brandsystem-mcp

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

No annotations are provided, so the description carries the full burden. It discloses behavioral traits such as preferring extraction evidence and having a fallback mechanism, which adds context beyond the input schema. However, it doesn't mention critical aspects like whether this is a read-only or mutation operation (e.g., does it modify files?), potential side effects, or error handling, leaving gaps for a tool that generates files.

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 a single, well-structured sentence that efficiently conveys the core functionality and key behavioral nuance (preference for evidence). It's front-loaded with the main action and avoids redundancy. However, it could be slightly more concise by integrating the fallback detail more seamlessly, but overall it earns its place with zero waste.

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 complexity (generating design documentation from a brand system), lack of annotations, and no output schema, the description is moderately complete. It covers the purpose and basic behavior but misses details like what the generated files contain, how errors are handled, or dependencies on other tools (e.g., brand_extract_* tools). For a file-generation tool with 2 parameters, it's adequate but has clear gaps in behavioral context.

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?

Schema description coverage is 100%, so the schema already documents both parameters (source and overwrite) with descriptions. The description adds marginal value by reinforcing the source preference ('prefers rendered extraction evidence') and implying context for manual edits, but doesn't provide additional syntax, format details, or examples beyond what the schema states. Baseline 3 is appropriate as the schema does the heavy lifting.

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 tool generates a DESIGN.md file and design-synthesis.json from the brand system, specifying it prefers extraction evidence but can fall back to current brand state. It uses specific verbs ('generate', 'prefers', 'fall back') and identifies the resource (design documentation). However, it doesn't explicitly differentiate from sibling tools like brand_audit or brand_report that might also document aspects of the brand.

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 implies usage context by mentioning 'prefers rendered extraction evidence when available' and 'after manual edits or compile steps,' suggesting it's for synthesizing design documentation from brand data. However, it doesn't explicitly state when to use this tool versus alternatives like brand_audit (which might audit without generating files) or brand_export (which might export different formats), nor does it provide exclusions or prerequisites.

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