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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context beyond annotations: it clarifies that total_mi is the whole network, not a single runnable distance, and it explains the error behavior for unknown slugs. It doesn't mention rate limits or pagination, but those are not relevant for a single-resource read tool.

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 well-structured and front-loaded: the first sentence states the core purpose, followed by clear Args, Returns, Examples, and Error handling sections. Every section earns its place, and the total length is appropriate for the tool's complexity. The use of a compact JSON return example is efficient.

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?

The tool has a rich output schema, full parameter documentation, and clear annotations. The description adds the missing context: how to get the slug, what the numbers mean, and what happens on error. An agent has everything needed to select and invoke this tool correctly without opening the schema.

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%, so the schema already documents both parameters. The description adds value by telling the agent where to obtain the slug (from ourpr_list_trail_systems) and by giving a concrete example. It also explains the practical difference between 'markdown' and 'json' output formats, which goes beyond the schema's enum definition.

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 opens with a specific verb ('Read') and a clear resource ('one trail system'), then enumerates exactly what data is returned: miles, mapped ways, location, and source. It is easily distinguished from siblings like ourpr_get_course or ourpr_list_trail_systems, which operate on different resources or list multiple items.

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 explicitly tells the agent to get the slug from ourpr_list_trail_systems, provides concrete examples ('How many miles of trail are in Fort Worth?' -> slug='trinity-trails'), and explains when to use the response_format. It also covers error handling by stating that an unknown slug returns a slug list suggestion. This is strong, actionable guidance.

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