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

Annotations already establish readOnlyHint=false, destructiveHint=false and openWorldHint=true, so the bar is lower. The description adds generation quantity and item structure, but says nothing about latency, cost, failure behavior, or what happens when neither unit_id nor any source is supplied despite auto_research defaulting to true.

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, front-loaded with the core action and output shape before the mode split. Every sentence earns its place, though the final 'Supports both course-based and standalone modes' partially restates the opening clause.

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 13 optional parameters, no required fields, and no output schema, the description should say more about what is returned (quiz ID, question payload) and what happens with zero inputs. It covers the generation contract well but leaves the return side and default-input edge case unaddressed.

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 every one of the 13 parameters is already documented in structured data. The description reinforces the unit_id-versus-sources mutual exclusivity, but adds no format or precedence details beyond that. 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?

States a specific verb and resource ('Generate 10 AI-powered match-pair questions') plus the exact output shape (2 sets of 5 pairs). The two sourcing modes are named, which cleanly separates it from siblings like edit_match_pair or create_mcq.

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?

It clearly frames the two modes — course-based via unit_id or standalone via title + sources — so an agent knows which path to take. It does not explicitly say when to use edit_match_pair instead, nor does it warn about which source parameters can be combined.

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