brandsystem-mcp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does well by declaring it as 'Read-only' and specifying that it returns a compiled document for AI agents. It mentions the content includes identity, visual rules, voice constraints, and strategy summary, but lacks details on potential errors, response format, or performance considerations.

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 front-loaded with the core purpose, followed by key details and usage guidelines in three concise sentences. Every sentence adds value without redundancy, making it efficient and well-structured.

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?

Given the tool's complexity (reading a compiled brand system) and lack of annotations or output schema, the description is mostly complete. It explains what the tool does, when to use it, and what it returns, but could benefit from mentioning the output format or any limitations, though this is mitigated by the zero-parameter 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing on the tool's purpose and usage, which aligns with the baseline expectation for zero-parameter tools.

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 clearly states the specific action ('Read the compiled brand runtime contract'), identifies the resource ('brand-runtime.json'), and distinguishes it from siblings by specifying it returns 'the single-document representation of the brand system that AI agents use to generate on-brand content.' It explicitly differentiates from brand_compile for refreshing.

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?

It provides explicit guidance on when to use ('Use when loading brand context for content generation') and when not to use ('Read-only — run brand_compile to refresh'), naming the alternative tool (brand_compile) for updates, which is crucial among many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.