architect

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

Annotations already declare readOnlyHint=true, so the tool is read-only. The description adds that it is a 'software architect' providing analysis and design, which is consistent. No additional behavioral details beyond what annotations provide, so score is baseline.

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?

Two sentences, each earning its place. First sentence defines the tool's role, second specifies exact use cases. Front-loaded with the core purpose, no wasted words.

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 (6 parameters, no output schema), the description is too sparse. It explains the 'when' but not the 'how'—no parameter semantics, no behavior beyond read-only, no return value hints. Incomplete for an AI agent to use correctly.

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 0%, and the description provides no explanation of any parameter. The required parameter 'prompt' is not described, nor are optional parameters like 'expert', 'files', etc. This leaves the agent without guidance on how to fill parameters.

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?

Description clearly states the tool is for system design, tradeoff analysis, and complex decisions. It identifies specific use cases (architecture, API/schema design, multi-service interactions) and distinguishes from siblings by mentioning a fresh perspective after failed fixes.

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?

Provides explicit guidance on when to use: for architecture tasks, and after two failed fixes. This implies when not to use (simple tasks) but does not name alternatives explicitly. Nonetheless, context is clear.

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