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assessQuality

Analyze image quality by processing stored image files to evaluate visual characteristics and technical parameters.

Instructions

图片处理-图片质量评估

Input Schema

NameRequiredDescriptionDefault
objectKeyYes图片在存储桶里的路径

Input Schema (JSON Schema)

{ "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "objectKey": { "description": "图片在存储桶里的路径", "type": "string" } }, "required": [ "objectKey" ], "type": "object" }

Implementation Reference

  • MCP tool handler that calls the assessQuality service method on CIAIInstance and formats the result into MCP content structure with error flag.
    async ({ objectKey }) => { const res = await CIAIInstance.assessQuality(objectKey); return { content: [ { type: 'text', text: JSON.stringify(res.data, null, 2), }, ], isError: !res.isSuccess, }; },
  • Zod input schema defining the 'objectKey' parameter for the assessQuality tool.
    { objectKey: z.string().describe('图片在存储桶里的路径'), },
  • src/server.ts:339-357 (registration)
    Registration of the 'assessQuality' tool using server.tool, specifying name, description, input schema, and handler function.
    server.tool( 'assessQuality', '图片处理-图片质量评估', { objectKey: z.string().describe('图片在存储桶里的路径'), }, async ({ objectKey }) => { const res = await CIAIInstance.assessQuality(objectKey); return { content: [ { type: 'text', text: JSON.stringify(res.data, null, 2), }, ], isError: !res.isSuccess, }; }, );
  • Core helper function in CIAIService class that performs the Tencent Cloud COS image quality assessment via CI process request.
    async assessQuality(objectKey: string) { try { const result = await this.cos.request({ Bucket: this.bucket, Region: this.region, Method: 'GET', Key: objectKey, Query: { 'ci-process': 'AssessQuality', }, }); return { isSuccess: true, message: '图片处理成功', data: result, }; } catch (error) { return { isSuccess: false, message: '图片处理失败', data: error, }; } }

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