save_reading_annotation

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

Even though annotations already indicate readOnlyHint=false and destructiveHint=false, the description adds valuable behavioral context by warning that it 'Changes stored DeepTutor learning data' and emphasizing the need for explicit user authorization. This goes beyond the annotations and helps the agent understand the write risk.

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 short and front-loaded with the most critical warning, followed by a usage instruction and a clear action statement. There is minor redundancy with the confirm parameter's schema description, but overall it is efficient.

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?

For a 9-parameter mutation tool with complete schema coverage and an output schema present, the description covers safety and usage requirements well. It does not need to explain return values, and the warning about explicit user consent fills an important contextual gap.

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 the baseline is 3. The description does not explain individual parameters beyond listing annotation kinds, which duplicates the schema. It adds no new semantic detail for material_id, locator, note, color, or confirm.

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 verb 'Create or update' and the resource 'a highlight, underline, note or citation on a material', making the tool's purpose specific and unambiguous. It also names the exact annotation kinds, which distinguishes it from related tools like delete_reading_annotation and list_reading_annotations.

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 states when to call the tool ('call only when the learner explicitly requests this action') and warns to 'Check the target ID and values'. This provides clear usage context and a key prerequisite, though it does not explicitly name sibling alternatives for when not to use it.

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