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

Annotations already declare read-only, idempotent, non-destructive, closed-world semantics, so the safety profile is covered. The description adds modestly useful behavior: components are returned and null means 'not measured that day,' plus optional history. It doesn't say what the components are or how the score is derived (a sibling get_methodology presumably covers that).

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?

A single compact sentence with the core reading and its range front-loaded, then scope, then the component/history caveats. Nothing is wasted, though the parenthetical nesting makes it slightly dense.

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?

There's no output schema, so the description carries the return-value burden, and it does name the main return pieces (score, components, optional history series) and the null convention. What's missing is minor: component identities and whether the reading is daily-refreshed versus real-time.

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 both parameters are already documented in the schema, including 'layer slug' and a 1-365 day range. The description's 'omit for the whole index' and 'optional score history' restate the schema rather than adding format or edge-case detail, so baseline 3 applies.

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 a specific resource ('AI Fear & Greed reading') and its scope ('AI stocks overall or one layer'), with a concrete value range (0-100). It is clearly distinguishable from the sibling tools, none of which return an index reading.

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 only implied: read the description as 'call this to get today's sentiment reading.' The one guidance given, omitting layer for the whole index, is really parameter behavior, not when-to-use-versus-alternatives routing.

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