academy_review_grade

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 describes the effect of grades ('again resets to 1d, good/easy grows the interval via SM-2'), which adds useful context beyond basic functionality. However, it lacks details on permissions, error handling, or response format, which are important for a mutation tool with no output schema.

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 extremely concise and front-loaded, consisting of two sentences that directly explain the tool's purpose and parameter effects. Every word earns its place, with no redundant or unnecessary information, making it highly efficient 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 the tool has 2 parameters, no annotations, and no output schema, the description provides basic purpose and parameter effects, but it's incomplete for a mutation tool. It lacks details on return values, error cases, or broader context like how it integrates with other tools (e.g., 'academy_review'), leaving gaps that could hinder correct invocation.

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 50% (only 'id' has a description), and the description adds meaning for the 'grade' parameter by explaining the effects of each enum value ('again resets to 1d, good/easy grows the interval via SM-2'). This compensates partially for the low schema coverage, but it doesn't clarify the 'id' parameter beyond what's implied, so it meets the baseline for moderate compensation.

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: 'Grade a review item after recall attempt.' It specifies the action (grade) and resource (review item), and distinguishes it from siblings like 'academy_review' or 'academy_quiz_submit' by focusing on grading after recall. However, it doesn't explicitly differentiate from all siblings (e.g., 'academy_progress_complete'), so it's not a perfect 5.

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 context ('after recall attempt'), suggesting this tool is used post-recall, but it doesn't provide explicit guidance on when to use it versus alternatives like 'academy_quiz_submit' or 'academy_review'. No exclusions or clear alternatives are mentioned, leaving some ambiguity for the agent.

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