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create_post

Create a new feedback post in a Canny board with title, description, category, and custom fields to collect and organize customer feedback.

Instructions

Create a new post in a Canny board

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
authorIdYesID of the user creating the post
boardIdYesID of the board to create the post in
categoryIdNoID of the category for the post (optional)
customFieldsNoCustom field values as key-value pairs (optional)
detailsNoDetailed description of the post (optional)
titleYesTitle of the post

Implementation Reference

  • The complete createPostTool object defining the 'create_post' MCP tool, including input schema, description, and handler function that validates args, calls CannyClient.createPost, and formats success response.
    export const createPostTool = {
      name: 'create_post',
      description: 'Create a new post in a Canny board',
      inputSchema: {
        type: 'object',
        properties: {
          authorId: { type: 'string', description: 'ID of the user creating the post' },
          boardId: { type: 'string', description: 'ID of the board to create the post in' },
          title: { type: 'string', description: 'Title of the post' },
          details: { type: 'string', description: 'Detailed description of the post (optional)' },
          categoryId: { type: 'string', description: 'ID of the category for the post (optional)' },
          customFields: { 
            type: 'object', 
            description: 'Custom field values as key-value pairs (optional)',
            additionalProperties: true 
          },
        },
        required: ['authorId', 'boardId', 'title'],
        additionalProperties: false,
      },
      handler: async (args: unknown, client: CannyClient) => {
        const { authorId, boardId, title, details, categoryId, customFields } = validateToolInput<CreatePostInput>(args, CreatePostSchema);
        
        const response = await client.createPost({
          authorID: authorId,
          boardID: boardId,
          title,
          details,
          categoryID: categoryId,
          customFields,
        });
        
        if (response.error) {
          throw new Error(`Failed to create post: ${response.error}`);
        }
    
        if (!response.data) {
          return 'Post creation failed - no data returned';
        }
    
        const post = response.data;
        return `Successfully created post!\n\n` +
          `**${post.title}** (ID: ${post.id})\n` +
          `Board: ${post.board.name}\n` +
          `Author: ${post.author.name}\n` +
          `Status: ${post.status}\n` +
          `Created: ${new Date(post.createdAt).toLocaleString()}\n` +
          `URL: ${post.url}`;
      },
    };
  • Zod validation schema (CreatePostSchema) used by validateToolInput in the create_post handler for input validation.
    const CreatePostSchema = z.object({
      authorId: z.string().min(1, 'Author ID is required'),
      boardId: z.string().min(1, 'Board ID is required'),
      title: z.string().min(1, 'Title is required'),
      details: z.string().optional(),
      categoryId: z.string().optional(),
      customFields: z.record(z.any()).optional(),
    });
  • Registration of createPostTool in the main exported tools array for MCP toolset.
    export const tools: Tool[] = [
      // Board management
      getBoardsTool,
      
      // Post management
      getPostsTool,
      getPostTool,
      searchPostsTool,
      createPostTool,
      updatePostTool,
    
      // Extended functionality - temporarily disabled for debugging
      // getCategoresTool,
      // getCommentsTool,
      // getUsersTool,
      // getTagsTool,
    ];
  • CannyClient.createPost helper method invoked by the create_post tool handler to make the API POST request to Canny.
    async createPost(data: {
      authorID: string;
      boardID: string;
      title: string;
      details?: string;
      categoryID?: string;
      customFields?: Record<string, any>;
    }): Promise<CannyApiResponse<CannyPost>> {
      return this.makeRequest<CannyPost>({
        method: 'POST',
        url: '/posts/create',
        data,
      });
    }
  • src/tools/index.ts:3-9 (registration)
    Import statement that brings createPostTool into the index for registration.
    import { 
      getPostsTool, 
      getPostTool, 
      searchPostsTool, 
      createPostTool, 
      updatePostTool 
    } from './posts.js';
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool creates a post, implying a write/mutation operation, but doesn't mention permissions required, rate limits, side effects (e.g., notifications), or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 that directly states the tool's purpose without any fluff or redundancy. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, achieving maximum clarity with minimal verbiage.

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?

For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., post ID, success status), error conditions, or behavioral nuances. While the schema covers parameters well, the overall context for safe and effective use is lacking, especially given the tool's write nature.

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, providing clear documentation for all 6 parameters. The tool description adds no parameter-specific information beyond what's in the schema, so it doesn't enhance understanding of semantics. However, with full schema coverage, the baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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 ('Create') and target resource ('a new post in a Canny board'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'update_post', but the verb 'Create' versus 'Update' provides inherent distinction. The description is specific enough to avoid vagueness or tautology.

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 'update_post' or 'get_posts'. It lacks context about prerequisites (e.g., needing board IDs from 'get_boards'), exclusions, or typical use cases. Without such information, the agent must 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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