Skip to main content
Glama
bbruhn91

Aedifion MCP Server

by bbruhn91

assign_task

Assign tasks to users in the Aedifion building performance platform to manage project workflows and responsibilities.

Instructions

Assign a task to a user.

Args: task_id: The task ID. user_id: The user ID to assign.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYes
user_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool performs an assignment operation (implying mutation) but doesn't describe what happens during assignment: whether it overwrites existing assignments, requires specific permissions, triggers notifications, or has side effects. For a mutation tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately brief with two sentences: a purpose statement and parameter listing. The structure is front-loaded with the core action. However, the parameter section could be integrated more smoothly rather than as a separate 'Args' block.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists, the description doesn't need to explain return values. However, for a mutation tool with no annotations, 0% schema description coverage, and two parameters, the description should provide more context about behavioral outcomes, error conditions, and relationships to sibling tools like 'unassign_task'.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that names both parameters (task_id, user_id) and specifies they are IDs, adding basic semantics. However, it doesn't explain format expectations, valid ranges, or where to obtain these IDs, leaving significant gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Assign a task') and the target ('to a user'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'unassign_task' or explain how assignment differs from other task-related operations like 'update_task' or 'create_task'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. It doesn't mention prerequisites (e.g., task must exist, user must have appropriate permissions), when assignment might fail, or when to use 'unassign_task' instead. The agent must infer usage from context alone.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/bbruhn91/mcp-server-aedifion'

If you have feedback or need assistance with the MCP directory API, please join our Discord server