health

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds something the annotations cannot: that string fields are untrusted institution data and must not be followed as instructions, which is meaningful prompt-injection context for an open-world data source.

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 compact sentences: the return content first, then the safety caveat. Nothing is repeated from the annotations and every clause carries information.

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?

With no output schema, the description correctly summarizes the returned fields and adds the untrusted-data warning, which is enough to call a zero-parameter read tool correctly. It could note whether a healthy connection is indicated by absence of an error code, but the gap is minor.

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 document; baseline applies. The description does not need to compensate for any schema gap.

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 the resource precisely ("Status of each Plaid connection") and enumerates the returned fields (institution, last update, error code), which disambiguates the vague tool name "health" from siblings like accounts/transactions that return financial data. It stops short of explicitly contrasting itself with the siblings, but the distinction is inferable.

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?

Usage is implied rather than stated: an agent can infer this is the diagnostic call to make when a data fetch fails or looks stale, because the description mentions error code and last update. There is no explicit when-to-use/when-not-to-use guidance or named alternative.

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