add_task

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 states the tool creates a task but doesn't explain what happens after creation (e.g., whether it returns a task ID, triggers notifications, or affects board state). It mentions note creation via the 'create_note' parameter but doesn't clarify default behavior or side effects, leaving significant gaps 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 a single, front-loaded sentence that efficiently conveys the core purpose without unnecessary words. Every part of it ('Add a new task', 'to a specific column', 'in a Kanban board') contributes essential information, 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?

For a mutation tool with 7 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral outcomes (e.g., what the tool returns, error conditions), doesn't address sibling tool relationships, and relies too heavily on the schema for parameter context, leaving the agent under-informed about usage and effects.

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 description doesn't explicitly discuss parameters, but the input schema has 71% description coverage, documenting most parameters well (e.g., 'description', 'labels', 'acceptance_criteria', 'create_note'). However, it doesn't compensate for the 29% gap (undocumented 'board_name', 'column_name', 'task_text'), though the required parameters are implied by the description's focus. Given the schema's solid coverage, this earns above baseline.

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 action ('Add a new task') and target resource ('to a specific column in a Kanban board'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'move_task' or 'create_board' beyond the basic verb+resource distinction, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives like 'move_task' or 'create_board'. It doesn't mention prerequisites (e.g., needing an existing board/column), exclusions, or typical scenarios for task creation, leaving the agent with minimal contextual direction.

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