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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so safety is covered. The description adds useful caveats beyond annotations: the answer is AI-generated, may contain errors, is processed by Kabuken rather than raw FSA data, and is not investment advice.

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 purpose is front-loaded, but the description includes licensing URLs and legal boilerplate that are not essential for tool selection or invocation. It is reasonably structured but could be tighter.

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 three-parameter QA tool with no output schema, the description adequately explains the source, the AI-generated nature of the answer, and important limitations. It could say more about answer format or length, but the core context is present.

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 all three parameters are already documented in the input schema. The description does not add parameter-specific meaning beyond what the schema provides, which is acceptable at baseline 3.

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 states a specific verb and resource: ask a question about a Japanese financial document from EDINET and receive an AI-generated answer. It is clear what the tool does, but it does not explicitly distinguish itself from siblings like get_document_summary or get_financial_facts.

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 by saying to ask a specific question about a document, but it never states when to choose this tool over alternatives such as get_document_summary or get_financial_facts. No exclusions or prerequisites are provided.

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