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Modus MCP Server

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by mod-us

modus_get_team_performance

Retrieve team performance overview with performance labels (e.g., Top performer, At risk) and employee metrics including revenue, bookings, opportunities, pipeline, ASP, and close rate.

Instructions

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear for performance data
quarterNoQuarter number (1-4)
monthNoMonth number (1-12)
limitNoMaximum number of employees to return
offsetNoPagination offset
sortByNoSort by: revenue, bookings, opportunities, pipeline, ASP, closeRate
sortOrderNoSort order: asc or desc

Implementation Reference

  • Input schema definition for modus_get_team_performance tool. Defines parameters: year, quarter, month, limit (default 50), offset, sortBy, sortOrder.
    {
      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",
          },
        },
      },
    },
  • Tool registration in the TOOLS array (line 290-329). The array is used by the ListToolsRequestSchema handler to advertise available tools.
    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_team_performance. Extracts args (year, quarter, month, limit, offset, sortBy, sortOrder), calls GET /api/sales/performance/team, processes response with summary statistics (totals, averages, counts by label), and returns JSON result.
    case "modus_get_team_performance": {
      const { year, quarter, month, limit = 50, offset, sortBy, sortOrder } = args || {};
      const params = new URLSearchParams();
    
      if (year) params.append("year", year.toString());
      if (quarter) params.append("quarter", quarter.toString());
      if (month) params.append("month", month.toString());
      if (limit) params.append("limit", limit.toString());
      if (offset) params.append("offset", offset.toString());
      if (sortBy) params.append("sortBy", sortBy);
      if (sortOrder) params.append("sortOrder", sortOrder);
    
      response = await modusApi.get(`/api/sales/performance/team?${params.toString()}`);
      const data = response.data || {};
      const team = data.employees || [];
    
      // Add summary statistics
      const summary = {
        totalEmployees: team.length,
        countByLabel: groupByLabel(team),
        teamTotals: {
          revenue: team.reduce((sum, emp) => sum + (emp.revenue || 0), 0),
          bookings: team.reduce((sum, emp) => sum + (emp.bookings || 0), 0),
          opportunities: team.reduce((sum, emp) => sum + (emp.opportunities || 0), 0),
          pipeline: team.reduce((sum, emp) => sum + (emp.pipeline || 0), 0),
        },
        teamAverages: {
          ASP: team.reduce((sum, emp) => sum + (emp.ASP || 0), 0) / team.length || 0,
          closeRate: team.reduce((sum, emp) => sum + (emp.closeRate || 0), 0) / team.length || 0,
        },
        topPerformer: team[0]?.name || null,
      };
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify({ summary, team, total: data.total || 0 }, null, 2),
          },
        ],
      };
    }
  • Helper function groupByLabel used by the team performance handler to count employees grouped by their performance label.
    // Team Performance Helpers
    function groupByLabel(team) {
      const groups = {};
      if (!team || !Array.isArray(team)) return groups;
      team.forEach((emp) => {
        const label = emp.label || "No label";
        groups[label] = (groups[label] || 0) + 1;
      });
      return groups;
    }
Behavior2/5

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

With no annotations, the description must fully convey behavioral traits. It mentions returned metrics but omits critical details such as read-only nature, pagination behavior (despite having offset parameter), authentication requirements, or any side effects. The lack of such information limits transparency.

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 concise at two sentences, front-loading the primary purpose and key labels. Every sentence adds value without unnecessary detail, making it efficient for quick comprehension.

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

Completeness3/5

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

Given the complexity (7 optional parameters, no output schema), the description provides a good overview of returned metrics but misses important context: how time dimensions interact, return format, sorting behavior implications, and any prerequisites. It is adequate for basic understanding but incomplete for fully autonomous invocation.

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 descriptions cover 100% of parameters, providing basic meaning per param. The description adds high-level context about the output but does not elaborate on parameter usage beyond the schema. For example, it lists metric names that map to sortBy values, which is already in the schema. Thus, the description adds marginal value, consistent with the baseline of 3.

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 it gets a team performance overview with specific metrics and labels, making the purpose clear. However, it does not explicitly differentiate this tool from siblings like modus_get_performance_leaderboard or modus_get_sales_insights, which could be distinct in scope or granularity.

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?

No guidance is provided on when to use this tool versus alternatives. The description only explains what it returns, leaving the agent to infer appropriate usage context without any explicit when-to-use or when-not-to-use advice.

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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