callout_help

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. While it mentions the tool's purpose and usage context, it lacks details about what the tool actually does behaviorally—such as whether it returns a list of features, provides interactive guidance, or displays documentation. 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.

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

The description is extremely concise and well-structured, consisting of two sentences that directly address purpose and usage guidelines. Every word earns its place, with no redundant information, making it easy to parse and understand 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 complexity (low, with no parameters) and the lack of annotations and output schema, the description is adequate but incomplete. It covers purpose and usage well, but fails to describe what the tool outputs or how it behaves, which is crucial for an AI agent to understand the result of invocation. This leaves gaps in contextual understanding.

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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately focuses on purpose and usage. A baseline of 4 is justified as the description compensates well for the lack of parameters by providing clear context.

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: 'Show what Callout can do and how to use it.' This specifies the verb ('show') and resource ('Callout capabilities and usage'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'init' or 'coach', which might have overlapping introductory functions.

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 provides explicit guidance on when to use this tool: 'Call this when a user first connects or asks about Callout.' This clearly defines the triggering conditions (initial connection or user inquiries about Callout), making it easy for an AI agent to decide when to invoke it versus alternatives.

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