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

Annotations already declare readOnly/openWorld/idempotent, so the bar is lower. The description adds genuinely useful context beyond annotations: the Wikipedia data source, historical depth back to 1963, and the fact that changes are S&P-announced swaps with stated reasons — none of which is derivable from structured fields.

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?

Front-loaded with the core purpose, then example queries, then the scope limit. Dense but every clause carries information; the long parenthetical listing the returned fields is the only slightly heavy part.

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?

No output schema exists, and the description compensates by enumerating the returned fields (effective date, ticker/company added, removed, stated reason). Combined with the full-coverage input schema and readOnly annotations, an agent has everything needed to call and interpret it.

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 all four parameters (from, to, index, limit) are documented in the schema with formats and defaults. The description adds no parameter-level syntax or format detail beyond that, so baseline 3 is appropriate.

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 (dated additions/removals from the S&P 500) with source, date range, and the exact fields returned. It clearly differentiates from siblings like index_constituents (current membership) and recent_changes by emphasizing dated historical swaps.

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?

Gives concrete example questions it answers ('what changed in the S&P 500 in 2024', 'when was X removed and what replaced it') and states the scope limit ('Only sp500 is covered'). It doesn't explicitly name which sibling to use instead for other indexes, but the coverage exclusion is clear.

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