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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds useful context beyond annotations: that guessed slugs are rejected and that the result reflects how the library is organized. It does not need to explain return values because an output schema exists.

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?

Two sentences, front-loaded with the primary action and followed by the key usage rationale. Every sentence earns its place with no redundant formulation.

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 simple, single-optional-parameter discovery tool with rich annotations and an output schema, the description covers what an agent needs: what it returns, when to call it, and why guessing is unsafe. Nothing material is missing.

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 description coverage is 100%, so the optional 'contains' parameter is already fully documented in the schema. The description does not add syntax or meaning beyond that, which is acceptable given the schema carries the parameter detail.

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 names a specific verb and resource ('List every topic slug') plus the returned counts, and ties itself explicitly to the sibling tool search_titles. An agent can immediately tell this is the discovery tool for valid topic slugs.

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?

It gives an explicit directive ('Call this before filtering by topic rather than guessing a slug') and explains the consequence of not doing so: an invalid slug guess is rejected. The relationship to search_titles is named directly, leaving little inference needed.

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