list_categories

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

Without annotations, the description carries full transparency burden. It clearly states the tool returns categories with project counts, implying a safe, read-only operation with no side effects. The verb 'List' and phrase 'discover what types' indicate a simple query. A small gap exists: it doesn't explicitly state it's read-only, but the context is highly supported.

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 uses two efficient sentences without any wasted words. It front-loads the core purpose ('List all available project categories on AiList with project counts.') and immediately follows with the usage rationale, earning its place completely.

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 no parameters, no output schema, and no annotations, the description fully covers the behavior: it lists categories with counts for directory discovery. For a simple read-only list tool with no inputs or side effects, this is complete and sufficient.

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% with zero parameters, removing the need for parameter documentation. The description adds value by explaining the return contents (project counts included), which goes beyond the empty schema. A baseline of 4 is appropriate given no parameters need clarification.

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's action ('List all available project categories'), identifies the specific resource ('project categories on AiList'), and indicates what information is included ('with project counts'). It also explains the tool's utility, distinguishing it from siblings that search or get individual projects.

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 when to use this tool ('Use this to discover what types of Ai projects are in the directory'). It implicitly contrasts with sibling tools like 'search_projects','get_project', and 'get_trending', which serve different discovery purposes (filtered search vs. broad overview).

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