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

Adds real value beyond the annotations by pre-empting a likely misread: 'Read-only (a POST search)' tells the agent that a POST endpoint does not imply a mutation, which the readOnlyHint alone might not convey confidently. It also discloses the return payload (products, payments, dispatch data, customer), which annotations do not cover. It stops short of pagination behavior or result caps, which are only partially in the schema.

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?

Three short sentences, front-loaded with the searchable dimensions, then the return shape, then the read-only caveat and endpoint. Nothing is repeated from the schema and no sentence is filler.

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 summarizes the return payload, and with 10 fully documented parameters the input side is covered by the schema. The only gap is that total-count/pagination semantics for the response are unstated, a minor omission for a 0-required-param search tool.

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% — every one of the 10 parameters carries its own description, enum, and pattern — so the schema does the heavy lifting. The description's list of filter dimensions mirrors those parameters without adding format, combination, or defaulting semantics (e.g. how date_from/date_to interact with date_type). 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 and resource ('Search orders') and enumerates the filter dimensions (status, date range, customer, ids, serial numbers), so the agent knows exactly what the tool does. However, it never distinguishes itself from the sibling `idosell_get_orders`, which sounds like a competing way to retrieve orders — that ambiguity keeps it below a 5.

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 enumerated filters imply this is the tool for filtered/queried retrieval, which gives an implicit usage cue. But there is no explicit when-to-use, no when-not, and no routing to `idosell_get_orders` or `idosell_get_order_packages`, so the agent must infer the choice from sibling names alone.

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