aws_describe_view

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

Annotations already mark it read-only, open-world, and non-destructive, so the description doesn't need to restate safety. It adds useful behavioral context by explaining the tool reveals the 'AWS call behind it' and the view's 'output shape,' making clear this is a descriptive, non-executing operation. This goes beyond the schema and complements the annotations without contradicting them.

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 two lines: a front-loaded purpose sentence followed by a minimal parameter explanation. Every clause adds value—the purpose states exactly what is shown, and the args note supplies source and example. No filler, repetition, or unnecessary detail.

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 simple one-parameter read-only introspection tool, the description is complete: it states what the tool shows, how to obtain a valid view_id, and that the call itself is only described. An output schema exists, so the return structure need not be spelled out. The combination of annotations, schema, and description covers everything an agent needs to select and invoke it correctly.

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?

Schema coverage is 0%, so the description bears the full burden for explaining view_id. It does this well: 'A view id from the catalog tool' specifies provenance, and the example 'ec2.instances.list' gives concrete format and namespace conventions. For a single parameter, this is complete and actionable semantic guidance.

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 uses a specific verb and resource: 'Show one view's parameters, output shape and the AWS call behind it.' This clearly identifies the tool as an introspection/metadata operation on a single view, distinguishing it from siblings like aws_read_resource and aws_query, which operate on actual resource data. The focus on view metadata rather than execution makes its purpose unambiguous.

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 contextual guidance: the view_id comes from the catalog tool, with a concrete example ('ec2.instances.list'). This tells the agent where to obtain the required input and implies the tool is used after browsing the catalog. It does not explicitly enumerate when-not-to-use alternatives, but the context is strong enough to avoid confusing this with executing a view or reading a resource.

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