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

Annotations already declare the tool as read-only and idempotent. The description adds significant behavioral context: it explains the sandboxed environment, the 'spec' variable structure, and the return shape similarity to 'execute', providing transparency beyond the annotations.

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 with no unnecessary words. It front-loads the main purpose, then details, followed by an example and limitations, making it easy to parse.

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's complexity (searching a tool catalog) and lack of output schema, the description covers input, behavior (sandbox, spec variable), output shape, and limitations ('No live YNAB API access'), making it fully complete for effective use.

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 has one parameter 'code' with no description (0% coverage). The description fully compensates by explaining it is a Python snippet that filters the 'spec' list, and provides a concrete example, adding complete semantic meaning 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's purpose: 'Discover available YNAB tools by running a Python snippet against the tool catalog.' It uses a specific verb ('discover') and specifies the resource ('tool catalog'), effectively distinguishing it from sibling tools like 'execute' which run actual API calls.

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 clear context by stating 'No live YNAB API access' and that it returns the same shape as 'execute'. However, it does not explicitly exclude alternative use cases or provide 'when not to use' guidance, though the purpose is implicitly for tool exploration.

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