get_brand_kitReads the Brand Kit of the workspace: name, tone, topics to cover and avoid, guidelines, colors, fonts and preferred hashtags.
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_brand_kit"
}
}| 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?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, so the safety profile is covered. The description earns credit by disclosing the shape of the returned data (tone, topics to cover AND avoid, guidelines, colors, fonts, hashtags), which matters because there is no output schema. It does not state behavior for a workspace with no configured kit, keeping it short of a 5.
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?
One sentence, front-loaded with the verb and resource, with the field list appended as a compact colon-delimited inventory. Every clause carries information; nothing is repeated from the title or annotations.
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 parameters and a full annotation set, the remaining descriptive burden is the return payload, and the description covers it in reasonable detail. Absence of any fallback/empty-state behavior or workspace-scoping note is the only real gap for this complexity level.
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 schema to describe and no ambiguity to compensate for. The description correctly adds no parameter prose, though it also does not note that the kit is implicitly scoped to the current workspace rather than a passed-in ID.
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?
Specific verb and resource ('Reads the Brand Kit of the workspace') followed by an enumeration of exactly what that resource contains (name, tone, topics, guidelines, colors, fonts, hashtags). No sibling tool reads brand data, so there is no ambiguity for the agent to resolve.
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 only implied: an agent can infer this is the source of brand context for generate_post, but the description never says when to call it, whether it is a prerequisite for content generation, or what to do if it is empty. No alternatives or exclusions are named.
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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