macro_usa_michigan_consumer_sentiment

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

Annotations already establish readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false. The description adds useful behavioral context beyond that by disclosing the historical coverage from 19700301 to present, the source URL, and the return type as a pandas.DataFrame. It does not cover authentication or rate limits, but those are not central for this kind of public macro data report.

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 definition is short and front-loaded: the first line states the report and coverage, followed by the source URL and return type. The ':return:' line is somewhat redundant because it repeats the first line, but overall it remains appropriately sized for a simple no-parameter data retrieval tool.

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?

For a no-parameter macro time-series report, the description provides the essential context: what the series is, its historical range, its source, and that the return type is a pandas.DataFrame. It does not document output columns, but no output schema exists and the tool is simple enough that the current description is nearly complete for invocation purposes.

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?

This tool has zero input parameters, so there are no parameter semantics to explain. The baseline for a no-parameter tool is 4, and the description does not introduce any confusing or contradictory parameter behavior.

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 clearly identifies the resource: the University of Michigan US consumer sentiment preliminary report, with the historical coverage starting from 19700301. It is specific enough for an agent to know what data this tool returns, but it does not explicitly differentiate itself from related siblings such as macro_usa_cb_consumer_confidence or other US macro sentiment/confidence tools.

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?

The description gives no explicit when-to-use or when-not-to-use guidance, nor does it name a sibling alternative. It only states what the report is and its data range, leaving the agent to infer that this tool should be used when Michigan consumer sentiment data is needed.

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