manual_check_in

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action 'manually mark' without explaining side effects, such as whether re-marking an existing check-in updates, overwrites, or creates duplicates. It does not mention idempotency, undoability, or required permissions. The enumerated 'kind' values add some clarity but do not compensate for missing behavioral context, which is critical for a mutation tool.

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 and well-structured: a one-sentence summary followed by an Args block with bullet points for each parameter. It front-loads the purpose and provides parameter details in a scannable format without any redundancy or filler.

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?

The description covers purpose and parameters well, and since an output schema exists, return values need not be detailed. However, the behavioral transparency gap (duplicate handling, idempotency, permissions) leaves the description incomplete for a mutation tool with no annotations. The tool has 3 parameters and no annotation support, so more behavioral context would be needed for full completeness.

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 has zero parameter descriptions, so the description must compensate. It does this thoroughly: event_id is explained as 'The session ID (from list_attendance_sessions results)', user_ids as 'List of user IDs to check in', and kind with a list of valid statuses ('present', 'late', 'excused', 'absent'). This adds meaning beyond the schema's bare types and defaults.

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: 'Manually mark students' attendance for a session.' It uses a specific verb ('manually mark') and identifies the resource (students' attendance for a session). This distinguishes it from related tools like list_check_ins (viewing) and undo_check_in (reverting), and it references the prerequisite tools (list_users, list_attendance_sessions) to clarify its role.

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 provides some usage context by directing users to list_users for user IDs and list_attendance_sessions for event_id, which are necessary prerequisites. However, it does not explicitly compare this tool to alternatives such as list_check_ins or undo_check_in, nor does it mention when not to use it (e.g., for automated check-ins). Thus, the guidance is implied rather than explicit.

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