recommend_tools

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It openly describes ranking by fit, enforcement of hard constraints, and the returned shortlist components: fit scores, caveats, verified starting prices, and next steps. It could disclose more about data sources or no-match behavior, but for a non-mutating recommendation tool this is substantial transparency.

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 tightly written sentences. The purpose is front-loaded, the differentiation from search_tools is immediate, and the output characteristics are summarized without wasted words.

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?

Given that there is no output schema or annotations, the description does a good job covering what the tool returns and when to use it. It also conveys the ranking and constraint behavior. It does not cover edge cases like zero matching results or how to choose among the remaining siblings, but these are minor gaps.

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%, so the schema already documents each parameter. The description adds a useful high-level framing by identifying budget, pricing, and category as 'hard constraints' and mentioning fit-based ranking, but it does not add significant per-parameter semantic detail beyond what the schema provides.

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'), a clear resource ('software tools'), and a clear purpose ('for a described need'). It also explicitly contrasts itself with search_tools ('Unlike search_tools (raw retrieval)'), so an agent can distinguish it from a key sibling without opening the schema.

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 an explicit usage trigger: 'Use this when a user asks "what should I use for X"' and explains how it differs from search_tools. However, it does not address when to prefer other siblings like compare_tools, get_alternatives, or get_pricing, so there is no full exclusion guidance.

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