The six criteria every listing is marked against, with definitions and the support values (native = Built in, pattern = Documented pattern, none = Not claimed).
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_criteria"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full disclosure burden. It does add real value by defining the three support-value labels (native = Built in, pattern = Documented pattern, none = Not claimed), which an agent cannot get from any structured field. However, it never states that the call is a side-effect-free read, nor the returned shape or size beyond 'six criteria', leaving behavioral gaps.
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?
A single dense sentence with the core content front-loaded and the label mappings tucked into a parenthetical that earns its space. Minor deduction for the verbless fragment construction, which reads slightly like a schema note rather than a tool description.
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 zero-parameter reference tool with no annotations and no output schema, the description covers the essentials: what is returned, that definitions accompany it, and the meaning of each value label. It stops short of describing the response format or how the criteria relate to fields on get_listing results, which would fully close the loop.
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 tool takes zero parameters, so there is nothing for the description to disambiguate beyond what the empty schema already says. The baseline of 4 for parameterless tools applies.
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 names the specific resource (the six criteria every listing is marked against) and enumerates its parts: definitions plus the native/pattern/none support values. An agent can tell exactly what content comes back. It lacks a verb ('Returns...') and any explicit differentiation from siblings such as get_listing or compare_tools, which keeps it below a 5.
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?
There is no when-to-use or when-not-to-use guidance. The reader must infer that this is a static reference lookup used to interpret criterion values seen on listings. No alternative or prerequisite is mentioned, so selection guidance is absent.
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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