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

The annotations already cover read-only, idempotent, non-destructive behavior, and the description adds useful context: monthly frequency, aggregate asset basis, the default category, and the distinction from flow/rating data. It does not describe return shape or units, but it is still transparent about the tool's domain and scope.

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?

The description is dense but not bloated; every clause adds useful information. It front-loads the main purpose with the distinguishing qualifier near the end, though the long single sentence could have been split for easier scanning.

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 read-only query tool with fully documented parameters, the description is quite complete: it covers source, frequency, category semantics, default behavior, and the sibling to use for exploration. The main omission is an explicit statement about return values/units, but the overall context is strong enough for correct selection and invocation.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real semantic value by explaining what the category enum means (repo split by collateral and counterparty, plus securities and other assets) and confirming the default. This goes beyond the raw enum names.

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 clearly identifies the resource (money market mutual fund investment composition from OFR's MMF Data Release) and the exact domain (balance-sheet composition, not credit-rating or fund-flow data). It names the sibling ofr_search_funding_series and explains the distinction, so an agent can disambiguate without inspecting schemas.

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 states when this tool is appropriate (composition data) and what it is not (credit-rating or fund-flow data). It also tells the agent to call ofr_search_funding_series with dataset:"mmf" to discover all underlying series, providing a clear alternative path.

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