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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=true), so the description's job is to add semantics — and it does, by explaining the subtraction formula behind the number and warning that service products return NULL. That NULL caveat is exactly the kind of result-shape surprise an agent needs before interpreting data; only auth/rate-limit context is absent.

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?

Two sentences, zero filler: the metric definition leads, the edge cases (NULL for service products, empty product_no) follow. Nothing is repeated from the title or schema.

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?

With no output schema, the description usefully compensates by explaining what the returned stock figure means and how service products appear. For a small, all-optional-parameter read tool this is nearly sufficient; only ordering/pagination expectations for the result set are unaddressed.

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 100%, so limit, offset, company_no and product_no are all documented in the schema itself. The description only adds the empty-product_no-means-all clarification, which is helpful but marginal against an already complete schema — 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 ('Currently available stock per product') and pins down the metric precisely: on-hand stock of available stock types minus demand due today or earlier. That definition separates it from collmex_list_products, which would otherwise look like the obvious sibling for product queries.

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?

'Leave product_no empty for every product' gives usage guidance for the all-products case, which is the main calling decision. However, it never says when to prefer this over collmex_list_products or how it relates to other stock views, so the choice between siblings is left to inference.

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