crossref

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format (title, authors, DOI, publication date) and the limit of 5 most recent works, which is useful. However, it lacks details on error handling, rate limits, authentication needs, or whether it's a read-only operation, leaving gaps for a tool with no annotation support.

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 efficiently conveys the tool's purpose, input, and output without any wasted words. It is front-loaded with the core functionality, 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?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is reasonably complete for basic use. It covers what the tool does and what it returns. However, without annotations or an output schema, it lacks details on behavioral traits like error conditions or response structure, which could hinder agent reliability.

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 input schema already documents the 'issn' parameter with an example. The description adds context by specifying it's for a journal and that it retrieves recent works, but does not provide additional semantic details beyond what the schema offers, such as format constraints or edge cases.

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 specific action ('Get'), resource ('5 most recent works published in a journal'), and scope ('by its ISSN'), with distinct output details. It differentiates from sibling tools like 'get_work' (likely for individual works) and 'search_works' (likely broader searches) by focusing on journal-specific recent publications.

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 when needing recent works from a specific journal via ISSN, but it does not explicitly state when to use this tool versus alternatives like 'search_works' or 'get_work'. No exclusions or prerequisites are mentioned, leaving some ambiguity for the agent.

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 of behavioral disclosure. It describes the return data (title, authors, etc.) and implies a read-only operation, but lacks details on error handling, rate limits, authentication needs, or performance characteristics. It adds basic context but misses deeper behavioral traits.

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 in the first clause, followed by a concise list of return values. It uses two efficient sentences with zero waste, making it easy to scan and understand quickly without unnecessary elaboration.

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 low complexity (single required parameter) and no output schema, the description adequately covers the purpose and return data. However, it lacks information on error cases (e.g., invalid DOI), response format details, or integration with sibling tools, leaving some contextual gaps for an agent to handle edge cases.

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%, with the parameter 'doi' fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides (e.g., no extra examples or constraints), so it meets the baseline for high schema coverage without compensating further.

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 specific action ('Get full metadata'), resource ('academic work'), and identifier ('by its DOI'), distinguishing it from sibling tools like 'get_journal' (journal-level) and 'search_works' (search multiple). It precisely defines what the tool does without being vague or tautological.

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 implicitly indicates usage context by specifying 'by its DOI', suggesting this tool is for retrieving metadata when a DOI is known. However, it does not explicitly state when to use it versus alternatives like 'search_works' (for broader searches) or 'get_journal', nor does it provide exclusions or prerequisites, leaving some guidance gaps.

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 full burden. It mentions the return fields (title, authors, etc.) but doesn't disclose important behavioral traits like rate limits, authentication needs, pagination, error handling, or whether this is a read-only operation. The description adds minimal behavioral context beyond basic functionality.

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 efficiently conveys purpose, method, and return values. Every element earns its place with zero waste, making it appropriately sized and 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?

Given no annotations and no output schema, the description provides basic functionality and return fields but lacks completeness for a search tool. It doesn't cover error cases, result ordering, or detailed behavioral context, leaving gaps in understanding how the tool behaves in practice.

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 both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples of query syntax beyond the schema's example, no clarification on 'limit' behavior). Baseline 3 is appropriate when 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 specific action ('Search academic works'), the resource ('Crossref index'), the method ('by keyword'), and distinguishes from sibling tools by specifying it's for searching rather than retrieving specific items like 'get_journal' or 'get_work'.

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 (searching academic works by keyword) but doesn't explicitly state when to use this tool versus the sibling tools 'get_journal' or 'get_work'. No guidance on exclusions or alternatives is provided.

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