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

Annotations already cover readOnly, idempotent, openWorld, and non-destructive behavior. The description adds valuable behavioral context by stating that the endpoint is paginated and that result.total is only the returned count (TOTAL_NOT_REPORTED), not a true total. There is no contradiction with the annotations.

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

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

The description is two short sentences with the core purpose first and the return-value caveat second. Every phrase earns its place, and there is no fluff or redundant restating of the tool name.

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 an output schema and rich annotations, the description covers the essential invocation context: a specific author's papers with pagination, plus a nonobvious total-count caveat. It does not mention sort order or explicitly route agents away from sibling tools, but those are secondary for a simple paginated lookup.

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 description's 'by one author' and 'paginated' map naturally to author_id and the limit/offset parameters, and the nested input schema provides the concrete constraints and defaults. The tool description does not add much parameter-level detail beyond this, but it gives enough orientation for a correct call.

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 identifies the resource (papers) and the selection criterion (one author), and the pagination note adds operational context. It lacks an explicit action verb and does not name sibling tools, but an agent can distinguish it from s2_get_author, s2_search_papers, and s2_citations by its author-scoped paper listing.

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 'Papers by one author, paginated' implies the tool should be used when the agent already has an author identifier and needs that author's papers. However, it provides no explicit when-to-use or when-not-to-use guidance, nor does it point to alternatives such as s2_search_papers for keyword search or s2_get_author for author metadata.

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?

The description discloses an important behavioral trait beyond the annotations: partial failure handling via PARTIAL_NOT_FOUND diagnostic and coverage_note listing unresolved IDs. Annotations already indicate read-only/idempotent, so this additional error-handling context is valuable.

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 tightly worded sentences with no redundancy. The key batch limit is front-loaded, and the partial-failure behavior is succinctly described.

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 straightforward batch lookup with a single parameter, the description covers the operational limit, the input mode, and the return envelope's failure diagnostics. Annotations and output schema fill remaining needs, so nothing critical is missing.

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 description adds the 'up to 500' limit and batch semantics, but it does not explain accepted ID types (S2 IDs, DOIs, ArXiv IDs) or format requirements. The input schema provides this detail, and with only one parameter the description's contribution is limited but meaningful.

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?

Description states a specific action ('Look up'), resource ('papers'), and mode ('by ID', batch up to 500). This clearly distinguishes it from s2_search_papers (search by query) and s2_get_paper (single ID lookup).

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 usage context clear: use when you have a batch of paper IDs to resolve. It does not explicitly name alternatives or exclusions, but the contrast with single-ID and search tools is strongly implied by 'at once by ID'.

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

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

Annotations already indicate read-only, open-world, and idempotent behavior, so the description does not need to restate those. It adds valuable API quirk information: the endpoint reports no total, so result.total is the returned count (TOTAL_NOT_REPORTED). This goes beyond the annotations and helps the agent correctly interpret the response.

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 focused sentences with no filler. The primary purpose is front-loaded, and the total-count caveat is presented as a separate, useful note. Every word 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?

Given the presence of an output schema and comprehensive annotations, the description is largely sufficient. It covers the core operation and an important response quirk. However, it leaves out any mention of how to obtain or format the paper_id, and the phrase 'unified envelope' is unexplained, though the output schema may resolve this for the 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?

The description only clarifies the 'citations' vs 'references' direction concept, which is already present in the schema's direction property. It does not explain paper_id format, limit/offset behavior, defaults, or the required params wrapper. With schema description coverage reported as 0%, the description fails to compensate for the lack of parameter-level meaning.

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 identifies the tool as retrieving papers that cite a given paper or are cited by it, distinguishing it from sibling tools that search, fetch, or recommend papers. It also states the return format ('unified envelope') and scope of the operation, making it easy for an agent to select this tool for citation graph traversal.

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

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

The description does not provide any guidance on when to use this tool versus alternatives such as s2_search_papers or s2_get_paper. It also does not mention when not to use it or what prerequisites exist (e.g., needing a valid paper identifier). No exclusions or alternative routing are given.

