get_cloud_diagram_components

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

Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds that it returns diagrams with connected layers and optionally components, and that it is a discovery endpoint. Does not disclose rate limits or auth, but annotations cover safety.

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?

Four sentences, tightly organized. Each sentence serves a purpose: usage context, output summary, primary discovery hint, parameter filtering options, and exclusions.

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?

No output schema, but description states return value: diagrams with connected layers and optionally components. Given the tool's discovery role and many siblings, this is sufficient. Could mention potential volume or pagination, but not required.

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 100%, baseline 3. Description adds practical context: explains when to set include_components=true (to get component IDs for other endpoints) and mentions skip_empty defaults to false. This adds value beyond schema descriptions.

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 discovers all cloud infrastructure diagrams and their layers, and retrieves layer IDs. It explicitly distinguishes from sibling tools like run_query and search_cloud_diagrams.

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?

Provides explicit guidance: uses it as primary discovery before endpoints needing layer ID, and explicitly says NOT to use for cost analysis (use run_query) or diagram search (use search_cloud_diagrams).

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