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pushkarsingh32

Semantic Pen MCP Server

create_article

Generate SEO-optimized articles by specifying topic, keyword, word count, language, and tone for content creation.

Instructions

Create a new article

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetArticleTopicYesThe topic/title for the article
targetKeywordNoTarget SEO keyword for the article (optional)
wordCountNoTarget word count (default: 1000)
languageNoLanguage for the article (default: English)English
articleTypeNoType of article (default: Article)Article
toneOfVoiceNoTone of voice (default: Professional)Professional

Implementation Reference

  • The primary handler function that executes the create_article tool logic. It constructs the request payload from input arguments, sends a POST request to the '/articles' API endpoint using makeRequest, and formats a success response with the new article's ID or an error message.
    private async createArticle(args: CreateArticleRequest) {
      const request = {
        targetArticleTopic: args.targetArticleTopic,
        targetKeyword: args.targetKeyword || '',
        wordCount: args.wordCount || 1000,
        language: args.language || 'English',
        articleType: args.articleType || 'Article',
        toneOfVoice: args.toneOfVoice || 'Professional'
      };
    
      const result = await this.makeRequest<CreateArticleResponse>('/articles', {
        method: 'POST',
        data: request
      });
      
      if (result.success && result.data) {
        return {
          content: [
            {
              type: "text",
              text: `āœ… **Article Created Successfully!**\n\n**Topic:** ${args.targetArticleTopic}\n**Article ID:** ${result.data.id}\n**Status:** ${result.data.status}\n**Settings:**\n- Keyword: ${args.targetKeyword || 'None'}\n- Word Count: ${args.wordCount || 1000}\n- Language: ${args.language || 'English'}\n- Type: ${args.articleType || 'Article'}\n- Tone: ${args.toneOfVoice || 'Professional'}\n\nšŸ”„ Your article is being generated. Use \`get_article\` with ID \`${result.data.id}\` to check progress and retrieve the content.`
            }
          ]
        };
      } else {
        return {
          content: [
            {
              type: "text",
              text: `āŒ Failed to create article: ${result.error}`
            }
          ],
          isError: true
        };
      }
    }
  • src/index.ts:309-324 (registration)
    The dispatch logic in the CallToolRequestSchema handler that validates input arguments, constructs the CreateArticleRequest object, and delegates to the createArticle handler function.
    case "create_article": {
      if (!args || typeof args !== 'object' || !('targetArticleTopic' in args) || typeof args.targetArticleTopic !== 'string') {
        throw new Error("targetArticleTopic is required and must be a string");
      }
      
      const createRequest: CreateArticleRequest = {
        targetArticleTopic: args.targetArticleTopic,
        targetKeyword: 'targetKeyword' in args && typeof args.targetKeyword === 'string' ? args.targetKeyword : undefined,
        wordCount: 'wordCount' in args && typeof args.wordCount === 'number' ? args.wordCount : undefined,
        language: 'language' in args && typeof args.language === 'string' ? args.language : undefined,
        articleType: 'articleType' in args && typeof args.articleType === 'string' ? args.articleType : undefined,
        toneOfVoice: 'toneOfVoice' in args && typeof args.toneOfVoice === 'string' ? args.toneOfVoice : undefined,
      };
      
      return await this.createArticle(createRequest);
    }
  • src/index.ts:231-268 (registration)
    The tool registration in the ListToolsRequestSchema response, defining the name, description, and input schema for the create_article tool.
    {
      name: "create_article",
      description: "Create a new article",
      inputSchema: {
        type: "object",
        properties: {
          targetArticleTopic: {
            type: "string",
            description: "The topic/title for the article"
          },
          targetKeyword: {
            type: "string",
            description: "Target SEO keyword for the article (optional)"
          },
          wordCount: {
            type: "integer",
            description: "Target word count (default: 1000)",
            default: 1000
          },
          language: {
            type: "string",
            description: "Language for the article (default: English)",
            default: "English"
          },
          articleType: {
            type: "string",
            description: "Type of article (default: Article)",
            default: "Article"
          },
          toneOfVoice: {
            type: "string",
            description: "Tone of voice (default: Professional)",
            default: "Professional"
          }
        },
        required: ["targetArticleTopic"]
      }
    },
  • TypeScript interface defining the input structure for the createArticle handler, used for type safety.
    interface CreateArticleRequest {
      targetArticleTopic: string;
      targetKeyword?: string;
      wordCount?: number;
      language?: string;
      articleType?: string;
      toneOfVoice?: string;
    }
  • TypeScript interface for the API response from creating an article.
    interface CreateArticleResponse {
      id: string;
      status: string;
      [key: string]: any;
    }
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 but only states the basic action. It doesn't mention what happens after creation (e.g., where the article is stored, if it's editable, permissions needed, or any side effects), leaving significant gaps for a mutation 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 tool with a clear purpose and well-documented schema, making it easy to parse and understand immediately.

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 creation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, where the article is created, or any behavioral nuances. Given the complexity of a 6-parameter mutation tool, more context is needed to guide the agent 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%, so the schema fully documents all 6 parameters with their types, defaults, and descriptions. The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high coverage but not exceeding it.

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 'Create' and the resource 'article', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_article' or 'get_project_articles' beyond the obvious create vs. get distinction, which prevents 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. There are no mentions of prerequisites, when not to use it, or how it relates to sibling tools like 'get_article' or 'search_projects'. The agent must infer usage from context 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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