Conference Partner

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

Given the readOnlyHint annotation is already present, the description adds valuable context: it requires credentials (with exact authentication methods and URL), and cautions that responses link to the Conference Partner detail_page rather than the venue's external website. These are meaningful behavioral traits beyond the annotation.

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

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

The description is two sentences: the first front-loads the purpose and content details, the second conveys credential requirements and a linking caveat. Every sentence adds unique information with no redundancy or fluff.

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, the description lists the returned components, mentions required authentication, and flags an important linking behavior. This is sufficient for an agent to know what to expect and how to call the tool, even without structured response details.

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% because the only parameter 'id' is described as 'Conference id' in the input schema. The description repeats this without adding new semantic details like validation rules or how to obtain the id. This matches the baseline for high schema coverage.

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

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

The description clearly states the tool gets full details of a conference by id, enumerating the types of data included (basics, CFP text, acceptance-rate history, edition history, ratings, comments, related venues). This specific verb+resource combination distinguishes it from siblings like get_journal and search_conferences.

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

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

The description implies use when you have a conference id and need comprehensive details, which is clear context. It does not explicitly mention alternatives or when-not-to-use, but the purpose statement differentiates from search/list tools sufficiently for an agent to select it appropriately.

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 readOnlyHint=true, and the description adds valuable behavioral context: it requires credentials (Authorization header) and notes that responses point to the Conference Partner detail_page rather than the venue's external site. These go beyond the static safety hint and help the agent anticipate authentication needs and response quirks.

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 concise (two sentences) and front-loaded with the main purpose. The second sentence packs necessary credential and response details without fluff. Every word adds value, and the structure is clear.

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 read tool with no output schema, the description thoroughly covers what is returned (basics, CFP, special issues, ratings, related items) and the required auth context. All essential information is present, making it self-sufficient for an agent.

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

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

The schema covers 100% of parameters (only 'id' with description 'Journal id'). The description merely reiterates 'by id' and adds no extra syntax, format, or constraints. With high schema coverage, baseline 3 is appropriate; no additional value is provided.

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+resource: 'Get full details of a journal by id' and enumerates the exact content (basics, CFP text, special issues, structured ratings, related journals/conferences). This clearly distinguishes it from siblings like list_journals (listing) and search_journals (search).

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 clearly implies when to use this tool (when you have a journal id and need full details). It lacks an explicit 'use this instead of X' statement, but the id-based scope and the contrast with listing/searching siblings provide clear context. No when-not or alternative tool is named.

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 readOnlyHint=true, and the description adds valuable behavioral context: it requires credentials (Bearer token), always excludes contact details, and has no search/enumeration capability. This goes beyond the annotation by clarifying authorization needs and data exclusions, though it does not mention error scenarios or exact response structure.

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

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

The description is two sentences that are front-loaded with the purpose and include only essential operational details (credentials, exclusions, limitations). Every sentence adds value and there is 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 tool has only one parameter, no output schema, and a read-only annotation, the description covers all necessary context: what is returned, what is not returned, how to authenticate, and the id-based access pattern. It is complete for this level of complexity.

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

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

The input schema covers 100% of the single parameter with a clear description ('Researcher (user) id'). The description reinforces 'by id' but does not add new semantic details such as format, constraints, or examples. Baseline 3 is appropriate since the schema already does the heavy lifting.

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

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

The description begins with a specific verb+resource: 'Get a researcher's public profile by id' and enumerates the exact contents (name, institution, research-interest summary, CV, conferences, journals). It clearly distinguishes from sibling tools by focusing on researchers vs conferences/journals/statistics, and there is no other researcher-specific tool.

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

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

The description provides explicit when-to-use ('by id only') and when-not-to-use ('there is no researcher search or enumeration', 'Never includes contact details'). It also notes the credential requirement as a prerequisite. However, it does not name specific alternative tools, though no search/list researcher siblings exist, so the exclusion is effectively guidance.

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 readOnlyHint annotation already indicates no destructive side effects, and the description adds extensive detail about what data is returned (totals, distributions, deadlines, tiers). It also explains the research-field key convention, which goes beyond the annotation. No behavioral contradictions.

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

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

The description is a single dense paragraph that front-loads the core purpose (site-level public statistics) and lists specific categories. It could be slightly more structured with bullet points, but it is reasonably concise for the amount of detail conveyed.

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

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

Given no parameters and a read-only annotation, the description covers the tool's output comprehensively. However, there is no output schema, so it would be helpful to know the response format or whether fields are optional. The research-field key note partially compensates.

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

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

The input schema has no parameters (schema coverage 100%), so the description provides all needed context about what the tool returns. The baseline for zero-param tools is 4, and the description richly details the output categories, which is appropriate.

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

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

The description clearly states the tool returns 'Site-level public statistics' and enumerates the exact categories (conference/journal totals, open CFPs, deadlines by month, tier distributions, research-field distributions, journal impact-factor, publisher distributions). It also clarifies that research-field keys match those used by search tools, which distinguishes it from sibling tools that focus on individual records or search.

