Yamagishi Lab: math-physics papers and separators

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

No annotations are provided, so the description carries the full disclosure burden. It is clearly a read that returns a fixed field set, but it says nothing about what happens with an invalid or retired number, or whether missing fields (e.g. no English abstract) are omitted or null.

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

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

A single front-loaded sentence with no filler; the field enumeration is dense but every item is informative. It reads cleanly, though the long field list could be tightened.

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 no output schema, enumerating the returned fields is the right compensatory move and makes the response shape predictable. The remaining gap is failure behavior for nonexistent numbers, which for a one-parameter read tool is a modest omission.

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

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

Schema description coverage is 100%, and the schema itself carries the non-obvious note that number 47 is retired and merged into 46. The description only restates that input is a paper number, adding no meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb (返す) and resource (論文の番号から) and enumerates exactly which fields come back (title, subtitle, separator sentence, abstracts, keywords, YOI address, DOI). It never names the siblings search_papers or list_separators, so the agent must infer the difference from the tool name alone.

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?

Usage is only implied: the tool takes a paper number, so an agent can infer it is the lookup-by-id step. There is no explicit statement that search_papers should be used first to obtain a number, and no guidance for a number that no longer exists.

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

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

No annotations exist, so the description carries the full burden; it does disclose the return content (the separator sentence plus the YOI address), which is valuable since there is no output schema. It says nothing about read-only semantics, permissions, or pagination beyond the limit parameter, and 'YOI の住所' is left unexplained.

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 short sentences with the resource description front-loaded and the query filter second; nothing is wasted, though the telegraphic style and undefined term 'YOI' cost some clarity.

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 two-parameter list tool with no annotations or output schema, the description covers what is listed and what is returned. It falls short on explaining the specialized vocabulary and on where this tool sits relative to get_paper and search_papers.

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

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

Schema coverage is 100% and both parameters already document their defaults and examples, so the baseline is 3. The description's query note largely restates the schema's own '語を含む' wording without adding syntax or matching behavior beyond it.

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?

States a concrete verb and resource: a list of papers whose subtitle reads '分離子は、…', returning the separator sentence and the YOI address. The narrow, pattern-based scope is implicitly distinct from a general paper search, but no sibling is named, so differentiation from search_papers rests on inference.

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 second sentence implies the usage rule — pass query to narrow to separators containing that word, omit it to get the newest-first list — but this is framed as a parameter note rather than guidance on when to choose this tool over search_papers or get_paper.

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

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

With no annotations, the description must carry behavioral burden. It usefully discloses the collection bounds (1–1095), exactly which fields are searched, and the bilingual query tolerance. However it says nothing about result ordering, match semantics beyond the schema's AND note, or what a hit contains, and never explicitly confirms 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.

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

Three short sentences, front-loaded with the resource and scope. The parenthetical clarifying that 'subtitle' includes the separator sentence is the one dense detail, and it earns its place by resolving a domain ambiguity. Slight redundancy between the opening 'by word' and the later field list, but 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?

For a 3-parameter search tool with no output schema and no annotations, the description covers input scope well but leaves the return side unaddressed, and gives no hint about how to escalate from a broad query to fetching a specific paper with get_paper. Adequate but with a clear gap on results and on sibling handoff.

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

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

Schema coverage is 100%, with per-parameter descriptions, defaults, enum values and example terms, so the baseline would be 3. The description adds genuine meaning beyond the schema by stating that queries may be issued in Japanese or English, which is a substantive semantic fact about the query parameter that the schema does not convey.

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?

States a specific verb and resource plus a concrete scope: word-search over Yamagishi Lab's mathematical physics papers numbered 1–1095, across title, subtitle (including the separator sentence), keywords and abstract. That is far more specific than a name restatement. It never names the sibling get_paper (single-paper fetch) to draw the retrieval boundary, but the search-vs-fetch distinction is strongly implied by the name and the 'by word' framing.

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 only usage guidance is 'Japanese or English both fine', which tells the agent the query language is unconstrained. There is no statement of when to prefer this over get_paper or list_separators, and no guidance on what to do with an empty result set. Usage is inferable from the tool name but not explicitly routed.

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