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agentic_kpi_collect

Collects and visualizes key performance indicators for GitHub development workflows to track progress and identify areas for improvement.

Instructions

KPI収集・ダッシュボード生成

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNo集計期間

Implementation Reference

  • The handler function that implements the core logic for the 'agentic_kpi_collect' tool. It runs a Node.js script to collect KPIs for the specified period and returns the output in a formatted response.
      private async handleKPICollect(args: { period?: string }) {
        const period = args.period || '24h';
    
        const { stdout } = await execAsync(
          `node scripts/collect-metrics.js --period=${period}`
        );
    
        return {
          content: [
            {
              type: 'text',
              text: `## 📊 KPI収集完了
    
    **期間**: ${period}
    
    ${stdout}`
            }
          ]
        };
      }
  • The tool definition in the TOOLS array, including name, description, and input schema for validating parameters like 'period'.
    {
      name: 'agentic_kpi_collect',
      description: 'KPI収集・ダッシュボード生成',
      inputSchema: {
        type: 'object',
        properties: {
          period: {
            type: 'string',
            enum: ['6h', '24h', '7d', '30d'],
            description: '集計期間'
          }
        }
      }
    },
  • server.ts:241-242 (registration)
    The switch case that registers and routes calls to the 'agentic_kpi_collect' handler within the CallToolRequestSchema handler.
    case 'agentic_kpi_collect':
      return await this.handleKPICollect(args as any);
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 mentions collecting KPIs and generating dashboards, but fails to describe critical behaviors such as whether this is a read-only or mutating operation, what permissions are required, how data is sourced, or any rate limits. This leaves significant gaps for a tool that likely involves data processing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise with just two phrases ('KPI収集・ダッシュボード生成'), which is efficient and front-loaded. However, it is under-specified rather than optimally concise, as it lacks necessary details for full understanding, slightly reducing its effectiveness.

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

Completeness2/5

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

Given the complexity implied by KPI collection and dashboard generation, with no annotations and no output schema, the description is incomplete. It doesn't explain what KPIs are collected, how the dashboard is generated or returned, or any behavioral traits, making it inadequate for the agent to use the tool effectively.

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?

The input schema has 100% description coverage, with the 'period' parameter well-documented as an enum for aggregation periods. The description does not add any meaning beyond what the schema provides, as it doesn't explain how the period affects KPI collection or dashboard generation. With high schema coverage, the baseline score of 3 is appropriate.

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

Purpose3/5

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

The description 'KPI収集・ダッシュボード生成' states the tool collects KPIs and generates dashboards, which gives a general purpose. However, it's vague about what specific resources or data sources are involved, and it doesn't distinguish this from sibling tools like 'agentic_metrics_view' or 'agentic_issue_analyze' that might also handle metrics or analysis.

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 provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context for KPI collection, or comparisons to sibling tools such as 'agentic_metrics_view' for viewing metrics or 'agentic_issue_analyze' for analysis, leaving the agent with no usage instructions.

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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