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modus_get_historical_attrition

Retrieve historical attrition rates and counts for trend analysis over specified time periods with optional department filter.

Instructions

Get historical attrition metrics for trend analysis. Returns attrition rates and counts over specified time periods.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoTime period for historical data (90, 180, or 365 days)
departmentNoFilter by department name

Implementation Reference

  • Input schema definition for the modus_get_historical_attrition tool, defining parameters: days (90/180/365, default 180) and department (string).
    {
      name: "modus_get_historical_attrition",
      description:
        "Get historical attrition metrics for trend analysis. Returns attrition rates and counts over specified time periods.",
      inputSchema: {
        type: "object",
        properties: {
          days: {
            type: "number",
            enum: [90, 180, 365],
            default: 180,
            description: "Time period for historical data (90, 180, or 365 days)",
          },
          department: {
            type: "string",
            description: "Filter by department name",
          },
        },
      },
    },
  • The tool is registered in the TOOLS array (line 137-156), listed via ListToolsRequestSchema handler (line 388-392), and dispatched via CallToolRequestSchema switch statement (line 642).
    const TOOLS = [
    {
      name: "modus_get_current_headcount",
      description:
        "Get current headcount by team, role, or department with filtering. Returns employee data including roles, departments, and employment status.",
      inputSchema: {
        type: "object",
        properties: {
          department: {
            type: "string",
            description: "Filter by department name (e.g., 'Sales', 'Engineering')",
          },
          role: {
            type: "string",
            description: "Filter by job role (e.g., 'Account Executive', 'SDR')",
          },
          status: {
            type: "string",
            enum: ["ACTIVE", "INACTIVE"],
            default: "ACTIVE",
            description: "Filter by employment status",
          },
        },
      },
    },
    {
      name: "modus_get_attrition_risks",
      description:
        "Get ML-powered attrition risk predictions with confidence scores (0-1). Returns employees at risk of leaving with risk factors and confidence levels. Uses cached insights by default for speed, set fresh=true for real-time analysis.",
      inputSchema: {
        type: "object",
        properties: {
          threshold: {
            type: "number",
            description: "Minimum risk threshold (0-1). Default: 0.7 (70% risk)",
            default: 0.7,
            minimum: 0,
            maximum: 1,
          },
          department: {
            type: "string",
            description: "Filter by role/department name (e.g., 'Account Executive', 'SDR')",
          },
          fresh: {
            type: "boolean",
            default: false,
            description: "Generate fresh insights (slower but current). Default: false (uses cached data for speed)",
          },
        },
      },
    },
    {
      name: "modus_get_open_positions",
      description:
        "Get open job requisitions and hiring forecast by quarter. Returns open positions with status, department, and planned start dates.",
      inputSchema: {
        type: "object",
        properties: {
          status: {
            type: "string",
            enum: ["OPEN", "DRAFT", "CLOSED", "ALL"],
            description: "Filter by requisition status. Default: OPEN",
          },
          department: {
            type: "string",
            description: "Filter by department name",
          },
        },
      },
    },
    {
      name: "modus_get_ramp_profiles",
      description:
        "Get ramp time profiles showing how long new hires take to reach full productivity. Returns month-by-month productivity percentages by role.",
      inputSchema: {
        type: "object",
        properties: {
          role: {
            type: "string",
            description: "Job role to get ramp data for (e.g., 'Account Executive')",
          },
        },
      },
    },
    {
      name: "modus_get_historical_attrition",
      description:
        "Get historical attrition metrics for trend analysis. Returns attrition rates and counts over specified time periods.",
      inputSchema: {
        type: "object",
        properties: {
          days: {
            type: "number",
            enum: [90, 180, 365],
            default: 180,
            description: "Time period for historical data (90, 180, or 365 days)",
          },
          department: {
            type: "string",
            description: "Filter by department name",
          },
        },
      },
    },
    {
      name: "modus_get_sales_breakdown",
      description:
        "Get comprehensive sales breakdown with hiring/capacity analysis including targets, capacity, attrition impact, and quarterly waterfall metrics. Returns month-by-month capacity projections with revenue gaps and hiring needs. The period type is auto-detected: use quarter for quarterly analysis, year for annual, or startDate/endDate for custom ranges.",
      inputSchema: {
        type: "object",
        properties: {
          period: {
            type: "string",
            description: "Period type (optional - auto-detected): YTD, QUARTER, YEAR, CUSTOM_RANGE, LAST_12_MONTHS, NEXT_12_MONTHS",
            enum: ["YTD", "QUARTER", "YEAR", "CUSTOM_RANGE", "LAST_12_MONTHS", "NEXT_12_MONTHS"],
          },
          year: {
            type: "number",
            description: "Year to analyze (e.g., 2025). Required for QUARTER, YEAR, or YTD periods.",
          },
          quarter: {
            type: "number",
            description: "Quarter number (1-4). When specified, automatically uses QUARTER period.",
          },
          startDate: {
            type: "string",
            description: "Start date (YYYY-MM-DD). When specified with endDate, automatically uses CUSTOM_RANGE period.",
          },
          endDate: {
            type: "string",
            description: "End date (YYYY-MM-DD). When specified with startDate, automatically uses CUSTOM_RANGE period.",
          },
          scenarioId: {
            type: "number",
            description: "Optional scenario ID to analyze",
          },
        },
      },
    },
    {
      name: "modus_get_sales_insights",
      description:
        "Get AI-powered sales insights across 30+ categories including revenue gaps, attrition risk, territory performance, pipeline coverage, and competitive analysis. Returns detailed insights with recommendations and confidence scores.",
      inputSchema: {
        type: "object",
        properties: {
          categories: {
            type: "string",
