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bbruhn91

Aedifion MCP Server

by bbruhn91

get_favorite_datapoints

Retrieve all personal favorite datapoints for a specific project in the Aedifion building performance platform to access preferred monitoring data.

Instructions

Get all personal favorite datapoints.

Args: project_id: The project's numeric ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It implies a read operation ('Get') but doesn't disclose behavioral traits such as authentication needs, rate limits, pagination, or what 'personal favorite' entails (e.g., user-specific vs. project-wide). This leaves significant gaps for an agent to understand how to use it effectively.

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 front-loaded with the main purpose in the first sentence, followed by a concise Args section. It avoids unnecessary words, though the structure could be slightly improved by integrating the parameter explanation more seamlessly.

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 there is an output schema (which reduces the need to describe return values) and no annotations, the description is minimally adequate. However, for a tool with 1 parameter and 0% schema coverage, it should provide more context about the 'favorite' concept and usage scenarios to be fully helpful.

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%, but the description adds the parameter 'project_id' with a brief explanation ('The project's numeric ID'). This provides basic semantics beyond the schema's title 'Project Id', but it doesn't clarify why this parameter is required or how it affects the output, leaving room for improvement.

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 verb 'Get' and the resource 'all personal favorite datapoints', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'get_datapoint' or 'get_project_datapoints' by explaining what makes 'favorite' datapoints distinct.

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?

No guidance is provided on when to use this tool versus alternatives like 'get_datapoint' or 'get_project_datapoints'. The description only states what it does without context about prerequisites, timing, or comparisons to other tools in the list.

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

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