Server Quality Checklist

Tool Scores

• search_semantic_scholarC
  2.7/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden. It states it returns a result list, which implies a limited read-only operation, but does not disclose pagination, result format, or why it is 'legacy'. The description adds minimal behavioral context beyond what the tool name implies.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, succinct sentence that is front-loaded with the key action ('Legacy paper search'). It avoids fluff, but it is so brief that it leaves out necessary details. Still, for what it contains, it is well-structured and concise.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool is simple (2 params) but lacks annotations and has a vague description. It does not explain what 'result list' means, how it differs from search_semantic_scholar_papers, or provide any guidance on when the legacy version is appropriate. An output schema exists but its content is not visible here, so the description must cover more ground than it does.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description should compensate for parameter meaning, but it does not. The schema itself clearly defines 'query' and 'num_results' with types and defaults, but the description adds no additional semantics or usage context for these parameters.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly identifies the tool as a paper search with the verb 'search' and resource 'paper', and adds that it returns 'only the result list'. This distinguishes it from more comprehensive sibling tools like search_semantic_scholar_papers, though it doesn't explicitly explain what the result list contains.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance is provided on when to use this tool versus alternatives. The word 'legacy' hints that it may be deprecated, but there is no explicit recommendation to prefer search_semantic_scholar_papers or another sibling. No exclusions or prerequisites are mentioned.

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

• get_semantic_scholar_paper_authorsC
  2.8/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden. It adds only 'offset pagination' as a behavioral detail, but fails to disclose anything about safety, rate limits, default field behavior, or response structure beyond what the output schema already provides. Minimal behavioral insight is given.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, efficient sentence that front-loads the primary purpose and notes pagination. There is no redundant wording or unnecessary filler, though its brevity does limit the amount of useful information conveyed.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with four parameters and a custom output schema, the description is too sparse. It omits crucial context such as the expected paper_id format, the meaning of 'fields', and pagination corner cases. Even though an output schema exists, the description fails to provide the operational context an agent needs to select and use the tool effectively.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate, but it does not explain any of the four parameters (paper_id, limit, offset, fields). The mention of 'offset pagination' is generic and does not clarify the semantics of 'fields' or the required 'paper_id' format.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb and resource ('List the authors of a paper') and clearly distinguishes itself from sibling tools like get_semantic_scholar_paper_details or get_semantic_scholar_author_details. The scope is unambiguous and immediately understandable.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description lacks any guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or when a different sibling tool would be more appropriate, leaving the agent without clear decision-making context.

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

• recommend_semantic_scholar_papers_for_paperC
  2.8/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden for behavioral disclosure. It only states the core function and gives no insight into how similarity is computed, whether any modifications occur, or what the response structure entails beyond the output schema. Minimal indication that this is a read-only operation.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, clear sentence that is front-loaded and free of filler. However, it is so minimal that it borders on under-specification, though it does effectively communicate the core purpose.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with four parameters, no annotations, and an output schema, the description is insufficient. It omits key context about how parameters like pool_from and fields affect behavior, and does not explain the recommendation criteria or any preconditions.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, and the description does not explain any of the four parameters. 'paper_id' is implicitly linked to 'one positive example paper', but limit, fields, and pool_from are entirely unexplained, leaving the agent without necessary parameter meaning.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool recommends papers similar to one positive example paper, using a specific verb ('Recommend') and resource ('papers'), and distinguishes itself from the sibling tool 'recommend_semantic_scholar_papers' by specifying 'one positive example paper'.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance is provided regarding when to use this tool versus alternatives like search or the batch recommendation tool. The intended usage is only implied by the phrase 'similar to one positive example paper', with no explicit context or exclusions.

