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cremich

promptz.dev MCP Server

by cremich

list_prompts

Browse and filter available prompts from promptz.dev to reduce context switching in development workflows.

Instructions

List available prompts from promptz.dev

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoPagination token for fetching the next set of results
tagsNoFilter prompts by tags (e.g. ['CLI', 'JavaScript'])

Implementation Reference

  • The listPromptsToolHandler function that executes the 'list_prompts' tool: parses arguments, fetches prompts using searchPrompts from GraphQL client, maps results, and returns formatted JSON response.
    export async function listPromptsToolHandler(request: CallToolRequest): Promise<CallToolResult> {
      const nextToken = request.params.arguments?.nextToken as string | undefined;
      const tags = request.params.arguments?.tags as string[] | undefined;
      const response = await searchPrompts(nextToken, tags);
      const prompts = response.searchPrompts.results;
    
      const result = {
        prompts: prompts.map((prompt) => ({
          name: prompt.name,
          description: prompt.description,
          tags: prompt.tags || [],
          author: prompt.author,
        })),
        nextCursor: response.searchPrompts.nextToken || undefined,
      };
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(result, null, 2),
          },
        ],
      };
    }
  • Input schema definition for the 'list_prompts' tool in the ListToolsRequestHandler response, specifying cursor and tags parameters.
    {
      name: "list_prompts",
      description: "List available prompts from promptz.dev",
      inputSchema: {
        type: "object",
        properties: {
          cursor: {
            type: "string",
            description: "Pagination token for fetching the next set of results",
          },
          tags: {
            type: "array",
            items: {
              type: "string",
            },
            description: "Filter prompts by tags (e.g. ['CLI', 'JavaScript'])",
          },
        },
      },
    },
  • src/index.ts:108-110 (registration)
    Dispatch registration in the CallToolRequestHandler switch statement, routing 'list_prompts' calls to listPromptsToolHandler.
    case "list_prompts": {
      return await listPromptsToolHandler(request);
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but only states the basic action. It doesn't mention whether this is a read-only operation, how results are returned (e.g., pagination behavior implied by the 'cursor' parameter), rate limits, authentication needs, or what 'available prompts' means in context. This leaves significant gaps for a listing tool.

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 wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information, 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 no annotations and no output schema, the description is incomplete for a tool with two parameters and implied pagination behavior. It doesn't explain what 'available prompts' includes (e.g., public vs. private), how results are structured, or error conditions, leaving the agent with insufficient context for reliable 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?

Schema description coverage is 100%, with both parameters ('cursor' and 'tags') clearly documented in the schema. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline of 3 where 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 ('List') and resource ('available prompts from promptz.dev'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'get_prompt' (which likely retrieves a single prompt) or 'list_rules' (which likely lists rules rather than prompts), missing the opportunity for 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 like 'get_prompt' or 'list_rules'. There's no mention of use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name 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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