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

Annotations cover the safety profile (readOnly, idempotent, non-destructive), and the description adds substantive context the annotations cannot: the upstream data source and the bidirectional matching semantics (rows returned whether the RSSD ID is predecessor or successor). It stops short of covering edge cases such as institutions with no recorded transformations or data freshness, so not a full 5.

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 purpose is front-loaded and every sentence contributes — event types, source, motivating questions, and return shape. It is a dense single paragraph with heavy em-dash and inline-quote usage, which slightly hampers scannability but wastes nothing.

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 present, the description carries the burden of describing the return and does so precisely: rows where the RSSD ID is predecessor or successor, each with counterpart name, RSSD ID, and event date. Combined with 100% parameter coverage and explicit annotations, an agent has everything needed to call it 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?

Schema coverage is 100% for the single rssd_id parameter, so the baseline is already high. The description genuinely adds meaning by explaining that the ID is matched in either role (predecessor absorbed, or successor that absorbed another), which shapes how an agent interprets the argument beyond the schema's 'NIC RSSD ID'.

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+resource ('history for an institution') and enumerates the event types covered (merger, acquisition, failure, charter-transformation). It also names the data source (Federal Reserve NIC Transformations), which distinguishes it cleanly from siblings like nic_get_institution and nic_get_hierarchy.

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?

Supplies concrete usage questions ('what predecessor institutions merged into this bank?' / 'what happened to this bank?') that map directly onto agent intents, giving clear context for when to reach for it. It does not, however, explicitly contrast itself with the NIC siblings, so selection between them is left to inference.

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