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

• get_semantic_scholar_dataset_diffsC
  2.9/5.0
  Behavior2/5

  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 only says 'Get incremental update/delete files' but does not disclose return format, pagination, authentication needs, or whether it returns metadata or file contents. This is minimal and leaves the agent guessing.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, front-loaded sentence with no wasted words. It is efficiently written, though it sacrifices valuable context for brevity.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's moderate complexity (3 required parameters, no annotations) and the existence of an output schema, the description is too sparse. It does not clarify what 'diffs' entail, how releases are identified, or what the caller can expect from the result. The agent would need to rely on parameter names and possibly external knowledge to use it confidently.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. The description mentions 'two dataset releases' which hints at start_release_id and end_release_id, but it does not explain dataset_name or the expected format/range of releases. Parameter names are self-explanatory, but the description adds very little beyond what the schema already exposes.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states a specific verb ('Get') and resource ('incremental update/delete files between two dataset releases'), which distinguishes it from sibling tools like get_semantic_scholar_dataset_release or get_semantic_scholar_dataset_download_links. It is immediately actionable.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It simply states what it does without contextual hints about appropriate scenarios.

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

• search_semantic_scholar_papersC
  2.9/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It does add value by disclosing that results are relevance-ranked and that offset pagination is supported, which are behavioral traits beyond the raw schema. However, it omits any mention of return format, error conditions, or rate limits, which are important for a search tool. This is adequate but not rich.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single concise sentence that front-loads the tool's purpose and key capabilities. Every word contributes, and there is no redundancy or fluff.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Despite the presence of an output schema, this is a complex tool with 11 parameters, and the description does not explain how to use them effectively. It omits important context like how filters interact, what venue/publication_types accept, and pagination limits. The description is too sparse for an agent to make informed parameter choices.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate, but it does not. It merely mentions 'filters' without explaining any of the 11 parameters (e.g., year, venue, fields_of_study, min_citation_count). This provides no additional meaning over the schema's bare titles.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool runs a relevance-ranked search for papers, which is a specific verb+resource. It distinguishes from sibling tools like author or snippet search by explicitly mentioning 'paper search'. However, it does not name any alternatives, so it misses the full distinguishing power 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.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance is provided on when to use this tool versus alternatives such as batch_get_semantic_scholar_papers or search_semantic_scholar. The description only says what it does, not when to prefer it over siblings, leaving the agent without usage context.

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

• batch_get_semantic_scholar_authorsB
  3.1/5.0
  Behavior2/5

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

  No annotations are provided, so description must disclose behavior. It only states a maximum of 1,000 IDs, but fails to mention read-only nature, rate limits, error behavior, or what happens with invalid IDs. Minimal behavioral disclosure.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Single sentence that is front-loaded with the action and limit. No wasted words.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Although an output schema exists (covering return values), the description lacks essential context such as allowed field values, prerequisites, and when to choose this batch tool over alternatives. For a tool with no annotations and zero param descriptions, this is insufficient.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Because schema description coverage is 0%, the description must explain parameters. It clarifies that author_ids are Semantic Scholar author IDs, but this is largely redundant with the parameter name. The optional 'fields' parameter is completely unexplained, leaving the agent to guess what values it accepts.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  Clear verb ('Get'), resource ('authors'), method ('by Semantic Scholar author ID'), and scope ('multiple', max 1,000). Distinguishes from single-author and paper batch tools by explicitly limiting to authors.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance on when to use this versus alternatives like get_semantic_scholar_author_details or batch_get_semantic_scholar_papers. The only implied usage is that it is for multiple author IDs, but no exclusions or alternative recommendations are provided.

