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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses that the Census leg requires an API key while the BLS leg is keyless, that sources corroborate each other, and that a failing source is noted rather than fatal. It also clarifies that the returned value is a wage/payroll lower bound, not revenue. This substantially exceeds what annotations alone convey.

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 dense but every sentence earns its place: purpose, data sources, inputs, output semantics, and caveats are each addressed without redundancy. The core value proposition is front-loaded, and the caveats are placed at the end without burying the actionable guidance.

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 four-parameter optional-input tool with no output schema, the description covers inputs, defaults, override behavior, return categories, source-specific requirements, failure handling, and interpretation caveats. An agent has enough information to select the tool, construct valid parameters, and understand what the result means.

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?

Although the schema already documents all four parameters at 100% coverage, the description adds meaningful semantic context: 'naics' overrides 'industry', state/metro are optional with national default, and metro requires the Census key. This helps an agent correctly construct calls beyond the raw schema descriptions.

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 states a specific verb and resource: it provides a TAM/market-size read for an industry in a US geography by joining Census CBP and BLS QCEW data. It distinguishes itself by describing the unique output (establishment count, employment, wage/payroll-based anchor, per-source evidence), which separates it from raw-data siblings like census_business or bls_series.

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 clear context on when to use this tool: when a one-call market-size/TAM estimate is needed, and clarifies that it is informational, not a guarantee. It doesn't explicitly name sibling alternatives or state when NOT to use it, but the 'one-call' framing and market-size definition make the intended use unmistakable.

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