Materials that can be vacuumed. E.g.: combustible dust, welding fumes, oils, liquids.
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": "getApplications"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| search | No | Optional text filter | |
| includeEmpty | No | If true, include terms with no published products |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It provides domain context (vacuumable materials) and examples, but no operational details such as return behavior, filtering semantics, or whether results are sorted/curated. It does not explain how search or includeEmpty affect behavior beyond their schema descriptions.
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 very short and has no filler, which is positive, but it is under-specified. It reads more like a vague list of examples than a clear tool description. It earns points for efficiency but loses for clarity.
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 tool with no output schema and no annotations, the description should provide a fuller picture. It lacks an explicit statement of what is returned, what an 'application' is, or any usage context. The examples help, but the tool is not self-contained enough for an AI agent to invoke confidently.
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 100%, so the schema already provides clear meanings for both parameters. The description adds no parameter-specific information. Baseline 3 is appropriate since the description and schema together cover the parameters adequately.
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 implies the tool returns materials that can be vacuumed, with examples, but it never explicitly states an action like 'get' or 'list.' The name 'getApplications' helps, but the description alone is vague about what an 'application' is versus the material examples. It partially distinguishes from siblings by focusing on vacuumable materials, but lacks a clear verb+resource statement.
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 instead of siblings like getProductCategories, getUsages, or getSectors. The description gives no context about typical use cases or when to prefer a sibling tool. This is a clear gap.
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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