review_batch

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 return value (adaptive scheduler state with streak and next review) and describes the input structure as {id, success}. However, it does not explicitly state side effects (e.g., mutations to scheduler state), idempotency, failure modes, or any prerequisites, leaving important behavioral aspects undisclosed.

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 a single sentence, front-loaded with the main action and immediately providing input and output details. Every word contributes meaning, with no redundant phrases, making it highly concise and well-structured.

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 a simple parameter set and no output schema, the description covers the essential aspects: what the tool does, the input format, and the return value. However, it omits details about side effects, error handling, or behavior for invalid inputs, which would be beneficial for a batch operation. The description is adequate but not exhaustive.

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 only lists 'answers' with nested properties, and schema coverage is 0%. The description adds semantic meaning by clarifying that each answer is {id, success} and these represent spaced-repetition outcomes. It also implies the expected structure ('for every card') beyond the raw schema, which is valuable given the low schema documentation.

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 applies a batch of spaced-repetition outcomes, using a specific verb ('Apply') and resource ('batch of spaced-repetition outcomes'). It also specifies the return value (adaptive scheduler state for every card), which differentiates it from single-card tools like 'review' or 'record_outcome' among its siblings.

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 implies usage for batch processing of repetition outcomes but does not provide explicit when-to-use guidance or exclusions. It does not mention alternatives or context where this tool should be preferred over singular review tools. The 'batch' qualifier offers some implicit context, but no direct comparison.

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