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

The annotations already mark this as a safe, read-only, idempotent operation, so the bar for extra value is lower. The description adds meaningful behavioral context beyond annotations: it covers session characterization, event/flow/quiet classifications, evidence-based reasoning, and the data-tier caveat about Pro and Ultimate. There is no contradiction and no hidden side effects implied.

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 opens with a strong 'START HERE' hook and every subsequent sentence earns its place by adding scope, evidence basis, or a data-access caveat. Some wording is slightly lengthy, but it is structured to front-load the key decision and then elaborate on return semantics.

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 needs to convey what the agent will get back, and it does thoroughly: asset classes, economic releases, desk sentiment, supporting evidence, and trading regimes. The guidance about when to use it and what it returns is complete 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?

There are zero parameters, and the schema description coverage is 100%, so there is nothing for the description to add about parameter meanings. The baseline for a no-parameter tool is 4, and the description reinforces that the tool uses no arguments by framing it as a single omnibus call.

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 states a specific verb-resource pairing: 'START HERE for any why-is-the-market-doing-this question' and lists the aggregated content (cross-asset board, scored releases, desk read). It clearly distinguishes itself from the sibling board tools by calling itself the whole-board summary and positioning them as alternatives.

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 tells the agent when to use it ('any why is the market doing this question' and 'Use this before the individual board tools'), and names the alternative class of tools to switch to for narrower data. The guidance that it saves five calls further informs selection behavior.

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