summarize_text

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses that the tool uses an external AI provider, implying a network call and potential nondeterminism, but it does not mention side effects, data handling, or privacy implications of sending arbitrary text to a provider. This is a moderate gap, though the non-destructive nature of summarization reduces the risk.

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?

A single sentence that front-loads the action and resource, includes a useful example, and identifies the underlying mechanism. There is no fluff or redundancy—every word contributes to understanding the tool's purpose.

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?

For a straightforward summarization tool, the description covers the purpose, input type, and mechanism. The return value (a summary) is implied, and no output schema exists to explain formatting. The main omission is a note about output format or potential limitations, but this is a minor gap for a tool of this simplicity.

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 schema already documents the 'workspace' and 'instructions' parameters with descriptions, covering 67% of parameters. The 'content' parameter lacks a schema description, but the tool description's 'arbitrary text' clarifies its meaning. The description does not add further parameter-specific detail beyond what the schema provides, so it meets the baseline without exceeding it.

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 states a specific verb ('Summarize') and a clear resource ('arbitrary text'), with a concrete example ('tool output') and the mechanism ('Gateway's configured AI provider'). This clearly differentiates it from workspace-scoped siblings like chat_with_workspace, which would handle workspace-specific context rather than arbitrary text.

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 gives clear context that this tool is intended for arbitrary text, especially tool output, implying it is for content not tied to a workspace. However, it does not explicitly name alternative tools or state conditions when it should not be used, stopping short of full usage guidance.

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