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

With no annotations, the description carries transparency burden. It discloses that the returned question differs by category, gives concrete examples of what it considers decisive for specific categories, and lists the taxonomy components. This goes beyond the schema and sets accurate expectations, though it doesn't mention any side effects (not relevant for a read-only lookup).

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 concise and front-loaded with the core purpose. It packs substantive examples and taxonomy details into two sentences without redundancy. Every clause earns its place, and the structure flows from purpose to examples to usage guidance.

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?

There is no output schema, so the description must convey what the tool returns; it does list the decisive question and the taxonomy with examples. It also provides usage context. It could be more explicit about the exact structure of the output (e.g., fields per category), but for a reference-style tool the description is sufficiently complete.

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 baseline is 3. The description adds value by explaining what the category parameter returns (e.g., video, design, API, chat examples) and that omitting category returns the full taxonomy, but these meanings are already largely captured in the schema descriptions. The description doesn't introduce syntax or format details beyond the schema.

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 returns the decisive question for a category of AI tools and the free-tier metering taxonomy, with specific verb 'Get' and resource. It distinguishes itself from siblings like get_free_tier_limit and compare_free_tiers by focusing on the 'question to ask' before comparing numbers.

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 advises 'Use this before recommending anything in a category' and frames it as a pre-comparison step, providing clear usage context. It doesn't name sibling tools as alternatives, but the context is sufficient for an agent to decide when to invoke it.

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