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

No annotations are provided, so the description carries the full behavioral burden. It does disclose what the dictionary contains (field names, source, units, employee definitions), which is useful context about the payload. But it never states that this is a safe read-only lookup, whether results are cached or paginated, or anything about the expected size of the dictionary.

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 no filler, and the primary purpose leads. The second sentence is a deliberate disambiguation note rather than padding. Slightly terse given the undocumented search parameter, but structurally clean.

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?

An output schema exists, so return values need no explanation in prose. For a simple single-parameter lookup tool this is close to adequate, but the undocumented 'search' parameter and the absence of any when-to-use guidance leave real gaps.

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?

There is one optional parameter, 'search', with 0% schema description coverage, and the description never mentions it or explains its matching behavior (substring? fuzzy? case sensitivity?). With a single undocumented filter parameter, the description should have compensated and does not.

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 states the resource (bank fields) and enumerates the dictionary's contents — source, units, employee definitions — so an agent knows this returns field metadata rather than data. It also explicitly contrasts itself with the NCUA list_fields sibling, which sharpens the distinction. The verb ('list') is only implied, but the intent is unambiguous.

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 sentence 'Bank fields are separate from the NCUA list_fields dictionary' implicitly routes the agent to the right tool depending on whether the data is bank or credit-union based, which is genuine routing value. However, it never states when to call this tool, whether it requires prior calls (e.g. before bank_metric_series), or any prerequisites.

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