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 tool is for aggregate statistics about the site rather than individual entities, but does not explicitly state when to use it over siblings like get_conference or search_conferences. There is no mention of alternatives or exclusions, though the scope is reasonably clear from the content.

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 readOnlyHint annotation already covers safety, and the description adds useful behavioral context: results are paginated and this is a browsing rather than searching operation. It does not contradict the annotation and provides enough behavioral framing for a read-only list tool.

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

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

The description is two sentences with no fluff. It front-loads the core purpose, gives representative examples, and ends with the key routing caveat. Every sentence 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?

For a read-only, paginated list tool with a rich input schema, the description combined with the schema gives the agent everything needed to invoke it correctly. The return type is obvious from the tool name and description, and no output schema is required.

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

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

The input schema already provides 100% parameter coverage, including detailed explanations for every ranking enum value. The description adds minimal parameter-level meaning beyond examples, so the baseline of 3 is appropriate.

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

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

The description states a specific verb ('browse') and resource ('conference lists and rankings'), with concrete examples of list categories. It explicitly distinguishes itself from search_conferences by noting the lack of keyword filtering.

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 clearly tells the agent when not to use this tool ('No keyword filtering') and directs it to search_conferences instead. The schema further reinforces this by pointing users to search_conferences for full-tier catalogue queries.

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 readOnlyHint=true, so the safety profile is known. The description adds behavioral context beyond that: it is paginated and supports multiple list types. It could also mention that no filtering is possible, but it does state that clearly, which helps set expectations.

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

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

The description is two sentences, front-loaded with the main purpose, and includes a clear exclusion with an alternative tool. Every word serves a purpose; no redundant or vague language.

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

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

Given the tool's simplicity and the richness of the schema (100% coverage) plus annotations, the description provides the necessary context: what the tool does, that it is paginated, and how it differs from search_journals. It does not describe return values, but no output schema exists and the outcome is reasonably inferable from the 'browse' phrasing.

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

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

Schema description coverage is 100%, so parameters are already documented. The description adds minor semantic value by explaining what each ranking type means (e.g., 'special-issue CFPs'), but this largely mirrors the schema's enum descriptions. No additional meaning is provided for page or per_page beyond the 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 ('Browse') and identifies the resource ('journal lists and rankings') with concrete examples (CFPs, CCF, impact factor, popularity). It also distinguishes itself from the sibling search_journals by explicitly stating it has no keyword filtering.

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?

Provides clear usage guidance: when to use this tool (browsing lists) and when not to (keyword search), naming the alternative tool explicitly. The different ranking options are also described, giving context for choosing a parameter value.

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 readOnlyHint=true, so the description need not restate safety. It adds useful behavioral context: all parameters are optional, filter-only queries are valid, and the result is a paginated list. No contradiction with 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 three short sentences, front-loaded with the core purpose. Every sentence earns its place: first defines the tool, second explains parameter flexibility, third gives an example and return type. No redundancy or superfluous detail.

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

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

Given the tool has 12 optional parameters and no output schema, the description provides key context (search, filter combinations, paginated list) without over-explaining. It doesn't detail result fields or sorting, but those are not essential for selecting the tool, especially since sibling get_conference likely covers detail retrieval.

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 descriptions cover 100% of parameters, so baseline is 3. The description adds meaning by explaining that parameters can be combined arbitrarily and that filter-only queries (e.g., field plus submission_date window without keyword) are valid, which is not obvious from individual schema entries.

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 'Search academic conferences', which is a specific verb+resource. It clearly distinguishes from siblings like list_conferences (search vs. list) and search_journals (conferences vs. journals), and emphasizes the flexible filtering capabilities.

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

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

The description provides clear context: every parameter is optional and can be combined, and filter-only queries are explicitly supported with a concrete example (field=ai plus submission-deadline window). It doesn't explicitly name alternatives or exclusions, but the search/filter nature is implicit from the sibling names.

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 annotations already declare readOnlyHint=true, covering the safety profile. The description adds that all parameters are optional and that the result is a paginated list, which is useful behavioral context. However, it does not clarify logical combination semantics (AND/OR) or behavior when no filters are applied.

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

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

The description is two sentences, front-loaded with the primary purpose, and contains no filler or redundancy. Every sentence contributes to understanding the tool's functionality.

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 7-parameter search tool with no output schema, the description is minimal. It does not mention the updated_since parameter or the incremental sync use case, nor does it clarify the relationship with list_journals. The pagination detail is present, but overall the description leaves gaps in a broader context.

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

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

Schema description coverage is 100%, with each parameter already well-documented. The description refers to 'keyword, CCF rank, research field and ISSN' but does not add significant meaning beyond the schema; 'keyword' also maps non-obviously to the 'query' parameter. This does not exceed the baseline of 3.

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

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

The description clearly states 'Search academic journals' with a specific verb and resource. It further explains that parameters can be combined and that results are paginated, making the tool's purpose unambiguous and distinct from sibling tools like list_journals and search_conferences.

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 that the tool is for flexible, filtered searching with all parameters optional, which gives some usage context. However, it does not explicitly differentiate when to use this tool versus list_journals or get_journal, nor does it provide any exclusions or mention alternative tools.

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