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

Annotations already establish read-only/idempotent/non-destructive behavior. The description adds meaningful behavioral context beyond annotations by specifying the response envelope, the operation name ('resolve_doi'), and the success/failure contract (one item vs. zero items plus diagnostic). This clarifies what happens in edge cases, which is not covered by annotations.

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, front-loaded with the primary purpose and then the response behavior. There is no redundancy or unnecessary detail. Every sentence contributes to understanding the tool's function and outcomes.

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 simplicity (one parameter) and the presence of an output schema, the description covers the essential aspects: the operation, success/failure representation, and error handling. It does not mention pagination or other complexities because they are not applicable. The schema description handles the parameter format. Overall, it is complete for an agent to use the tool 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?

The schema description for the 'doi' parameter already explains that it can be with or without the doi.org prefix, providing semantic meaning. Although the context signal says schema description coverage is 0%, the actual schema includes a description, so the baseline of 3 applies. The tool description adds no additional parameter information beyond what the schema provides.

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 explicitly states the verb 'resolve' and the resource 'a J-STAGE DOI to its article record.' It is specific and clearly distinguishes from the siblings (search_articles and list_issues) by focusing on DOI-based lookup. The purpose is immediately understandable.

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 does not explicitly mention when to use this tool versus the alternatives. However, the purpose (DOI to article) strongly implies usage when a DOI is available. There are no explicit exclusions or comparisons to siblings, so guidance is only implied, not stated.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description does not repeat those. It adds useful behavioral context: the return is 'structural JSON (volumes with publisher/journal metadata), not the record envelope'. This clarifies the nature of the output beyond what annotations capture and reinforces the navigation-purpose distinction. It does not contradict any annotation.

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 short sentences, front-loaded with the core purpose, and immediately clarifies what it is not. Every word earns its place; there is no redundant or vague language.

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?

The tool is relatively simple (one params object) and the description covers the essential purpose and output shape. An output schema exists, so the detailed return structure is likely defined elsewhere. The description could elaborate on pagination (count/start) or use cases, but for a navigation aid the current level is adequate. The only minor gap is not mentioning the filtering options beyond identifiers, but they are in the schema.

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% (description does not discuss the parameters object). The description mentions 'by material/issn/cdjournal', covering three of the seven fields, but omits count, start, pubyearfrom, and pubyearto. Given the low coverage, the description should compensate more, but it does highlight the primary identifiers. The schema itself provides titles and constraints for the remaining fields, so this is a partial compensation.

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: 'Return the volume/issue spine of a journal'. It also differentiates from siblings by asserting it is a 'Navigation aid, not literature retrieval', which precisely matches the listing vs. search/article functions. This leaves no ambiguity about what the tool does.

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 clear context: this is for navigation, not literature retrieval. It implies when to use it (when you need the structural spine) and when not (for literature retrieval, likely using search or get-article siblings). It also names the key identifiers ('by material/issn/cdjournal') but does not explicitly mention alternative tool names or exact conditions for choosing this over siblings. This is close to full guidance, but not explicit exclusions.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the bar is lower, and the description still adds substantial context. It explains full-text broad matching, loose multi-word handling, the meaning of matching_mode/result.breadth/diagnostics, SCRIPT_LATIN_QUERY implications, and differences from CiNii. This goes far beyond the structured annotations.

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 and then provides a dense but relevant paragraph of caveats. Every sentence earns its place, with no filler or repetition of annotation information.

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 search tool's complexity and the existing output schema, the description covers the response envelope, diagnostics, matching behavior, and cross-source caveats. It does not explicitly address when to choose this tool over siblings or provide examples, but the essential invocation and result-interpretation 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 0% at the top level, but the nested schema properties have individual descriptions. The tool description adds meaningful semantics for the central text parameter, explaining full-text matching, noise, and re-issuing in kanji/kana, which is not in the schema. It does not discuss filters or pagination, but those are covered in the nested 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 opens with 'Search articles on J-STAGE' and 'Returns the unified response envelope,' clearly stating the verb, resource, and scope. It is distinguishable from siblings like jstage_list_issues and jstage_get_article_by_doi by the search focus, though it does not explicitly contrast itself with them.

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 gives practical guidance for interpreting noisy results and re-issuing Latin-script queries in kanji/kana, which helps an agent act after receiving results. However, it does not explicitly state when to prefer this tool over the sibling tools or when not to use it, so usage selection is implied rather than explicit.

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