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 key behavioral traits: the tool operates in two modes (interview returns structured questions, record saves answers), it's part of a multi-session process (Session 2 after Session 1), and it affects other tools (anti-patterns become enforceable rules in brand_preflight). However, it doesn't mention potential side effects like file overwrites, error handling, or authentication needs, leaving some gaps for a mutation tool.

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 operational details and usage context. Every sentence earns its place: the first defines the tool's scope, the second explains the session and modes, the third provides prerequisites and consequences. It's appropriately sized with no redundant information, making it efficient and easy to parse.

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 (3 parameters, no annotations, no output schema), the description is mostly complete. It covers purpose, usage, modes, and workflow integration. However, it lacks details on return values (e.g., what 'section completion status' entails) and doesn't address potential errors or constraints, which could be important for a tool that writes to a file ('record' mode).

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 baseline is 3. The description adds value by explaining the semantics of the 'mode' parameter ('interview' returns questions for missing sections; 'record' saves answers to visual-identity.yaml) and the context of 'section' (referring to the 6 listed aspects like composition and anti-patterns). It doesn't detail 'answers' parameter format beyond 'JSON string with structured answers,' but overall compensates well beyond the schema.

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's purpose: to define visual identity rules beyond colors and fonts, specifying aspects like composition energy, pattern language, illustration style, photography direction, signature moves, and anti-patterns. It distinguishes itself from siblings by focusing on Session 2 of a brand identity process, following Session 1, and explicitly mentions that anti-patterns become enforceable rules in brand_preflight, which is a specific sibling tool.

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 provides explicit guidance on when to use this tool: 'Use after Session 1 (core identity extracted).' It also details two modes ('interview' and 'record') with their specific purposes, and mentions that anti-patterns feed into brand_preflight, indicating an alternative or complementary tool. This gives clear context for usage relative to other tools in the workflow.

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