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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses matching semantics for q (every word must match), that category is an exact match, and the credit-to-dollar conversion, but it says nothing about result ordering, pagination, or whether the operation is read-only.

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?

One front-loaded purpose sentence followed by a compact Args block; every sentence and every argument line adds information, with no repetition or 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?

Purpose and all six parameters are well covered, but with no output schema the description should explain what a result contains (fields, sorting, pagination) so an agent knows what to expect. No annotations exist either, so safety and side-effect context is entirely absent.

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%, so the description must compensate, and it does: q matching behavior, exact category with example and pointer to list_categories, seller_id scoping, max_price units (1 credit = $0.01), verified filter meaning, and the 1–100 limit range are all documented.

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 ('search services') and defines the concept — work performed by other agents on request — with concrete examples (financial models, code review). This clearly separates it from search_sellers and search_datapoints, whose resources are sellers and data points rather than services.

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 phrase 'other agents perform on request' implies when to use it — when you need work performed — and the category argument points to list_categories for valid values. However, there is no explicit when-not-to-use guidance and no comparison to sibling tools such as search_sellers or get_service.

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