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

• search_semantic_scholar_snippetsB
  3.1/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full responsibility for disclosing behavior. It only states the search action and source fields, but does not mention output format, pagination, result structure, or any limitations. The existence of an output schema partially covers return values, but the description adds no behavioral details beyond the basic purpose.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single concise sentence that front-loads the verb and object. It has no filler, and every word contributes to stating the tool's purpose. For a tool of this complexity, brevity is positive, though it comes at the cost of missing details noted in other dimensions.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (11 parameters, no annotations, no schema descriptions), the description is inadequate. While the output schema exists and covers return values, the description does not explain how the search works, what filters are available, or how to construct a query. It provides only the bare minimum context.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The input schema has 11 parameters with 0% description coverage, yet the description does not explain any parameters. It merely mentions the fields searched (titles, abstracts, full text), which does not map to specific parameters like venue, authors, or min_citation_count. The description fails to compensate for the lack of schema descriptions, leaving the agent to guess parameter meanings.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states a specific verb ('search') and resource ('relevant passages from paper titles, abstracts, and full text'). This distinguishes it from sibling tools like search_semantic_scholar_papers, which search for papers rather than passages. The scope of search is well-defined.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies the tool is for finding passages within papers, but it does not explicitly state when to use it over sibling tools like search_semantic_scholar_papers or search_semantic_scholar. No exclusions or alternative recommendations are provided. The usage context is only implied by the wording.

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

• match_semantic_scholar_paperB
  3.2/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of disclosure. It only states that the tool finds the best matching paper, but does not disclose how matching works (e.g., fuzzy vs exact), whether it returns null if no match, how filters affect the match, or any potential side effects (though likely read-only). This leaves significant behavioral ambiguity.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence with no filler, directly stating the core purpose. However, given the tool's 9 parameters, this brevity borders on under-specification, though it remains efficiently structured and front-loaded.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool has a rich schema (9 parameters) and sibling tools that differentiate among search/match/get operations, but the description gives no context on return value, filter behavior, or edge cases. It is complete only for a trivial tool and does not meet the needs of an agent selecting among closely related Semantic Scholar tools.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The description only clarifies that the 'query' parameter is the 'supplied title'; all other parameters (year, venue, fields, fields_of_study, open_access_pdf, publication_types, min_citation_count, publication_date_or_year) receive no explanation beyond their schema names. With 0% schema description coverage, the description fails to compensate for the missing parameter semantics.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses the verb 'Find' with resource 'paper' and specifies the matching criterion ('whose title best matches a supplied title'). This clearly distinguishes it from search tools (which return multiple results) and get-details tools (which take an ID), giving it a specific purpose.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage when the user has a title and wants the best-matching paper, but it does not explicitly state when to use this tool over search_semantic_scholar_papers or batch_get_semantic_scholar_papers, nor does it mention exclusions or alternative tools. Thus, usage guidance is only implied.

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

• get_semantic_scholar_citations_and_referencesB
  3.3/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden of disclosing behavior. It discloses that the tool is a legacy helper and returns only the first page, which is important for setting expectations. However, it does not mention the output structure, whether it combines citations and references or returns them separately, or any other side effects.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence that successfully conveys the main purpose and key limitations. It is efficiently written with no superfluous words.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The description covers the essential fact that this is a legacy first-page-only helper, but given the existence of separate citations and references tools, it could clarify when to use this combined one. The output schema exists but the description doesn't explain whether both types of results are included in the same response structure. Still, for a simple legacy tool, the description is adequately short.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema provides a single required parameter 'paper_id' with no description, and the description does not explain what format it should be in or how to obtain it. This leaves the agent without guidance on how to fill the parameter correctly.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's function: returning the first page of citations and references for a paper. The term 'Legacy helper' distinguishes it from more modern or comprehensive sibling tools like get_semantic_scholar_paper_citations and get_semantic_scholar_paper_references. However, it could be clearer about whether it returns both in one structure or as separate items.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies that this is a legacy tool, suggesting it may not be the preferred option, but does not explicitly name alternatives or provide conditions for when to use it. It notes that only the first page is returned, which warns against using it for full data retrieval, but does not say 'use X instead'.

