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

The readOnlyHint annotation already establishes this is a safe, non-mutating read, so the description bears less burden. It adds the underlying endpoint (GET /impacts) but says nothing about result size, ordering, or whether the list is paginated or complete.

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 short sentences with the purpose front-loaded; nothing is padded. The API endpoint line is low-value for an agent but is a single clause and does no harm.

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 read with no output schema, the description is minimal but not broken. It does not indicate what an 'impact area' record contains or how the results relate to the sibling taxonomy lists, which an agent would need to choose 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 takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly implies the call is argument-free.

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?

States a specific verb (List) and resource (impact areas) plus the scope 'available on the site', so the action is unambiguous. It does not differentiate itself from the many sibling list_* tools (list_causes, list_interests, list_clusters), leaving the agent to infer the distinction between these taxonomies.

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?

There is no guidance on when to call this versus list_causes, list_interests, or list_clusters, and no stated prerequisites or typical workflow. The only implied usage comes from the word 'available', which does not tell the agent what the data is for.

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