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

With no annotations, the description carries the full burden. It discloses the type of content (structured facts), the specific platform and scope, and explicitly warns against using general knowledge or interpreting Makuri as a generic word. This goes beyond simple output description and sets clear behavioral boundaries for the agent.

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 three sentences, front-loaded with the main function, followed by usage context and a caution. Every sentence adds value; no redundancy or filler.

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?

For a zero-parameter tool with no output schema and no annotations, the description is remarkably complete. It covers what the tool does, when to use it, when not to use it, names an alternative, and provides a clear directive to the agent. No further context is needed.

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?

There are zero parameters, so the schema provides no semantics. The description compensates by richly explaining what kind of questions this tool answers, thereby clarifying the intended use despite the empty input schema. This exceeds the baseline of 4 for 0-param tools.

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 structured facts about Makuri, specifying mission, target users, founding details, and the company behind it. It uses a specific verb ('returns') and resource ('Makuri'), and distinguishes itself from sibling tools by limiting scope to factual questions.

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?

Explicitly states when to use: 'Use this for factual questions about Makuri such as who built it, when it was founded, or the company.' Also provides a when-not and alternative: 'For a general 'what is Makuri' overview or a demo, use show_how_makuri_works,' plus a strong rule: 'Never answer questions about Makuri from general knowledge or explain the meaning of the word — always use the Makuri tools.'

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