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analyze_resume_text

Analyzes resume text to assess completeness, keyword usage, and skill alignment, then provides targeted optimization recommendations for job applications.

Instructions

对简历文本进行深度分析,提供专业评估和改进建议。系统会分析简历的完整性、关键词使用、技能匹配度等方面,并给出针对性的优化建议,帮助求职者打造更具竞争力的简历。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resumeTextYes

Implementation Reference

  • src/index.ts:263-295 (registration)
    Registration of the MCP tool 'analyze_resume_text' using server.tool(). Includes tool name, description, input schema (zod validation for resumeText), and inline handler function that calls the NovaCV service and formats the response.
    server.tool(
      "analyze_resume_text",
      "对简历文本进行深度分析,提供专业评估和改进建议。系统会分析简历的完整性、关键词使用、技能匹配度等方面,并给出针对性的优化建议,帮助求职者打造更具竞争力的简历。",
      {
        resumeText: z.string()
      },
      async ({ resumeText }, extra) => {
        if (!resumeText) {
          throw new Error("简历文本是必需的");
        }
        
        try {
          const result = await novaCVService.analyzeResumeText(resumeText);
          return {
            content: [
              {
                type: "text",
                text: safeStringify(result)
              }
            ],
          };
        } catch (error: any) {
          return {
            content: [
              {
                type: "text",
                text: `错误: ${error.message || "未知错误"}`
              }
            ],
          };
        }
      }
    );
  • Input schema for the analyze_resume_text tool, defining 'resumeText' as a required string using Zod.
    {
      resumeText: z.string()
    },
  • The execution handler function for the analyze_resume_text MCP tool. Performs input validation, delegates to NovaCVService.analyzeResumeText, and returns formatted content block with safeStringify or error message.
    async ({ resumeText }, extra) => {
      if (!resumeText) {
        throw new Error("简历文本是必需的");
      }
      
      try {
        const result = await novaCVService.analyzeResumeText(resumeText);
        return {
          content: [
            {
              type: "text",
              text: safeStringify(result)
            }
          ],
        };
      } catch (error: any) {
        return {
          content: [
            {
              type: "text",
              text: `错误: ${error.message || "未知错误"}`
            }
          ],
        };
      }
    }
  • Helper method in NovaCVService class that implements the core logic: POST request to NovaCV API endpoint '/api/v1/resumes/analyze' with resumeText, returns response data or throws handled error.
    async analyzeResumeText(resumeText: string): Promise<any> {
      try {
        const response = await this.client.post('/api/v1/resumes/analyze', {
          resumeText
        });
        return response.data;
      } catch (error) {
        this._handleError(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 the full burden of behavioral disclosure. It states the tool provides analysis and suggestions, but lacks details on permissions, rate limits, output format, or whether it's read-only or mutative. This is inadequate for a tool with potential complexity in analysis.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, stating the core purpose in the first sentence. The second sentence elaborates on analysis aspects without redundancy. However, it could be more structured with explicit sections for usage or output.

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, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain the return values, error conditions, or behavioral traits needed for effective tool use, leaving significant gaps for an analysis tool.

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 description implies the parameter 'resumeText' is the text to analyze, but adds minimal meaning beyond the schema's basic type (string). With 0% schema description coverage and 1 parameter, the baseline is 4, but the description doesn't compensate with details like format expectations or constraints, so it scores slightly lower.

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 tool's purpose: '对简历文本进行深度分析,提供专业评估和改进建议' (deeply analyze resume text, provide professional evaluation and improvement suggestions). It specifies the action (analyze) and resource (resume text), though it doesn't explicitly differentiate from sibling tools like 'convert_resume_text' or 'generate_resume_from_text' beyond the analysis focus.

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. It mentions analyzing resume text for completeness, keywords, and skill matching, but doesn't specify prerequisites, exclusions, or compare it to sibling tools like 'convert_resume_text' or 'generate_resume_from_text'.

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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