ai-dev-analytics

Instructions

Implementation Reference

• src/mcp/server.ts:429-468 (handler)

  The handler function `handleLogDeviation` which implements the logic for the `aida_log_deviation` tool.

  function handleLogDeviation(args: any): any {
    const rootCause = args.rootCause || 'other';
    const category = args.category || 'other';
    const { path, data } = ensureRunJson();
    const id = nextId(data.deviations, 'DEV');
    const deviation: DeviationItem = {
      deviationId: id,
      title: args.title,
      rootCauseCategory: rootCause as DeviationItem['rootCauseCategory'],
      deviationCategory: category as DeviationItem['deviationCategory'],
      aiOutput: '',
      expectedOutput: '',
      files: [],
      ruleSedimented: null,
      detectedAt: now(),
      fixedAt: null,
    };
    data.deviations.push(deviation);
    data.summary.deviationCount = data.deviations.length;
    addEvent(data, 'deviation_created', { deviationId: id });
    addTimeline(data, 'deviation', `${id}: ${args.title}`);
    save(path, data);
  
    const result: any = { success: true, deviationId: id, message: `${id} 已记录: ${args.title}` };
  
    // When rootCause is rule-missing, check for pattern and hint rule sedimentation
    if (rootCause === 'rule-missing') {
      const sameCategoryCount = data.deviations.filter(
        d => d.deviationCategory === category && d.rootCauseCategory === 'rule-missing',
      ).length;
  
      if (sameCategoryCount >= 2) {
        result.ruleHint = `同类偏差已出现 ${sameCategoryCount} 次（${category} / rule-missing）。如果修复方案属于项目级技术规范（非业务逻辑），请询问用户是否沉淀为规则：调用 aida_log_rule 工具，传入 content="<规则描述>" category="${category}" sourceDeviation="${id}"`;
      } else {
        result.ruleHint = `rootCause 为 rule-missing，修复后如果属于项目级技术规范（非业务逻辑），请询问用户是否沉淀为规则：调用 aida_log_rule 工具，传入 content="<规则描述>" category="${category}" sourceDeviation="${id}"`;
      }
    }
  
    return result;
  }

• src/mcp/server.ts:201-212 (registration)

  Tool registration for `aida_log_deviation` in the `TOOLS` array.

    name: 'aida_log_deviation',
    description: '当 AI 产出与用户预期不符时调用。记录偏差用于后续分析。当 rootCause 为 rule-missing 时，修复后如果属于项目级技术规范（非业务逻辑），应询问用户是否沉淀为规则。',
    inputSchema: {
      type: 'object',
      properties: {
        title: { type: 'string', description: '偏差描述' },
        rootCause: { type: 'string', enum: [...ROOT_CAUSE_VALUES], description: '根因分类' },
        category: { type: 'string', enum: [...DEVIATION_CAT_VALUES], description: '偏差类别' },
      },
      required: ['title'],
    },
  },