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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond them by specifying the shape of what comes back (value, unit, observation date) and that data is 'current', which matters because no output schema exists. It stops short of noting staleness windows or rate limits, so not a 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?

Front-loaded with the returned payload and its fields, followed by the calling convention. The long enumeration of chart subjects is dense but earns its place since there is no output schema to describe coverage. Slightly list-heavy but no wasted sentences.

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, the description carries the burden of describing returns, and it does so by naming the returned fields and the set of covered charts. The main remaining gap is routing relative to siblings (annual_returns, get_dataset, search_charts), which an agent would have to infer.

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 description coverage is 100% and the single `id` parameter is fully documented in the schema with example values. The description's 'pass id for one chart, or omit it for all' merely restates the schema's 'Omit for every reading' clause, adding no new semantics. Baseline 3 applies when the schema does the heavy lifting.

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 verb+resource ('current headline readings') and enumerates exactly which readings are returned (S&P 500 level, Shiller CAPE, forward P/E, VIX, drawdown, breadth, etc.), so an agent knows precisely what this tool produces. It is clearly distinct from siblings like search_charts and get_dataset, which are lookup/discovery tools rather than a latest-readings snapshot.

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 explains the two calling modes ('Pass id for one chart, or omit it for all'), which is genuine usage context, but gives no guidance on when to prefer this over siblings such as get_dataset or search_charts, and no exclusions. Usage is implied rather than situated against alternatives.

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