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

The readOnlyHint annotation already declares the tool safe, and the description adds meaningful behavior beyond that: it returns all topics with experience-mention counts and exposes slugs. It does not describe ordering or pagination, but for a parameterless listing tool this is a minor gap.

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 tightly written sentences with no filler; the core behavior is front-loaded and the downstream instruction earns its place.

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, read-only, parameterless listing tool, the description is complete: it states what is returned, what metric is included, and how the output connects to sibling tool search_experiences. No output schema is present, but none is needed to invoke this tool correctly.

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 tool has zero parameters, so the schema fully covers inputs; the baseline for a 0-parameter tool is 4. The description adds useful context about the returned slug field and its role in downstream filtering.

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 uses a specific verb ('list') and a concrete resource ('every phenomenon and practice') and names the output metric ('how many experiences mention it'). It clearly distinguishes this from the sibling search tool by positioning list_topics as the source of 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 explicitly instructs the agent to use the returned slugs to filter search_experiences, establishing a clear downstream use and differentiating the listing tool from the search tool. It does not formally state when not to use it or mention get_experience, but the intended context is clear.

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