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get_salary

Retrieve current compensation details including base salary, stocks, bonus, and total earnings to understand your complete financial package.

Instructions

Get your current salary/compensation details including base, stocks, bonus, and total compensation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The tool "get_salary" is registered and handled here using client.getProfileSalary().
    server.tool(
      'get_salary',
      'Get your current salary/compensation details including base, stocks, bonus, and total compensation',
      {},
      async () => {
        const salary = await client.getProfileSalary();
        return { content: [{ type: 'text' as const, text: JSON.stringify(salary, null, 2) }] };
      }
    );
Behavior2/5

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

No annotations are provided, so the description carries full burden. It indicates a read operation ('Get') but lacks details on permissions required, data freshness, rate limits, or error conditions. For a tool accessing sensitive compensation data with zero annotation coverage, this is a significant gap in behavioral disclosure.

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 front-loads the core purpose and details the specific compensation components. Every word adds value with zero waste, making it highly concise and well-structured.

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's simplicity (0 parameters, no output schema) and lack of annotations, the description adequately covers the purpose. However, it does not address behavioral aspects like authentication needs or return format, which are important for a tool handling sensitive data, leaving some contextual gaps.

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 tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics without redundant parameter info, earning a baseline score above minimum viable.

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 clearly states the specific action ('Get') and resource ('your current salary/compensation details'), including the exact data fields returned (base, stocks, bonus, total compensation). It distinguishes itself from sibling tools like 'update_salary' by focusing on retrieval rather than modification.

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?

The description implies usage for retrieving personal compensation data, but does not explicitly state when to use this tool versus alternatives (e.g., 'get_profile' might include salary, or 'update_salary' for modifications). No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.

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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