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

While annotations already declare readOnlyHint=true and destructiveHint=false, the description adds meaningful context: it reveals the tool's data scope (US containerised imports), the specific outputs (trend, origins ranked by trade and duty, tariff rate comparison), and a caveat that code-level origin rankings are 'not honest' at chapter granularity. It also notes 'No API key required.' This goes beyond the annotations, though it doesn't fully describe failure modes or return formatting.

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. It front-loads the core promise ('One HS chapter, whole, in a single call'), then details the exact data points, gives usage examples, names alternatives, and adds a caveat. It is appropriately sized for the tool's complexity and contains no fluff.

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?

Given the tool's complexity (4 parameters, no output schema), this description is fairly complete: it explains the expected return content, when to use it, and how to avoid misuse. The main gaps are the unaddressed 'detail' and 'months' parameters and the vague term 'studies', but the overall context is sufficient for an agent to decide on invocation.

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?

With schema description coverage at 50%, the description partially compensates: it clarifies that 'commodity' accepts an HS2 chapter number or name and explicitly warns against 6-10 digit codes. However, it does not explain the 'detail', 'months', or 'top_n' parameters beyond implying a ranking limit ('top supplying origins'). The description adds meaning for the key parameter but leaves the optional parameters ambiguous.

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 the tool's function: it returns a comprehensive profile for one HS2 chapter, including import volume/value, trends, top origins by trade and duty paid, tariff rate changes, and related studies. It specifies the resource (HS2 chapter) and the verb (open a commodity-level question), and distinguishes itself from siblings like trade_query, tariff_burden, and tariff_story by explicitly naming when to use those alternatives.

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 explicitly tells the agent when to use this tool ('Use this to OPEN any commodity-level question') and when not to ('for a specific 6-10 digit code call tariff_story instead'). It also contrasts with assembling trade_query + tariff_burden per origin manually, providing clear alternative selection guidance.

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