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

• recommend_semantic_scholar_papersB
  3.3/5.0
  Behavior3/5

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

  The description reveals that the tool uses positive examples and optional negative examples to generate recommendations, which adds context beyond the tool name. However, it does not disclose any other behavioral traits such as rate limits, authentication requirements, or how negative examples influence the output. Since no annotations are provided, the description carries the full burden but only partially fulfills it.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single concise sentence that gets straight to the point. It uses no unnecessary words and is well-structured, making it easy to parse quickly.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Although an output schema exists to describe return values, the description is too sparse for a tool with four parameters and a specific recommendation mechanism. It does not clarify the role of 'limit' and 'fields', nor does it provide any usage context. An agent would need to infer parameter meanings solely from names, which may be insufficient for correct invocation.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The description mentions positive and negative examples, which loosely map to positive_paper_ids and negative_paper_ids, but it does not explain the 'limit' or 'fields' parameters. Schema description coverage is 0%, and the description adds minimal meaning beyond what the parameter names already convey. It fails to compensate for the missing descriptions of the optional parameters.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's function: to recommend papers based on positive examples and optionally negative examples. It uses a specific verb 'recommend' and specifies the input resource, distinguishing it from sibling tools like search or get details, and even from 'recommend_semantic_scholar_papers_for_paper' which implies a single paper input.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives such as search or the other recommendation tool. It does not mention typical use cases, prerequisites, or situations where this tool would be preferred over others. No exclusions or alternative recommendations are given.

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

• get_semantic_scholar_author_detailsB
  3.4/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It discloses the basic read operation but omits any details about response shape, error behavior, or required fields. Minimal behavioral context beyond the trivial 'get' action.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, clear, front-loaded sentence with no superfluous words. It is concise without being a tautology.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple getter with an output schema, the description is minimally adequate but lacks guidance on when to use it over siblings and the meaning of the 'fields' parameter. The output schema covers return structure, but the description provides no extra context.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 0% and the description only clarifies the 'author_id' parameter ('by Semantic Scholar author ID'). The optional 'fields' parameter is not explained, and the description adds no additional semantics beyond what the schema's types already show.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb ('Get') and resource ('one author by Semantic Scholar author ID'), clearly distinguishing it from batch retrieval and search tools. It precisely states the tool's scope.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage when you have a specific author ID and need a single author's details, but it does not explicitly contrast with alternatives like search or batch tools, nor mention 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.

• search_semantic_scholar_authorsB
  3.4/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden of behavioral disclosure. It only mentions offset pagination but does not disclose whether authentication is needed, rate limits, sorting behavior, or what constitutes a match (e.g., exact vs fuzzy). This is minimal transparency for a search tool.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence with no wasted words. It front-loads the primary purpose and includes the key pagination detail, making it highly efficient.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has 4 parameters and no annotations, the description is too sparse to fully support correct usage. While an output schema exists, the description does not explain the meaning of 'fields', when to use this over sibling tools, or any constraints like result limits or error conditions. The context is incomplete for an agent to confidently invoke the tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. It adds meaning by specifying the query is an author name and indicates offset/limit pagination. However, the 'fields' parameter remains completely unexplained, leaving a significant semantic gap.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool searches for authors by name, using a specific verb and resource. It distinguishes itself from sibling tools like batch_get_semantic_scholar_authors and get_semantic_scholar_author_details by focusing on name-based searching with pagination.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies the tool is for name-based author searches but does not explicitly mention when to use it over alternatives such as batch_get_semantic_scholar_authors or autocomplete tools. No exclusions or alternative recommendations are provided, leaving usage context only implied.

