get_collection_docs

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

Annotations already declare readOnlyHint=true, so the description carries less burden. The description adds useful behavioral context: the result shape, error handling, and that it is a single API call. No contradiction with annotations. It could mention more about potential side effects (none expected) but overall adds value.

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 brief (4 sentences) and front-loaded: first sentence states purpose, followed by return shape and error case. Every sentence adds value with no redundancy or fluff. It is well-structured and easy to parse.

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 moderate complexity, full schema coverage, annotations, and an existing output schema, the description covers all essential aspects: purpose, result shape, error handling, and the fact that it is a single call. It fully compensates for any missing details in structured fields and is complete for an AI agent to understand the tool's behavior.

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?

Input schema coverage is 100%, so the schema already documents both parameters with descriptions. The tool description does not add any extra meaning beyond the schema. According to guidelines, baseline is 3 when schema coverage is high, which is appropriate here.

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 gets full module documentation for all modules in a collection from Galaxy, distinguishing it from sibling tools like get_module_doc or get_plugin_doc. It specifies the action ('get'), the resource ('full module documentation for all modules in a collection'), and the scope ('single API call without installing'). This is specific and 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 implies when to use this tool (for bulk collection docs) versus alternatives (e.g., get_module_doc for a single module). It provides context by noting it returns all module docs in one call. However, it does not explicitly state when not to use it or list alternative tools, leaving some implicit judgment to the AI agent.

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