score_japan_readiness

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool analyzes 5 specific categories and returns a breakdown with issues and quick wins. However, it doesn't mention performance characteristics (e.g., processing time), error handling, or authentication requirements that would be helpful for an agent.

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 efficiently structured in two sentences: the first states the core purpose and scope, the second details the 5 analysis categories and return format. Every sentence earns its place with zero wasted words, making it easy for an agent to parse quickly.

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?

For a 4-parameter analysis tool with no annotations and no output schema, the description provides good context about what the tool analyzes and returns. It covers the 5 evaluation categories and output structure (breakdown with issues and quick wins). However, without an output schema, more detail about the return format would be beneficial for agent understanding.

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 all 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain markup format requirements or context implications). Baseline 3 is appropriate when 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's purpose: 'Score any page or component for Japan-readiness on a 0-100 scale' with specific verb ('Score') and resource ('page or component'). It distinguishes from siblings by focusing on comprehensive analysis rather than specific generation or validation tasks like 'generate_jp_form' or 'validate_jp_form'.

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 through the 5 analysis categories (forms, copy, trust, typography, cultural), suggesting it's for evaluating Japanese localization readiness. However, it doesn't explicitly state when to use this tool versus alternatives like 'transform_for_japan' or 'validate_jp_form', nor does it provide exclusion criteria or prerequisites.

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