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

• autocomplete_semantic_scholar_papersA
  3.5/5.0
  Behavior2/5

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

  No annotations are provided, so the description must convey behavioral traits. It only states the core action and does not disclose any side effects, authentication needs, rate limits, or the nature of the response. The description 'Suggest... completions' is minimal and assumes read-only behavior without stating it.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, focused sentence with no unnecessary words. It front-loads the essential information about what the tool does and the condition under which it operates.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple single-parameter tool with an output schema, the description covers the basic purpose and parameter meaning. However, it lacks any guidance on when to use this tool versus alternatives and does not disclose behavioral expectations such as whether it is read-only or any limitations. Thus, it is minimally sufficient but has clear gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema has one parameter 'query' with no description (0% coverage). The description adds the qualifier 'partial query', which clarifies that the input should be a partial paper-title string. This provides some meaning beyond the schema, but it does not elaborate on format or constraints, so it only partially compensates.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb 'Suggest' with a clear resource 'paper-title query completions' and scoping condition 'for a partial query'. This clearly distinguishes it from sibling search tools like search_semantic_scholar_papers, which return full results rather than completions.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies the tool is for partial queries needing completions, but it does not explicitly state when to use this tool over alternatives or provide any exclusion criteria. There is no mention of related search tools or when autocomplete would be inappropriate.

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

• batch_get_semantic_scholar_papersA
  3.5/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden for behavioral disclosure. It only mentions what the tool does, not rate limits, batch size limits, error handling for invalid IDs, or read-only status. This leaves significant behavioral ambiguity.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single concise sentence that front-loads the verb and resource, then efficiently enumerates supported ID types. No filler or redundant information.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool is moderately complex with an output schema and two parameters. The description covers the core purpose and ID types, but lacks usage guidance, behavioral details, and clarity about the fields parameter. It is adequate but not comprehensive.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description is the only source of parameter meaning. It helpfully clarifies the paper_ids parameter by listing accepted ID formats (S2, CorpusId, DOI, etc.), but the fields parameter is entirely unexplained, leaving a gap.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: 'Get multiple papers' with a specific list of supported ID types. This distinguishes it from single-paper retrieval and search tools, and the 'batch' in the name reinforces the multi-item scope.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage when you have multiple paper IDs to fetch at once, but it does not explicitly specify when to use this tool versus alternatives like get_semantic_scholar_paper_details or search tools. No exclusions or alternative comparisons are provided.

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

• bulk_search_semantic_scholar_papersA
  3.5/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden of behavioral disclosure. It reveals the pagination mechanism (passing the token) and the high-volume nature, but omits details like rate limits, response format expectations, or any constraints around bulk usage.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, front-loaded sentence that conveys the core purpose and a key operational detail. It contains no filler or redundancy, earning its place efficiently.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has 11 parameters, no annotations, and zero schema descriptions, the description is too minimal. It covers the high-level purpose and pagination, but a complex bulk search tool with many optional filters needs more contextual guidance to be used effectively, even though the output schema exists.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0% and there are 11 parameters. The description only gives meaning to 'token' (returned token for next page) but does not explain query, sort, year, venue, fields, or other parameters. This is insufficient compensation for the low schema coverage.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states a specific action ('Run high-volume paper search') on a specific resource (Semantic Scholar papers). It also distinguishes this bulk variant from sibling search tools by emphasizing high-volume operation and pagination via a returned token.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies use for high-volume, paginated searches by mentioning 'high-volume' and 'pass the returned token for the next page', but it does not explicitly state when to choose this tool over regular search_semantic_scholar_papers or provide exclusions/alternatives.

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

• get_semantic_scholar_author_papersA
  3.5/5.0
  Behavior2/5

  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 only states the core action ('List') and filtering option, but does not mention pagination behavior, field selection, ID format, or any requirements/constraints. This leaves significant behavioral ambiguity.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, front-loaded sentence with no unnecessary words. It conveys the core action and the optional filter efficiently.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Despite having an output schema, the description under-specifies a tool with five parameters, no annotations, and no schema descriptions. It does not explain how to obtain author_id, what fields can be requested, or how pagination works, making it minimally viable only for the simplest invocation.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema has 0% description coverage, so the description must compensate by explaining parameters. It only hints at publication_date_or_year via 'optionally filtering by publication date/year', but says nothing about author_id, limit, offset, or fields. This is insufficient for a 5-parameter tool.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb ('List') and resource ('an author's papers'), clearly distinguishing it from sibling tools like get_semantic_scholar_author_details or search_semantic_scholar_papers. It also notes the optional filtering by publication date/year, adding useful scope.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description gives clear context: use this tool when you need to enumerate an author's papers, optionally filtered by date. However, it does not explicitly mention when not to use it or name alternative tools for related tasks, so it lacks explicit exclusions.

