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

Goes well beyond the readOnly/idempotent/openWorld annotations by disclosing a key behavioral quirk: BASIC scores are rarely published per FAST Act 2015, so the tool falls back to an always-available public safety summary. It also supplies interpretation rules (higher BASIC percentile = worse; lower OOS rate = better; national averages included), which is exactly the kind of context annotations cannot carry.

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?

Front-loaded with the core action and the data-availability caveat, and every sentence carries information. The example-question list is slightly padded ('is this carrier safe?', 'what's their safety record?', 'should I hire this carrier?' overlap substantially), costing a point on economy.

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?

There is no output schema, so the description must describe return values, and it does: both return shapes, their component fields (crash counts, fatal/injury crashes, OOS rates, inspection volumes), and comparative baselines. Nothing an agent needs to call and interpret the result is missing.

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% and the single dot_number parameter is already documented with an example and a positivity constraint. The description only restates 'by DOT number', adding no format, lookup, or ambiguity-resolution guidance, so the baseline 3 applies.

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?

States a specific verb and resource ('Get safety information for a trucking company by DOT number') and enumerates the returned content (CSA BASIC percentiles vs. public safety summary). It is clear on its own, but it never distinguishes itself from the crowded FMC/CSA sibling set (fmcsa_carrier_lookup, fmcsa_carrier_authority, fmcsa_carrier_compare, carrier_vetting_score), so an agent must still infer which FMC/CSA tool to reach for.

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?

Provides concrete trigger phrasing ('is this carrier safe?', 'how many crashes?', 'check their inspection history') that maps natural-language questions to this tool, which is strong positive guidance. However, it gives no when-not conditions and names no alternative, so the boundary with fmcsa_carrier_lookup or carrier_vetting_score is left implicit.

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