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Promptopia MCP

by lumile

list_prompts

Browse and discover available prompts in Promptopia MCP to find suitable templates for your AI interactions.

Instructions

Lists all available prompts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler execution for the 'list_prompts' tool: fetches prompts from service and returns them as JSON text content.
    case 'list_prompts': {
      const prompts = await this.promptsService.listPrompts()
      return {
        content: [{
          type: 'text',
          text: JSON.stringify({ prompts }, null, 2)
        }]
      }
    }
  • Registration of the 'list_prompts' tool in the tools list returned by listTools() method.
    {
      name: 'list_prompts',
      description: 'Lists all available prompts',
      inputSchema: {
        type: 'object',
        properties: {}
      }
    },
  • Core implementation of listing prompts by reading JSON files from the prompts directory.
    async listPrompts(): Promise<Prompt[]> {
      try {
        const files = await this.fileSystemService.listFiles(this.promptsDir, '.json')
        
        const prompts: Prompt[] = []
        
        for (const file of files) {
          try {
            const filePath = path.join(this.promptsDir, file)
            const prompt = await this.fileSystemService.readJSONFile<Prompt>(filePath)
            prompts.push(prompt)
          } catch (error) {
            console.error(`Error reading prompt file ${file}:`, error)
            // Continue with other files even if one fails
          }
        }
        
        return prompts
      } catch (error) {
        console.error('Failed to list prompts:', error)
        throw error
      }
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose whether this is a read-only operation, how results are returned (e.g., pagination, sorting), or any constraints like rate limits or authentication needs, which is inadequate for a tool with zero annotation coverage.

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, front-loading the core action. It avoids redundancy and is appropriately sized for a simple list operation, making it easy for an agent 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'lists' entails (e.g., format, structure, or limitations of the returned prompts), leaving gaps in understanding the tool's behavior and results for a read operation.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 for not introducing unnecessary information.

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 verb ('Lists') and resource ('all available prompts'), making the purpose immediately understandable. It distinguishes from siblings like 'get_prompt' (singular) and 'add_prompt' (creation), though it could be more specific about scope or format to reach a perfect score.

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 'get_prompt' (for a single prompt) or 'apply_prompt' (for execution). It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from tool names alone.

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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