Ask Shumi (free-form)

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

Annotations indicate readOnlyHint and openWorldHint. The description adds that the tool classifies the query, fetches relevant data, and synthesizes an answer. This contextualizes the behavior well, though it stops short of detailing how the fetching works or potential latency.

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 extremely concise: two sentences that front-load the core purpose and include usage guidelines. No wasted words.

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 free-form tool with 2 well-documented params and supporting annotations, the description provides sufficient context. However, it does not mention the format of the returned answer (e.g., plain text, JSON), which could be a minor gap for an agent expecting structured output.

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 input schema descriptions already cover both parameters (query and archetype) with examples. The tool description does not add further parameter-specific information, so given 100% schema coverage, a baseline of 3 is appropriate.

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 purpose: asking any crypto-market question in natural language, with the sub-steps of classification, data fetching, and synthesis. It explicitly distinguishes itself from specific typed tools, making it unambiguous.

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 guidance: 'Use this when no specific typed tool fits, or for multi-part / comparative questions.' This directly tells the agent when to select this tool over the 23 siblings.

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