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

No annotations are provided, so the description carries the burden, but the zero-parameter schema means there is little behavioral risk to disclose. It does reveal the return contents (tiers, price, networks, facilitators, wallet-configured flag), which is the most useful behavioral fact here, but it says nothing about output shape or size.

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?

A single front-loaded sentence with no filler; the verb comes first and the content list follows. The list is slightly dense but every item names a distinct data category the caller would want to know about.

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?

There is no output schema, so the description must convey what comes back, and it does so by listing the covered dimensions. For a zero-param introspection tool this is close to sufficient; only the structure of the returned data is left unspecified, which is a minor gap.

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?

With zero parameters there is nothing to disambiguate, so the baseline is 4. The description adds value by enumerating the data categories the response will cover, which orients the agent even though no parameters exist.

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 ('Describe') and enumerates the resource it covers: plan-fit query params, tiers, price, networks, facilitators, and wallet configuration status. This is clearly a metadata/introspection tool, distinguishable in intent from the sibling plan_fit which presumably executes queries, though the description never names that sibling to make the contrast explicit.

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 naming and content strongly imply this should be called before plan_fit to learn what inputs are available, but the description never states that usage rule or mentions the sibling. An agent can infer the 'discover params before querying' pattern, but it is inference rather than instruction.

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