sources
Data sources
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Data sources
| 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 burden of behavioral disclosure, and it discloses nothing. It does not say whether this returns a list of upstream data providers, licensing info, cache status, or anything else.
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?
Two words that front-load nothing and earn no place because they add no information beyond the tool name. This is under-specification rather than genuine conciseness.
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?
With no annotations and no output schema, the description is the only source of context, and it provides none. An agent has no way to know what a "source" is or what the response contains, making the definition effectively unusable for selection.
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 the baseline is 4 by rule. There is no parameter surface for the description to clarify.
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?
"Data sources" merely restates the tool name and does not state a verb or what the tool actually returns. An agent cannot distinguish it from siblings like coverage, glossary, or health, which are equally generic metadata endpoints.
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 indication of when to call this tool versus any of the ~90 siblings, nor any prerequisite or context. No guidance is provided at all.
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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