            description: "Comma-separated list of categories (e.g., 'REVENUE_GAP,ATTRITION_RISK,TERRITORY_PERFORMANCE'). Available: REVENUE_GAP, HEADCOUNT_PLANNING, CAPACITY_UTILIZATION, ATTRITION_RISK, ATTRITION_BACKFILLS, PIPELINE_COVERAGE, WIN_RATE_SHIFTS, SALES_CYCLE_BOTTLENECK, TERRITORY_PERFORMANCE, TERRITORY_DESIGN, TERRITORY_LOAD_MGMT, MARKET_EXPANSION, COMPETITIVE_ANALYSIS, SKILLS_GAP, and 20+ more.",
          },
          timeframe: {
            type: "string",
            description: "JSON timeframe (e.g., '{\"months\": 12}')",
          },
          includeRecommendations: {
            type: "boolean",
            default: true,
            description: "Include AI recommendations in results",
          },
          limit: {
            type: "number",
            default: 50,
            description: "Maximum number of insights to return (max: 100)",
          },
          skipCache: {
            type: "boolean",
            default: false,
            description: "Force fresh generation (slower but current). Default: false (uses cached data)",
          },
        },
      },
    },
    {
      name: "modus_get_benchmark_insights",
      description:
        "Get benchmark-driven sales insights with company data and industry comparisons. Optimized for fast retrieval (< 500ms) with multi-layer caching. Returns insights with company metrics (OTE, quotas, attrition rates), industry benchmarks with sources, variance analysis, and actionable recommendations. Use this for comparing your company's metrics to industry standards.",
      inputSchema: {
        type: "object",
        properties: {
          category: {
            type: "string",
            description: "Filter by insight category: 'territory', 'performance', or 'recommendations'. Omit for all categories.",
          },
          force: {
            type: "boolean",
            default: false,
            description: "Force fresh generation bypassing cache (slower). Default: false (uses cached data for speed).",
          },
        },
      },
    },
    {
      name: "modus_get_hiring_timeline",
      description:
        "Get planned hiring timeline with ramp details and quota assignments. Returns hiring schedule with time to hire, start/end dates, territory assignments, monthly ramp percentages, and quarterly quotas.",
      inputSchema: {
        type: "object",
        properties: {
          year: {
            type: "number",
            default: 2025,
            description: "Year to get hiring timeline for",
          },
          scenarioId: {
            type: "number",
            description: "Optional scenario ID to analyze",
          },
        },
      },
    },
    {
      name: "modus_get_performance_leaderboard",
      description:
        "Get top sales performers across key metrics including opportunities created/won, pipeline created, bookings, ASP, and close rate. Returns ranked list of top performers for each metric.",
      inputSchema: {
        type: "object",
        properties: {
          year: {
            type: "number",
            description: "Year for performance data",
          },
          quarter: {
            type: "number",
            description: "Quarter number (1-4)",
          },
          month: {
            type: "number",
            description: "Month number (1-12)",
          },
          limit: {
            type: "number",
            default: 6,
            description: "Number of top performers to show per metric",
          },
        },
      },
    },
    {
      name: "modus_get_team_performance",
      description:
        "Get team performance overview with performance labels (Top performer, High potential, At risk, etc.). Returns employee performance metrics including revenue, bookings, opportunities, pipeline, ASP, and close rate.",
      inputSchema: {
        type: "object",
        properties: {
          year: {
            type: "number",
            description: "Year for performance data",
          },
          quarter: {
            type: "number",
            description: "Quarter number (1-4)",
          },
          month: {
            type: "number",
            description: "Month number (1-12)",
          },
          limit: {
            type: "number",
            default: 50,
            description: "Maximum number of employees to return",
          },
          offset: {
            type: "number",
            description: "Pagination offset",
          },
          sortBy: {
            type: "string",
            description: "Sort by: revenue, bookings, opportunities, pipeline, ASP, closeRate",
          },
          sortOrder: {
            type: "string",
            enum: ["asc", "desc"],
            description: "Sort order: asc or desc",
          },
        },
      },
    },
    {
      name: "modus_get_employee_insights",
      description:
        "Get individual employee performance insights with AI analysis. Returns detailed performance summary including ramp progress, quota attainment, revenue, pipeline coverage, and AI-generated insights about performance trends and concerns.",
      inputSchema: {
        type: "object",
        properties: {
          employeeId: {
            type: "number",
            description: "Employee ID to analyze",
          },
        },
        required: ["employeeId"],
      },
    },
    {
      name: "modus_get_quota_assignments",
      description:
        "Get quota assignments by employee and territory. Returns employee quota assignments with quarterly and annual quotas, territory details, and regional breakdowns.",
      inputSchema: {
        type: "object",
        properties: {
          year: {
            type: "number",
            description: "Year for quota assignments",
          },
          search: {
            type: "string",
            description: "Search employee names",
          },
          region: {
            type: "string",
            description: "Filter by region",
          },
          role: {
            type: "string",
            description: "Filter by job role",
          },
        },
      },
    },
      {
        name: "modus_get_quarterly_capacity",
        description:
          "Get quarterly capacity breakdown showing beginning/end capacity, revenue targets, gaps, attrition impact, backfills, and capacity at risk. Returns 5 quarters (3 previous + current + 1 future) with detailed waterfall metrics. This is the PREFERRED tool for revenue gap analysis.",
        inputSchema: {
          type: "object",
          properties: {
            scenarioId: {
              type: "number",
              description: "Optional scenario ID to analyze",
            },
          },
        },
      },
    ];
  • Handler implementation for modus_get_historical_attrition. Makes a GET request to /api/employees/attrition with days and department params, returns summary with period, attritionCount, terminatedEmployees, and up to 50 employee records.
    case "modus_get_historical_attrition": {
      const { days = 180, department } = args || {};
      const params = new URLSearchParams();
    