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

• get_semantic_scholar_paper_citationsA
  3.5/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden of behavioral disclosure. It adds useful context about returned content (contexts, intents, influence) but omits details like pagination behavior, rate limits, or what 'influence' means. It's not misleading, just incomplete for a tool without any 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, front-loaded sentence that efficiently communicates the core action and high-value response features. No wasted words.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with 5 parameters, 0% schema coverage, and no annotations, the description is too sparse. An output schema exists but is not visible in the context, so relying on it for completeness is risky. The description provides the basic purpose but leaves parameter usage, alternatives, and behavioral nuances unaddressed.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate, but it doesn't explain any parameter. The mention of 'contexts, intents, and influence' hints at possible fields for the `fields` parameter, but `publication_date_or_year` and pagination parameters are left entirely ambiguous. Minimal added meaning beyond parameter names.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  Description uses specific verb 'List' and clearly states the resource: papers citing a given paper. It also highlights key included elements (contexts, intents, influence), distinguishing it from sibling tools that retrieve references rather than citations.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage (when you want to see citing papers), but it doesn't explicitly state when not to use it or provide comparisons with sibling tools like get_semantic_scholar_citations_and_references or get_semantic_scholar_paper_references. No exclusions are mentioned.

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

• get_semantic_scholar_paper_referencesA
  3.5/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden. It adds value by mentioning that references include contexts, intents, and influence, offering insight into returned data. However, it does not disclose pagination behavior, authentication needs, or rate limits, 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  A single, front-loaded sentence provides clear information without fluff. It efficiently communicates the core purpose and key inclusions.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  While an output schema exists, the description is incomplete for a 4-parameter tool. It lacks usage guidance, parameter explanations, and explicit behavioral caveats. The existence of related sibling tools like get_semantic_scholar_citations_and_references makes the missing guidance more noticeable.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. It only implicitly identifies paper_id as the target paper, but fails to explain limit, offset, and fields parameters. The output schema exists but does not help parameter understanding.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool lists a paper's references and specifies included content (contexts, intents, influence). The verb 'List' and resource 'paper's references' are specific, and the name distinguishes it from related tools like citations.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage: when you need a paper's references, use this tool. However, it does not explicitly mention when not to use it or alternatives like get_semantic_scholar_paper_citations or get_semantic_scholar_citations_and_references.

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

• list_semantic_scholar_dataset_releasesA
  3.5/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only operation by using 'list', which is transparent about the non-destructive nature, but it does not explicitly state return behavior beyond 'release IDs' or mention any potential rate limits or formatting details.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single concise sentence that precisely states the tool's function. Every word contributes meaning, with no fluff or repetition. It is appropriately sized for the simplicity of the tool.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the zero-parameter simplicity and the presence of an output schema, the description is mostly complete. It specifies the primary output (release IDs) and indicates enumeration of all available releases. However, it could slightly benefit from noting that this is a listing operation to precede other dataset tools, but that is a minor enhancement.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The tool has zero parameters, so the schema is trivially 100% covered. The baseline for 0 params is 4, and the description appropriately avoids padding with irrelevant parameter details. It adds no parameter-specific meaning because there are none to describe.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the action ('List') and the resource ('Semantic Scholar dataset release IDs'), making it easy to understand. It distinguishes itself from sibling tools like 'get_semantic_scholar_dataset_release' by indicating it enumerates all available IDs, though it does not explicitly reference these alternatives.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or context. It simply states what it does, leaving the agent to infer that it should be used to obtain release IDs before fetching specific releases.

