get_source_comments_and_annotations

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

With no annotations provided, the description carries the full burden and does well: it states the tool 'Returns a summary' and defines what comments and annotations are. It does not mention potential side effects or prerequisites, but the retrieval nature is clear and the return semantics are disclosed.

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 concise and front-loaded: the first sentence states the purpose, the second describes the output type, and the third clarifies the difference between comments and annotations. No word is wasted.

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 single-parameter tool with a fully described schema and an output schema, the description covers the essential behavioral aspects. It explains the return content and the nature of the data, making it self-sufficient for an agent to use 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 100% and the parameter source_name is already well-described in the schema. The description adds little beyond the schema, only referring generically to 'a source'. Thus the baseline of 3 is appropriate.

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 ('Retrieve') and resource ('comments and annotations for a source'), clearly distinguishing it from siblings like get_source_photometry or get_source_spectra. It also clarifies the difference between comments and annotations, which helps disambiguate the tool's scope.

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 clearly indicates the tool returns user comments and system/ML annotations, which provides enough context for an agent to decide when to use it. However, it does not explicitly mention alternatives or exclusions (e.g., when to use get_source_classifications instead), so it falls short of full explicit guidance.

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