Skip to main content
Glama

Analyze Burnout Risk

analyze_burnout
Read-only

Assess burnout risk across physical, emotional, and effectiveness dimensions. Provides a score, risk level, factors, urgency rating, and personalized recommendations based on user responses.

Instructions

Score burnout risk across 3 dimensions (physical, emotional, effectiveness). Returns a 0-100 total score, risk level (low/moderate/high/critical), risk factors, urgency rating, and personalized recommendations. Requires 3-20 response items covering at least the 3 dimensions. Free tier: 500 calls/month. All tiers have access.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
responsesYesArray of 3-20 scored responses across the 3 burnout dimensions. Must include at least one item per dimension (physical, emotional, effectiveness).
contextNoOptional context for more personalized analysis
languageNoResponse language: 'fr' (French, default) or 'en' (English)fr
include_recommendationsNoInclude personalized recommendations in the response. Default: true

Implementation Reference

  • Registration and implementation (handler) of the `analyze_burnout` tool.
    server.registerTool(
      "analyze_burnout",
      {
        title: "Analyze Burnout Risk",
        description:
          "Score burnout risk across 3 dimensions (physical, emotional, effectiveness). " +
          "Returns a 0-100 total score, risk level (low/moderate/high/critical), " +
          "risk factors, urgency rating, and personalized recommendations. " +
          "Requires 3-20 response items covering at least the 3 dimensions. " +
          "Free tier: 500 calls/month. All tiers have access.",
        inputSchema: {
          responses: z.array(ResponseItemSchema).min(3).max(20).describe(
            "Array of 3-20 scored responses across the 3 burnout dimensions. " +
            "Must include at least one item per dimension (physical, emotional, effectiveness).",
          ),
          context: ContextSchema,
          language: z.enum(["fr", "en"]).default("fr").optional().describe(
            "Response language: 'fr' (French, default) or 'en' (English)",
          ),
          include_recommendations: z.boolean().default(true).optional().describe(
            "Include personalized recommendations in the response. Default: true",
          ),
        },
        annotations: {
          readOnlyHint: true,
          openWorldHint: true,
        },
      },
      async ({ responses, context, language, include_recommendations }) => {
        const result = await apiRequest("/api/v1/analyze-burnout", {
          method: "POST",
          body: JSON.stringify({
            responses,
            context,
            options: {
              include_recommendations: include_recommendations ?? true,
              include_dimensions: true,
              language: language ?? "fr",
            },
          }),
        });
    
        if (!result.success) {
          return {
            isError: true,
            content: [
              {
                type: "text" as const,
                text: `Burnout analysis failed: ${result.error?.message || "Unknown error"}`,
              },
            ],
          };
        }
    
        const quotaInfo = result.meta
          ? `\n\nAPI Quota: ${result.meta.quota.used}/${result.meta.quota.limit} (${result.meta.quota.tier} tier)`
          : "";
    
        return {
          content: [
            {
              type: "text" as const,
              text: JSON.stringify(result.data, null, 2) + quotaInfo,
            },
          ],
        };
      },
    );
  • Zod schema definitions for the input parameters of `analyze_burnout`.
    const ResponseItemSchema = z.object({
      dimension: z.enum(["physical", "emotional", "effectiveness"]).describe(
        "Burnout dimension to score: physical (sleep, energy, health), emotional (motivation, stress, mood), effectiveness (productivity, focus, achievement)",
      ),
      question_id: z.string().min(1).describe(
        "Identifier for the specific question (e.g., 'sleep', 'motivation', 'productivity')",
      ),
      value: z.number().min(0).max(100).describe(
        "Score from 0 (worst) to 100 (best) for this question",
      ),
      weight: z.number().min(1).max(3).default(1).optional().describe(
        "Importance weight: 1 (normal), 2 (important), 3 (critical). Default: 1",
      ),
    });
Behavior4/5

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

Annotations indicate readOnlyHint=true, and the description adds valuable behavioral context including specific return values (0-100 score, risk levels, urgency rating), rate limits, and tier availability. No contradiction with 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?

Three efficiently structured sentences: purpose first, then requirements, then operational constraints. No redundant information; every sentence adds actionable detail not duplicated in the title or schema.

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

Completeness5/5

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

Despite no output schema, the description comprehensively documents return values. Given the complex nested input structure (4 parameters with enums and nested objects), it adequately covers operational constraints and prerequisites.

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?

With 100% schema coverage (baseline 3), the description reinforces critical constraints ('3-20 response items', 'at least the 3 dimensions') that help agents understand how to properly populate the complex nested 'responses' array parameter.

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?

The description uses specific verbs ('Score burnout risk') and identifies the resource (3 dimensions: physical, emotional, effectiveness). It distinguishes from sibling tools like 'quick_burnout_check' and 'generate_burnout_report' by emphasizing detailed multi-dimensional scoring with specific output metrics.

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

Usage Guidelines4/5

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

The description provides clear prerequisites ('Requires 3-20 response items covering at least the 3 dimensions') and rate limit context ('Free tier: 500 calls/month'). However, it lacks explicit guidance on when to choose this over 'quick_burnout_check' or 'generate_burnout_report'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/gomessoaresemmanuel-cpu/stresszero-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server