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

With no annotations, the description carries the full burden and does well: it discloses the return fields (reason_codes, signal_strength, risk_band), explains the baseline references (100 and long-run avg ~85), and explicitly warns about the absence of PESSIMISTIC/OPTIMISTIC labels to prevent misinterpretation.

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 is compact and front-loaded with the '[EVIDENCE v1.1]' tag. Each sentence contributes meaningful information: the index name/role, the output fields, and the critical caveat about labels. No filler or redundancy.

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 simple zero-parameter tool, the description covers purpose, output semantics, baseline values, and a key behavioral caveat. It could add interpretation thresholds for signal_strength/risk_band, but is sufficiently complete for an evidence-only utility.

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?

The tool has zero parameters, so the schema provides complete coverage. The description appropriately focuses on outputs rather than inputs, meeting the baseline for parameterless tools.

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 (Michigan Consumer Sentiment Index) and its role (evidence only), and explicitly distinguishes it from the retired macroracle version by stating 'NO PESSIMISTIC/OPTIMISTIC labels.' This makes it distinct among the sibling macro 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?

Usage is implied through 'as evidence only' and the caution about label absence, but there is no explicit statement of when to prefer this tool over alternatives or when not to use it. The context is clear enough for an agent to infer, but explicit guidance is missing.

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