update_product

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

With no annotations, the description carries the full behavioral burden. It discloses that only provided arguments are changed (partial update), and crucially explains the unit-change failure mode: 'Refused while any stock is on hand... 2 Packs silently becoming 2 Grams.' It also notes that min_stock is read by below_min_stock and add_missing_to_shopping_list, providing important side-effect context.

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 well-structured: a clear summary sentence, an explicit scope statement, and a compact argument list. Every sentence adds value—the unit constraint and min_stock note are not fluff. It is front-loaded with purpose and alternatives, and the argument documentation is organized and readable.

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 7-parameter tool with no output schema, this description covers all necessary aspects: purpose, alternatives, parameter semantics, behavioral nuances, and caveats. An agent could confidently invoke this tool correctly without further information.

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 coverage is 0%, so the description must fully document each parameter. It does so thoroughly: product (name/description fragment/barcode), name, description (brand, size, variant), category (exact name, see get_conventions), location_id (id or exact name), unit (with constraint), and min_stock (meaning and clearing behavior). Each parameter gains meaning beyond the raw schema.

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 ('Edit an existing product's catalog record') and enumerates concrete use cases (typo, recategorising, moving shelf, min stock). It explicitly differentiates itself from stock-related tools by naming add_stock, consume_product, and correct_stock, so an agent can immediately identify when this tool is the right choice.

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 explicit when-to-use and when-not-to-use guidance: 'For fixing a typo, recategorising something, moving its default shelf, or setting a minimum stock level' and 'This does not touch stock amounts — use add_stock, consume_product or correct_stock for those.' It also points to get_conventions for the category parameter, giving the agent a clear routing strategy.

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