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

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

Annotations already indicate this is a safe, idempotent read operation. The description adds useful behavioral context by specifying the return shape ('unified envelope with a single author item') and the NOT_FOUND outcome, which is beyond what the annotations provide.

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

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

The description is two short sentences with no filler. The primary action is front-loaded, and the return behavior is stated in a compact, informative second sentence.

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 simple one-parameter lookup tool with an output schema and read-only annotations, the description is nearly complete. It covers the input key, the single-item return envelope, and the not-found case; only explicit alternative routing to search tools is absent.

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?

There is only one parameter, author_id, and the description repeats its purpose ('by Semantic Scholar Author ID') rather than adding new details like ID format or how to obtain it. The schema also provides a minimal description, so combined coverage is sufficient but not enhanced.

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

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

The description states a specific verb ('Look up'), a clear resource ('one author'), and the exact key ('Semantic Scholar Author ID'). This distinguishes it from sibling tools like s2_search_authors, which search by query rather than lookup by ID.

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: use this when you have an Author ID and need a single author. However, it does not explicitly state when to prefer this over s2_search_authors or mention any exclusions, leaving the routing decision implicit.

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

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior. The description adds valuable disclosure about the return shape ('unified envelope with a single item') and NOT_FOUND case, which the annotations do not convey. It provides useful behavioral context beyond the structured hints.

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: the first states the action and resource, the second states the return behavior. No redundant adjectives or filler; every clause contributes to a usable definition.

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 single-parameter lookup tool with rich annotations and an output schema, the description is complete: it identifies the input format, the output container, and the not-found signal. No critical missing information remains for an agent to invoke it correctly.

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

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

With schema description coverage at 0%, the description fully compensates by enumerating the accepted identifier formats (S2 ID, DOI, ArXiv ID, URL). This gives an agent the exact semantics needed to populate the paper_id parameter correctly, including examples in the parameter schema.

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

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

The description uses a specific verb ('Look up') and resource ('one paper') and clearly distinguishes itself from sibling tools by specifying single-item lookup by ID, in contrast to search or batch retrieval. The identifier types are enumerated, making the scope unambiguous.

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 you have a single paper identifier and need that specific paper, but it does not explicitly state when to prefer this tool over s2_search_papers or s2_batch_papers. No exclusion criteria or alternatives are mentioned, leaving the routing to the agent's inference.

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

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

Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds useful non-obvious behavioral context: it returns a unified envelope with matching_mode similarity_ranked, and the seed IDs are echoed in query.params so the response receipt pins them. This goes beyond the annotation coverage.

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 sentences, with the primary purpose front-loaded and the return-behavior detail in the second sentence. There is no filler or repetition; every sentence contributes useful information.

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

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

Given the rich input schema, output schema, and annotations, the description covers the essential purpose and a key invocation quirk (seed IDs in query.params). It does not explain the 'unified envelope' jargon or route between siblings, but the remaining gaps are minor for an agent that has access to the full schema.

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

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

The nested input schema has clear descriptions for positive_paper_ids, negative_paper_ids, and limit, so the schema carries the parameter documentation burden. The description adds conceptual context ('positive seed papers', 'negative ones') but no additional syntax or constraints beyond what the schema already provides.

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

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

The description clearly states the core behavior: return papers similar to positive seed papers and dissimilar to optional negative ones. It distinguishes from s2_recommend_single by emphasizing a set of positive seeds, though it does not explicitly name the sibling or say 'recommend'.

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 for multi-seed similarity recommendations with optional negatives, but it gives no explicit guidance on when to choose this over s2_recommend_single or other siblings. No alternatives, exclusions, or when-not-to-use conditions are stated.

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

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

Annotations already cover read-only, idempotent, non-destructive, and open-world behavior. The description adds that the result is a 'unified envelope (matching_mode similarity_ranked)', but this phrase is cryptic and does not meaningfully explain output behavior or limitations beyond what annotations already provide.

