use.

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?

The input schema has 100% description coverage, with clear documentation for both parameters. The description adds no additional meaning beyond the schema, such as explaining how 'initialDescription' and 'projectName' relate to the clarification process. Baseline 3 is appropriate as the schema does the heavy lifting.

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 action ('start') and the resource ('project clarification process'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'provide-clarification' or 'generate-prd', which might involve similar clarification activities, so it's not fully specific.

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 like 'provide-clarification' or 'generate-prd'. It lacks context about prerequisites, such as whether this is an initial step in a workflow or when it's appropriate to invoke.

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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