List API systems

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

No annotations provided, so description carries full burden. It discloses case-insensitive filtering and flavor context, but does not mention default flavor behavior, pagination, or return format. Adequate but not rich.

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?

Two sentences, directly to the point, front-loaded with the main action and key modifiers. No redundant information.

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 simple listing operation, schema covers parameters well, and no output schema exists, the description provides sufficient context for an agent to understand the tool's purpose and primary options.

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 covers 100% of parameters. The description adds value by noting case-insensitivity for the filter, which is not in the schema. It also reiterates the flavor context, though schema already details enum and default.

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 verb 'List', the resource 'API systems (namespaces)', and the context 'for a flavor'. It distinguishes from sibling tools like get_api or search_api by specifying the listing operation and optional filtering.

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 (listing systems for a flavor) and mentions optional filtering. However, it lacks explicit guidance on when NOT to use or comparisons with alternative sibling tools.

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