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

With no annotations, the description carries the full burden and does disclose meaningful traits: it is read-only, sold units are excluded, and missing specs remain unknown rather than being fabricated. It does not cover how soft filters behave or what the OEM toggle changes, but the core behavioral profile is unusually well disclosed.

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 tight sentences with no filler, front-loading the primary behavior (recommend live inventory) before qualifications. Every clause earns its place.

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?

There is no output schema or annotation coverage, and the tool has a large nested soft-filter object plus a limit and free-text notes field. Given that complexity, the description omits too much about inputs and result shape to be considered complete.

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 0% across 5 parameters, including a nested soft-object with 15 undocumented filter fields. The description never names or explains job, soft, limit, job_notes, or include_oem_suggestions, only loosely hinting at 'job' and OEM suggestions. It fails to compensate for the coverage gap.

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 (recommend) and resource (machines) and adds scope detail: fitting live inventory first, then OEM models not in stock. This functionality is clearly distinct from retrieval siblings (get_listing, search_listings, get_specs), though it never names them.

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?

Usage is only implied ('for a job'). There is no guidance on when to choose this over search_listings or get_specs, no prerequisites, and no exclusions. An agent must infer the decision boundary.

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