get_project_tasks

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

No annotations are provided, so the description bears full burden. It discloses that the tool returns tasks 'with kanban columns if available,' implying conditional output. It also explains the include_completed parameter behavior. However, it does not mention auth details beyond 'Auth: V1' (which is a tag) or error handling. Still, it adds meaningful context beyond a bare read operation.

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 front-loaded with a clear one-line summary, followed by metadata tags and a well-structured Args section. Every sentence adds value; there is no fluff. The format is efficient and easy to scan.

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 tool has 2 parameters (one required), no enums, and an existing output schema (though not shown). The description covers the essential: what the tool does, how to use parameters, and a notable output detail (kanban columns). It also includes usage guidance and related tools, making it self-contained for an AI agent.

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?

Despite context signal claiming 0% schema coverage, the description provides detailed parameter explanations: 'project_id: The project ID (use list_projects to find it).' and 'include_completed: If True, include completed tasks (default: False).' This adds significant meaning beyond the input schema, which only has type and title, no descriptions.

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: 'Return all tasks from a specific project, with kanban columns if available.' It specifies the resource (tasks of a specific project) and adds detail about kanban columns, effectively distinguishing it from siblings like get_all_tasks (all projects) or get_task_detail (single task).

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 explicit guidance: 'use list_projects to find it' for project_id and lists related tools (list_projects, get_task_detail, get_inbox, list_columns). While it does not explicitly state when not to use this tool versus alternatives like query_tasks, the related tools list implies use cases, and the project-specific nature is clear.

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