Aedifion MCP Server

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

No annotations are provided, so the description carries full burden. It mentions pagination and filtering, which hints at behavior, but doesn't disclose critical traits like rate limits, authentication needs, error handling, or whether it's read-only (implied by 'Get' but not explicit). For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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 the core purpose, followed by a structured Args section. It's efficient with minimal waste, though the Args formatting is slightly verbose for a simple list. Every sentence adds value, and the structure aids readability.

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?

Given 4 parameters with 0% schema coverage and no annotations, the description provides basic parameter info but lacks depth on behavior, usage context, or output details. The presence of an output schema mitigates the need to explain return values, but overall completeness is moderate—adequate for a simple retrieval tool but with clear gaps in guidance and transparency.

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?

Schema description coverage is 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'Filter string for datapoint names'), adding some semantics beyond the bare schema. However, it doesn't detail format constraints (e.g., filter syntax), value ranges, or default behaviors for nullable parameters, leaving room for ambiguity.

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 verb ('Get') and resource ('all datapoints in a project'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_datapoint' (singular) or 'get_favorite_datapoints', which might retrieve different subsets or types of datapoints.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools related to datapoints (e.g., get_datapoint, get_favorite_datapoints, get_datapoint_timeseries), the description lacks context about prerequisites, typical use cases, or comparisons to other retrieval methods.

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