list_categories

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

No annotations provided, so the description carries the full burden. It discloses that the tool is a read-only list operation and details the return fields (e.g., id, name, market_cap). However, it does not mention any side effects, rate limits, or authentication requirements, which is acceptable for a simple list 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 with sections for args and returns, and it is front-loaded with the main purpose. It is concise, though the code block for args and returns adds slight verbosity.

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 the tool has one optional parameter and no output schema, the description adequately covers the input, output, and use case. It explicitly lists return fields, which is sufficient for an 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?

The only parameter is 'order' with an enum of sort orders. The description notes 'order: Sort order,' which adds minimal meaning beyond the schema's 'title' and enum values. The schema coverage is 0% for property descriptions, so the description should compensate more 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 'List all coin categories with aggregated market data (market cap, 24h volume, 24h change).' It specifies the verb (list), resource (coin categories), and differentiates from siblings by explicitly mentioning the use case of finding category IDs for list_top_coins.

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 provides explicit usage: 'Use to discover narratives... and to find category IDs you can pass to list_top_coins(category=...).' This gives clear context for when to use the tool, though it does not mention when not to use it or provide direct alternatives.

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