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 short and front-loaded: the core behavior appears in the first sentence. The second sentence adds output-mode terminology, but it is compact and does not bloat the definition, even if it could be clearer.

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 simple single-seed recommendation tool, the description is almost sufficient, and the output schema plus annotations carry some burden. It is missing explicit guidance on the `limit` semantics and on when to prefer s2_recommend_multi, so an agent would still need to infer some important call decisions.

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 description only mentions the seed-paper concept and gives no guidance about the `limit` parameter or how the recommendation set is influenced by it. With the reported low schema description coverage, the description does not compensate by explaining parameter roles, though the input schema itself does contain basic definitions for `paper_id` and `limit`.

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 that the tool returns papers similar to one seed paper using Semantic Scholar's recommender, which is a specific resource-and-action pair. It also distinguishes itself from s2_recommend_multi by emphasizing the single-seed-paper input.

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 this is for recommendation from a single seed paper, which gives some context about when to use it. However, it does not explicitly tell the agent when to choose this over s2_recommend_multi or when not to use it, leaving the routing partly to inference.

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

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds useful context beyond these annotations by explaining the return envelope structure, the per-item record_type, and which metrics appear in extra. This gives the agent a clearer picture of the operation's output without contradicting the annotations.

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

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

The description is two concise sentences with the core purpose front-loaded. It avoids repetition of the tool name and every sentence adds specific information about behavior or return structure. No filler or redundant content is present.

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 simple search tool with strong annotations and an output schema, the description is nearly complete: it covers the action, the entity type, and the key return fields. It could be slightly more complete by acknowledging pagination behavior, though the schema already defines limit and offset. Overall, an agent can invoke this tool correctly with high confidence.

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 description only partially addresses parameters by indicating the query is an author name. It does not compensate for the 0% schema description coverage: limit and offset are not mentioned, and there is no guidance on pagination or result sizing. The schema itself provides descriptions for these fields, but the tool description carries little semantic weight for them.

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

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

The description opens with a specific verb and resource: 'Search for authors by name.' It clearly differentiates this from sibling search tools like s2_search_papers by stating the exact entity type returned and even notes the record_type as author. This is unambiguous and immediately actionable.

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 usage context is implied: use this when you need to find authors by name. However, the description does not explicitly mention alternatives or conditions for choosing this tool over s2_get_author or s2_author_papers. There is no clear when-not-to-use guidance, so it falls short of a stronger score.

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?

The description adds substantial behavior beyond the annotations: relevance-ranking mode, result.total being an estimate, title script-based language classification, and a coverage caveat. These details help an agent interpret results correctly and are consistent with the readOnly/openWorld/idempotent hints.

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 primary purpose is front-loaded in a single clear sentence, and the second paragraph adds meaningful caveats about ranking and coverage. The title-script detail is niche but relevant; the description remains compact with no 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?

Given the rich output schema and annotations, the description covers the important missing semantics: matching behavior, result total interpretation, language typing, and fallback guidance for weak coverage. Pagination and per-field constraints are already in the schema, so no critical information is missing.

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 description summarizes the filter families (year, field-of-study, citations, open access) that correspond to schema parameters, but the schema itself already documents each parameter with clear descriptions. The description adds a concise framing but doesn't provide much semantic detail beyond what the structured schema already carries.

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

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

The description opens with a specific verb and resource: 'Search Semantic Scholar for papers by keyword' and enumerates the available filters. It clearly distinguishes this from author search and paper-retrieval siblings, so an agent can tell what it does without opening schemas.

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

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

The description gives a clear main use case (keyword search with filters) and adds practical guidance: a ZERO_RESULTS in non-English humanities is weak evidence, and it names alternative servers to consult. It doesn't explicitly contrast with sibling tools like s2_get_paper or s2_citations, but the search framing makes the primary context clear.

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