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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds meaningful behavioral context: 'Deterministic and free: it calls no model, costs nothing, and never runs out of quota.' This discloses resource usage and invocation behavior beyond the annotations. It also mentions it returns multi-step recipes, which is an important behavioral trait.

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?

The description is three sentences, each serving a distinct purpose: the primary function and benefit, the advanced recipe capability, and the cost/determinism plus usage recommendation. Every sentence contributes new, relevant information without redundancy, making it well-structured and appropriately sized.

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 the tool's meta-purpose, the description covers all necessary angles: what it does, when to call it, behavioral guarantees (deterministic/free), and what it returns (tool recommendations and multi-step recipes). The presence of an output schema covers the return format, so nothing critical is missing.

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?

The schema description covers 100% of the single 'task' parameter, but the description enhances it by adding 'plain language (any language)' and giving concrete examples such as 'reconcile a bank statement against my books' or '把一堆发票整理成能入账的表格.' This adds semantic clarity beyond the schema's generic 'What you are trying to do.'

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?

The description clearly states the tool's function: 'Describe a task in plain language... and get back exactly which tools on this server do it, with ready-to-run example calls.' It uses a specific verb ('get back') and names the resource ('tools on this server'), and it is immediately distinguishable from sibling tools like translate_text or check_grammar, which perform specific tasks rather than recommending tools.

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 description explicitly advises when to use this tool: 'Call this FIRST when you are not sure what this server offers.' It also frames it as an alternative to 'reading the whole catalogue and guessing,' giving clear context for using it over the sibling tools. This is direct, unambiguous guidance.

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