Where to list each MCP
get_catalog_placementWhich directories take the docs MCP vs the spend MCP. OpenAI is docs-only.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_catalog_placementWhich directories take the docs MCP vs the spend MCP. OpenAI is docs-only.
| 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?
The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered without description support. The description adds domain context ('OpenAI is docs-only') but no additional behavioral details such as output behavior, caching, or side effects. This is consistent with the annotations.
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 brief and front-loaded: it immediately states the placement question and adds one specific rule. The title and first clause overlap somewhat, but no excess material is present.
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 read-only lookup with no output schema, the description gives enough context to choose the tool: it names the entities involved (docs MCP vs spend MCP) and the decision being made (directory placement). It does not describe the exact return format, but the described purpose makes the likely output understandable.
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?
There are zero parameters, so the description does not need to explain parameter behavior. The schema already fully covers the input surface, and the description's subject matter is enough for the agent to know that no arguments are required.
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 states a specific question: which directories take the docs MCP vs the spend MCP. This is a clear query over a defined resource ('catalog placement'). It does not explicitly contrast itself with sibling tools, but the subject matter is distinct enough that an agent can identify its purpose.
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?
Usage is implied: use this tool when you need to know where to place or list the docs and spend MCPs. There is no explicit when-to-use or when-not-to-use guidance, and no alternative tools are mentioned, so the guidance is acceptable but not strong.
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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