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

• get_semantic_scholar_dataset_download_linksA
  3.6/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It does disclose that the links are 'temporary,' which is a useful behavioral trait, but it does not specify expiry duration, access requirements, or other behavioral nuances. This adds some value but falls short of rich transparency.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, concise sentence that front-loads the core purpose without extraneous words. Every word contributes meaning, making it highly efficient.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool has a simple interface with two parameters and an output schema, so the description need not elaborate on return values. However, it lacks context on how to discover valid release_id/dataset_name values, what 'temporary' implies operationally, and when to prefer this over sibling tools. Thus it is adequate but not complete.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0% and the description provides no additional parameter semantics beyond the parameter names themselves. While release_id and dataset_name are fairly self-explanatory, the description does not clarify formats, sources, or relationships (e.g., that dataset_name belongs to the given release), so it fails to compensate for the lack of schema descriptions.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the verb 'Get' and the resource 'temporary download links for one dataset in a release,' identifying exactly what the tool does. It also distinguishes itself from sibling tools like get_semantic_scholar_dataset_release and get_semantic_scholar_dataset_diffs by focusing on download links for a single dataset.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The implied usage is that this tool is for obtaining download links for a dataset within a release, but it provides no explicit guidance on when to use it versus alternatives, prerequisites (e.g., knowing the release_id), or when not to use it. The context from sibling names suggests differentiation but the description itself does not state it.

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

• get_semantic_scholar_paper_detailsA
  3.9/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It usefully discloses the accepted identifier formats, which is important behavioral detail. However, it omits any mention of error behavior, required encoding, or availability of an output schema, leaving some opacity.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, efficient sentence that front-loads the action and resource. Every word contributes, with no filler or redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool is simple and has an output schema, so return values are covered. However, the fields parameter is left unexplained, and the description doesn't clarify differences among the ID types or any prerequisites. It is adequate for basic invocation but not comprehensive.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Since schema description coverage is 0%, the description must explain parameters. It effectively explains paper_id by listing the ID types it accepts, but it completely ignores the optional 'fields' parameter, leaving its semantics (e.g., what field names are allowed) undocumented.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool gets one paper and enumerates the accepted identifier types (S2, CorpusId, DOI, arXiv, ACL, MAG, PMID, URL ID). This sharply distinguishes it from sibling tools like batch_get_semantic_scholar_papers or search_semantic_scholar_papers, which handle multiple papers or use queries.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The phrase 'Get one paper' implies a specific use case: retrieving a single paper by its ID. This gives clear context for when to invoke the tool and implicitly excludes bulk retrieval, though it doesn't explicitly name alternatives like batch_get_semantic_scholar_papers.

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

• get_semantic_scholar_dataset_releaseA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It clearly indicates a read-only listing operation and adds the behavioral detail that 'latest' is accepted. However, it omits any mention of potential pagination, rate limits, or large payloads, leaving 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, focused sentence with an inline code reference for 'latest'. Every word is purposeful; there is no filler or redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (one parameter) and the presence of an output schema, the description is sufficiently complete for selection and invocation. It covers the essential choice of release (including the 'latest' shorthand) and the action. Omitting details already addressed by the output schema or sibling tools is appropriate.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. It adds meaningful parameter semantics by noting that `release_id` accepts the special value 'latest', which is not in the schema. Still, it does not describe typical release ID formats or how to obtain them, partially mitigating the coverage gap.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses the specific verb 'List' and clearly identifies the resource: datasets and metadata within a release. It distinguishes itself from siblings like list_semantic_scholar_dataset_releases by focusing on contents of a specific release, and the inline note about 'latest' adds further specificity.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description clearly implies when to use this tool: with a release_id to list its datasets. It does not explicitly name alternatives, but the context of sibling tools makes the distinction apparent. There are no exclusions, so it is clear but lacks explicit when-not-to-use guidance.

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