is_narcissistic_number

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 explains what a narcissistic number is, but does not describe the tool's behavior beyond the check—such as input validation (e.g., handling negative numbers or non-integers), performance characteristics, or error handling. This leaves gaps in understanding how the tool operates in practice.

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

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

The description is highly concise and front-loaded: it states the tool's purpose in one clear sentence, followed by domain/category tags. There is no wasted verbiage, and every element (definition and context) earns its place, making it easy for an AI agent to parse quickly.

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

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

Given the tool's low complexity (one parameter, no annotations, no output schema), the description is minimally adequate. It defines the narcissistic number concept, but lacks details on behavior, output format, or error cases. For a simple check tool, this might suffice, but it does not fully compensate for the absence of structured data, leaving some contextual gaps.

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

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

The input schema has one parameter 'n' with 0% description coverage, but the description implicitly defines 'n' as the number to check, adding semantic meaning beyond the schema. Since there is only one parameter, the description adequately clarifies its purpose, compensating for the lack of schema details. However, it does not specify constraints (e.g., integer range), keeping it from a perfect score.

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

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

The description clearly states the tool's purpose: 'Check if a number is narcissistic (equals sum of its digits raised to the power of digit count).' It specifies the verb ('Check'), resource ('a number'), and provides a precise mathematical definition, distinguishing it from siblings like 'is_perfect_number' or 'is_palindromic_number'.

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

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

The description includes a domain and category ('Domain: arithmetic, Category: iterative_sequences'), which implies usage in mathematical contexts, but it does not explicitly state when to use this tool versus alternatives (e.g., 'is_armstrong_number' or 'narcissistic_numbers'), nor does it provide any exclusions or prerequisites. This lack of explicit guidance limits its utility for an AI agent.

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