mark_lecture_completed

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 mentions local storage persistence but does not say whether the operation is idempotent, overwrites existing completion state, or has side effects on schedules, backlogs, or statistics.

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 concise sentence with the action front-loaded and no wasted words. However, its brevity sacrifices important usage and behavior context.

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 mutation tool with no annotations and no output schema, the description is incomplete. It does not explain return values, effects on related data, error behavior, or how this relates to the sibling mark_lecture_incomplete.

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 0%, and the description adds no parameter-specific meaning beyond the lecture_id property name. The intent is inferable, but format, source, or required value details are absent.

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 states a specific verb ('mark') and resource ('lecture') with a clear outcome ('as completed in local storage'). It is distinguishable from the sibling mark_lecture_incomplete by the word 'completed', though it does not explicitly name that contrasting tool.

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?

There is no guidance on when to use this tool instead of mark_lecture_incomplete or update_watched_minutes, nor any mention of prerequisites or state implications. The agent must infer appropriate usage from the tool name.

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