Get brand sources
get-brand-sourcesGet background information sources for a specific brand. These sources are used to inform AI post generation.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| brandId | Yes | The brand (topic) ID to get sources for |
get-brand-sourcesGet background information sources for a specific brand. These sources are used to inform AI post generation.
| Name | Required | Description | Default |
|---|---|---|---|
| brandId | Yes | The brand (topic) ID to get sources for |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is clear. The description adds that the returned sources are background information used for AI post generation, but it does not disclose return format, pagination, or authorization requirements beyond what the annotations provide.
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 two concise sentences with no wasted words. It front-loads the core action (getting sources for a brand) before adding the purpose (informing AI post generation).
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 simple, read-only, single-parameter tool, the description plus annotations are nearly sufficient. The main gap is that no output schema exists and the description does not describe the shape of the returned sources, though this is a minor omission given the tool's simplicity.
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 single parameter brandId is fully documented in the input schema with a clear description. The tool description reiterates that sources are for a specific brand, but adds no syntax, format, or constraint details beyond the schema. With 100% schema coverage, the baseline score of 3 is appropriate.
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 verb and resource: getting background information sources for a specific brand. It is clear what the tool returns and for whom, but it does not explicitly contrast itself with sibling tools like list-brands or get-x-profiles.
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?
The description gives implied usage by saying these sources are used to inform AI post generation, which suggests when an agent might call it. However, it does not state when to use this tool versus alternatives, nor does it mention prerequisites or exclusions.
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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