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

No annotations are provided, so the description carries the full transparency burden. 'Retrieve' signals a read operation and the description adds useful identifier-mode context, but it does not disclose response shape, whether abstracts are always available, or access/entitlement behavior beyond the schema's 'ENTITLED' enum.

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, front-loaded sentences with no filler. The first sentence states the action and resource; the second expands on identifier support. Every clause earns its place.

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 schema is rich and covers parameter semantics, but the description lacks usage guidance, output-shape expectations, and any comparison with sibling tools. For a 4-parameter tool with no output schema and no annotations, the description is minimally adequate but leaves notable gaps.

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 already provides 100% coverage of the four parameters, including descriptions, enums, and examples. The description only restates the supported identifier types and does not add semantic details beyond what the schema provides, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Retrieve') and identifies a clear resource: 'detailed metadata and abstract for a specific Scopus document.' It also enumerates supported identifier types. It distinguishes from search-like siblings by focusing on identifier-based lookup, but it does not explicitly contrast with article_retrieval, so it stops short of a 5.

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 context is clear: use this tool when you have a document identifier (Scopus ID, EID, DOI, PII, PubMed ID) and need metadata/abstract. It does not explicitly state when not to use it or name alternatives such as scopus_search or article_retrieval, so it meets the 'clear context, no exclusions' level.

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?

With no annotations, the description must carry the behavioral burden. It discloses that access depends on API key entitlements, but omits failure modes, return format, and how the 'view' parameter affects output detail.

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, immediately states the primary action and object, and avoids filler. It is well-structured with no redundant content.

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 description covers the core retrieval purpose and access constraint, but lacks guidance on choosing among the view options, handling field selection, or what the response will contain. Without an output schema, this leaves significant ambiguity for an agent.

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% and every parameter has a description. The tool description adds only a high-level mention of identifier types without enriching beyond the schema's definitions, so the baseline score of 3 is appropriate.

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 specifies the verb 'Retrieve' and the resource 'full-text or metadata of a ScienceDirect article', with supported identifier types (DOI, PII, EID). This definitively distinguishes it from sibling search or serial title tools.

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 use when an article identifier is available, but does not explicitly state when to use this tool over alternatives like abstract_retrieval. The entitlement note gives a prerequisite but no exclusions or alternative references.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what is returned but does not mention that this is a read-only operation, any rate limits, pagination behavior, or error conditions. The description implies a search action but does not explicitly clarify safety or side-effect expectations.

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 remarkably concise: two sentences. The first sentence states the purpose and return value, and the second provides a compact list of key field codes. There is no wasted language, and the most important information is front-loaded.

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?

With 9 parameters, a rich schema, and no output schema, the description is adequate but not complete. It explains the basic return type but does not cover important behavior such as pagination defaults, the meaning of the view parameter (though schema covers it), or any rate limiting. The tool is moderately complex, and the description could better assist an agent in understanding operational expectations.

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 9 parameters with descriptions and examples. The description adds value by listing Scopus field codes (e.g., DOI(), KEY(), PUBYEAR) that are not all present in the schema's query examples, enhancing the user's ability to craft effective queries. This goes beyond simple repetition of schema information.

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 'Search the Scopus database of abstracts and citations' and specifies the return type: 'metadata about scholarly documents including titles, authors, DOIs, citation counts.' This distinguishes it from sibling retrieval tools like abstract_retrieval and article_retrieval, which focus on retrieving specific documents rather than searching.

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 explicit guidance on how to construct queries using Scopus field codes (TITLE(), AUTH(), etc.), which is helpful for usage. However, it does not explicitly state when to prefer this tool over sibling tools (e.g., abstract_retrieval), nor does it mention any exclusions or alternative tools. The context is clear for a search tool, but the when-vs-alternatives guidance is absent.

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?

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals what the response includes (publisher, subject areas, CiteScore), which is useful, but doesn't mention error behavior, authorization requirements, or whether the operation is read-only. While 'retrieve' strongly implies a safe read, the lack of any caveats about failures or access limits leaves some transparency gaps.

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 a single, well-structured sentence that immediately states the purpose and inclusions. It contains no redundant words, fulfills its role without overwhelming the reader, and front-loads the essential action and target.

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 tool with two parameters and no output schema, the description provides sufficient context to understand the tool's basic behavior. It lists the key data points returned, which helps set expectations. However, it doesn't explain the differences between the view options or mention what happens when an ISSN is invalid or not found, which are minor completeness gaps.

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 input schema describes both parameters (issn and view) with 100% coverage, so the baseline is 3. The description adds no additional meaning about how the parameters behave or how to format them. The mention of CiteScore metrics hints at the view enum but doesn't clarify when to use STANDARD vs ENHANCED vs CITESCORE, which would have added value.

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 action ('Retrieve detailed information'), the resource ('specific journal or serial publication'), and the identifier needed ('by its ISSN'). It also lists included content (publisher, subject areas, CiteScore), which distinguishes it from sibling tools like serial_title_search that likely handle searching rather than targeted retrieval.

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 makes the use case clear: you should use this tool when you have a specific ISSN and need detailed metadata. It implies a contrast with search functions, but doesn't explicitly name alternatives or when not to use it. Since the context is clear and no exclusions are needed for this straightforward retrieval operation, a score of 4 is appropriate.

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?

With no annotations provided, the description must disclose behavioral traits. It only states the searchable fields and does not mention pagination behavior, result format, default filters, OR/AND logic, or limitations. This is a significant gap for a search tool with no output schema.

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?

A single, front-loaded sentence that communicates the tool's core function efficiently. No redundant words or filler.

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?

Despite 10 parameters and no annotations or output schema, the description gives only a high-level search statement. It omits critical operational details such as response fields, pagination defaults, and filter combination semantics, leaving the agent under-informed for effective use.

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 input schema provides descriptions for all 10 parameters (100% coverage), so per guidelines the baseline is 3. The description merely restates a subset of these filters without adding semantic value about parameter interactions or defaults.

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 uses the specific verb 'Search' and identifies the resource as 'academic journals and serial publications in Scopus,' listing the filter criteria (title, ISSN, publisher, subject area, open access status). This clearly distinguishes it from siblings like scopus_search (documents) and serial_title_retrieval (specific record retrieval).

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 a clear use case: when you need to search for serials by bibliographic properties. It does not explicitly name alternatives or exclusions, but the context is clear enough to differentiate from nearby tools focused on article retrieval or single-title lookup.

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?

With no annotations provided, the description carries the full burden. It discloses that the tool returns 'classification codes, abbreviations, and descriptions,' which is a useful behavioral detail. However, it does not mention any additional behavior such as filtering logic, response size, or required permissions, leaving some gaps.

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 concise sentences immediately state purpose and usefulness, with no redundant wording. The title and description are front-loaded, making it easy to scan.

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 tool's simplicity and full schema coverage, the short description is largely sufficient. It mentions the return categories, partially compensating for the absence of an output schema. A bit more detail on filtering behavior would improve completeness, but it is generally complete for a metadata lookup 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?

The input schema has 100% coverage with descriptive parameter documentation, so the description need not add much. The description does not go beyond the schema's parameter descriptions, warranting the baseline score of 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 clearly states the tool's function: 'Retrieve subject area classifications used in Scopus or ScienceDirect' with a specific resource and purpose. It distinguishes itself from sibling search/retrieval tools by focusing on classification metadata rather than documents.

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 phrase 'Useful for finding subject codes to filter searches' provides clear context for when to use the tool. While it does not explicitly name alternatives or exclusions, it implies integration with search tools like scopus_search.

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