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

No annotations are provided, so the description carries the full burden. It discloses the effect ('routes through the learner's record so the change sticks'), authentication needs ('Requires admin_key'), and a prerequisite ('must have started a session first'). However, it does not mention whether the operation is irreversible, any rate limits, or what happens on failure.

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 concise: three sentences that are front-loaded with the purpose and example, followed by prerequisites and authentication. Every sentence adds necessary information without redundancy. This is excellent structure for an AI agent.

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 no output schema, the description should hint at return values or success/failure indicators. It does not. It covers inputs and behavior adequately, but the lack of return-type information is a gap. The prerequisite and authentication details partially compensate.

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% (all three parameters have descriptions). The description adds value by clarifying that 'learner' uses the same key as in start_session and that 'admin_key' is the 'Worker secret ADMIN_KEY'. It reinforces the enum values for 'level' with examples. This extra context goes beyond the schema alone.

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 purpose: 'reclassify an existing learner's track (scratch | intermediate | power).' The verb 'reclassify' combined with the target resource (learner's track) is specific, and the examples (e.g., 'scratch enrollee who's really a power operator') add clarity. It is well-distinguished from sibling tools like start_session or complete_lesson.

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 tells when to use the tool: 'Use when a learner was placed wrong.' It also provides a prerequisite: 'The learner must have started a session first,' and an authentication requirement: 'Requires admin_key.' However, it does not explicitly mention when NOT to use it or name alternatives among siblings.

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