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

The annotations only indicate read-only and open-world hints. The description goes well beyond this by disclosing the exact FRED series used, the calculation window, update frequency ('quarterly'), and a Gold tier requirement for the history parameter. No side effects are hidden, and the read-only nature is consistent with annotations. This is comprehensive behavioral transparency.

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 two sentences, front-loads the core return value and methodology, and packs the use cases into the second sentence. Every clause adds value; there is no fluff or repetition. It is appropriately sized for the tool's complexity.

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?

Despite having no output schema, the description explicitly lists all returned fields (score, trend, confidence, top_drivers, productivity_yoy_pct, ulc_yoy_pct, z-scores). It also covers access restrictions, update cadence, and intended use cases. For a read-only data retrieval tool with one optional parameter, this is fully complete.

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% for the single optional 'days' parameter, and the schema already explains its behavior (returns daily history, requires Gold tier, otherwise snapshot). The tool description does not add any parameter semantics beyond the schema, so the baseline of 3 is appropriate.

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 exactly what the tool returns: a 0-100 US productivity-vs-labor-cost index with specific data sources, calculation method, and output fields. It clearly distinguishes itself from the many sibling tools by the precise index definition and the listed use cases, making it easy to recognize when this tool is needed.

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 provides explicit triggering conditions: 'Call when the user asks about labor productivity, unit labor costs, wage or cost squeeze, or margin pressure, or when timing earnings-growth and margin assumptions in sector models.' This is clear usage guidance, though it does not mention alternatives or when not to use it, so it doesn't earn a 5.

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