      params.append("days", days.toString());
      if (department) params.append("department", department);
    
      response = await modusApi.get(`/api/employees/attrition?${params.toString()}`);
    
      // Extract data - API returns {employees: [], totalCount: 0}
      const data = response.data || {};
      const employees = data.employees || [];
      const attritionCount = data.totalCount || employees.length;
    
      const summary = {
        period: `${days} days`,
        attritionCount,
        terminatedEmployees: employees.length,
      };
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(
              {
                summary,
                employees: employees.slice(0, 50), // Show first 50 terminated employees
                note: employees.length > 50 ? `Showing first 50 of ${employees.length} terminated employees` : null,
              },
              null,
              2
            ),
          },
        ],
      };
    }
Behavior3/5

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

No annotations provided, so description carries full burden. It states output (rates and counts) but doesn't disclose behavior like read-only, auth needs, or data freshness, which is adequate but not thorough for a tool with no annotations.

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?

Two sentences, both essential, front-loaded with purpose and specificity. No redundancy or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, description adequately conveys return of rates and counts. Sibling context is covered by distinct purpose. Minor gap: no mention of edge cases like empty results or date range defaults.

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 coverage is 100%, so baseline is 3. Description adds minimal extra meaning beyond schema descriptions (e.g., 'specified time periods' for days, 'Filter by department name' already in schema).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb 'Get' and resource 'historical attrition metrics' for trend analysis, distinguishing from sibling tools like modus_get_attrition_risks or modus_get_current_headcount.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies use for trend analysis but lacks explicit when-to-use or when-not-to-use guidance, nor does it reference alternatives among the 12 sibling tools.

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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