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

Annotations already establish readOnly/non-destructive/idempotent behavior, and the description goes beyond them with genuinely useful context: the 2 MB cap, output truncation at 200 rows, null counts when a column is absent, and the explicit 'nothing is stored, input used and dropped' retention guarantee. The only gap is that the privacy/no-storage claim is asserted without any detail on processing boundaries, so it stops short of a 5.

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 action and the checked fields, followed by example queries, constraints and return shape; every sentence carries information. It is dense but borderline long for a single-parameter validator, which keeps it off a 5.

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?

An output schema exists, so the description need not detail return values, yet it briefly summarizes them and covers input format, size limit, and data-retention behavior. An agent has everything needed to invoke it correctly; only minor edge cases (e.g. malformed vs missing distinction) go unstated.

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?

One parameter with 100% schema description coverage, so the schema already documents the expected format and size limit. The description adds only the incidental fact that the text may come from either an inventory or product CSV, which is marginally useful but largely repeats the schema. Baseline 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?

Names a specific verb (check) and resource (Shopify Inventory CSV or product CSV) and enumerates exactly what it looks for: missing/malformed HS codes, countries of origin, item identifiers and invalid barcodes. This is clearly distinguishable from siblings like bulk_hs_candidates or landed_cost_estimate, which suggest or price rather than validate.

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 triggering questions ("which products have no HS code?", "is my export ready for customs?") that let an agent map a user request onto this tool. It does not name alternatives or state when NOT to use it, so it falls short of the explicit routing that a 5 requires.

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