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blackgirlbytes

GitHub Calendar MCP Server

find_best_assignee

Identify team members with the lightest workload to assign new tasks, optimizing task distribution and balancing team capacity.

Instructions

Find the team member with the lightest workload for assigning new tasks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core handler function that executes the find_best_assignee tool logic by analyzing team workload and selecting the best (least busy) assignee.
    async findBestAssignee(): Promise<string | null> {
      const analysis = await this.analyzeWorkload();
      
      // Return the person with the lightest workload
      if (analysis.leastBusy.length > 0) {
        return analysis.leastBusy[0];
      }
      
      // If no one has a light workload, return the person with the fewest issues
      const lightestMember = analysis.members.reduce((prev, current) => 
        prev.activeIssues < current.activeIssues ? prev : current
      );
      
      return lightestMember.login;
    }
  • src/index.ts:129-137 (registration)
    Tool registration in the MCP server's list of available tools, including name, description, and parameterless input schema.
    {
      name: 'find_best_assignee',
      description: 'Find the team member with the lightest workload for assigning new tasks',
      inputSchema: {
        type: 'object',
        properties: {},
        required: [],
      },
    },
  • MCP tool call dispatcher that invokes the WorkloadAnalysisTool's findBestAssignee method and formats the response.
    case 'find_best_assignee': {
      const bestAssignee = await this.workloadAnalysisTool.findBestAssignee();
      return {
        content: [
          {
            type: 'text',
            text: bestAssignee 
              ? `Best assignee for new tasks: ${bestAssignee}`
              : 'No suitable assignee found - all team members are at capacity',
          },
        ],
      };
    }
  • Key helper method called by findBestAssignee to compute workload analysis for all team members, categorizing their load and identifying least/most busy.
    async analyzeWorkload(): Promise<WorkloadAnalysis> {
      try {
        // Get all open issues
        const issues = await this.githubClient.getAllTeamIssues();
        
        // Get unique assignees
        const assigneeLogins = this.githubClient.getUniqueAssignees(issues);
        
        // Calculate workload for each member
        const members = assigneeLogins.map(login => {
          const memberIssues = issues.filter(issue => 
            issue.assignees.some(assignee => assignee.login === login)
          );
          
          const activeIssues = memberIssues.length;
          const workloadLevel = this.categorizeWorkload(activeIssues);
          const recommendation = this.getRecommendation(workloadLevel, activeIssues);
          
          return {
            login,
            activeIssues,
            workloadLevel,
            recommendation
          };
        });
    
        // Sort by active issues count
        members.sort((a, b) => a.activeIssues - b.activeIssues);
        
        // Find least and most busy members
        const leastBusy = members
          .filter(m => m.workloadLevel === 'light')
          .map(m => m.login);
        
        const mostBusy = members
          .filter(m => m.workloadLevel === 'overloaded' || m.workloadLevel === 'heavy')
          .map(m => m.login);
    
        return {
          members,
          leastBusy,
          mostBusy
        };
      } catch (error) {
        console.error('Error analyzing workload:', error);
        throw error;
      }
    }
  • Type definition for the WorkloadAnalysis return type used in the tool's implementation.
    export interface WorkloadAnalysis {
      members: Array<{
        login: string;
        activeIssues: number;
        workloadLevel: 'light' | 'moderate' | 'heavy' | 'overloaded';
        recommendation: string;
      }>;
      leastBusy: string[];
      mostBusy: string[];
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool finds a team member based on workload, but doesn't describe how workload is measured, what data sources are used (e.g., tasks, calendar events), whether it's read-only or has side effects, or what the output format is. For a tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality and appropriately sized for a tool with no parameters, making it easy for an agent to parse quickly.

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 tool has no parameters (simplifying input) but lacks annotations and an output schema, the description is minimally adequate. It explains what the tool does but doesn't cover behavioral aspects like how workload is determined or what the output looks like. For a tool that likely involves data analysis and returns a recommendation, more context would be helpful, but it meets the basic threshold.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add parameter details, which is appropriate here. Baseline is 4 for 0 parameters, as there's nothing to compensate for, and the description doesn't introduce confusion about inputs.

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: 'Find the team member with the lightest workload for assigning new tasks.' It specifies the verb ('find') and resource ('team member'), and indicates the selection criterion ('lightest workload') and intended use ('assigning new tasks'). However, it doesn't explicitly differentiate from sibling tools like 'analyze_workload' or 'get_team_status', which might provide related but different functionality.

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 implies usage for task assignment based on workload, but provides no explicit guidance on when to use this tool versus alternatives like 'analyze_workload' or 'get_team_status'. It lacks context on prerequisites, exclusions, or specific scenarios where this tool is preferred over siblings, leaving the agent to infer usage from the purpose alone.

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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