総合価値スコア

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds value by disclosing output features (radar, tier, peer comparison, AI narrative) beyond what annotations provide, making the tool's behavior more transparent.

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 two sentences with bilingual text, which is concise. However, some redundancy exists (English and Japanese say the same thing), and the second sentence could be merged with the first.

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 presence of a full output schema and annotations, the description adequately covers the tool's purpose and key outputs (radar, tier, peer comparison, AI narrative). No critical gaps are apparent for a composite scoring tool.

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 coverage is 100%, so baseline is 3. The description only lists high-level output features and does not add meaning to individual parameters beyond what the schema already provides (e.g., defaults, enum values, descriptions).

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 specifies a unique purpose: fusing 5 specific axes into a single 0-100 score with additional outputs (radar, tier, peer comparison, AI narrative). This clearly distinguishes it from sibling tools like 'assess_family_friendly_score' or 'forecast_land_price_trend' which focus on individual axes.

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 for composite scoring but provides no explicit guidance on when to use this tool vs. alternatives. For instance, it does not state that single-axis analysis should use different tools, nor does it mention prerequisites or when not to use it.

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