Copa do Mundo 2026

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

Annotations indicate idempotent but not read-only or destructive. Description adds critical behavioral details: it provides a login link, accepts a token for session-only login, and notes permanent config option. Does not contradict annotations; goes beyond by explaining effects of different inputs.

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?

Description is moderately concise, packed with instructions but in a single paragraph. It front-loads purpose and audience, then details. Could be broken into steps for readability, but every sentence adds value.

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 output schema and minimal annotations, description provides substantial guidance on usage scenarios Strings. Covers both setup methods and edge cases (no args vs. token), making it sufficiently complete for an auth tool.

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 has one parameter 'token' with no description (coverage 0%). Description compensates by explaining what token is (JWT) and how to provide it (paste it). This adds meaning beyond the bare 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 clearly states that the tool authenticates the user to the MCP server by logging in via browser and obtaining an access token. It distinguishes itself from siblings by being the only auth-related tool, though it does not explicitly contrast with others.

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 context on when to use: for IDE agents to authenticate. It explains two workflows (config-based permanent vs. session-based) and when to call with token vs. without, but lacks explicit 'when not to use' or alternative tool references.

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, idempotent, and non-destructive behavior. The description adds behavioral detail by explaining the different response based on connection state, but does not cover error conditions, rate limits, or side effects beyond what annotations imply.

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 no redundant wording. It efficiently conveys the core functionality and varying outputs without 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?

The description adequately explains the main return values (authenticated flag, pending array, connect URLs) for the primary scenarios. Though it lacks an explicit output schema or error handling details, for a simple status-checking tool it is sufficiently complete.

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 tool has no parameters, so schema coverage is complete (100%). The description does not need to explain parameters, and the baseline for zero parameters 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 connection status and URLs, specifying the resource (connection status). It does not explicitly contrast with sibling tools like authenticate, but its purpose is unambiguous and distinct enough.

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 for checking connection status by describing two scenarios (all providers connected vs. missing credentials), but it lacks explicit guidance on when to prefer this tool over alternatives (e.g., authenticate) or 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.

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

Annotations indicate idempotent and non-destructive, but the description does not disclose the outcome of reporting (e.g., ticket creation). It does mention the conversation requirement, adding some behavioral context, but lacks detail on side effects or post-action behavior.

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, consisting of two short sentences that directly convey the purpose and a key requirement. No unnecessary words or repetition.

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?

The description is sufficient for the tool's simplicity. It covers the action and the main data requirement, and the absence of an output schema means no need to explain return values. Minor gaps remain regarding the exact usage of 'context' and 'message', but overall it is complete enough.

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 explains the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'), but leaves 'message' and 'context' unexplained. Since the schema has no field descriptions, this partial guidance improves clarity but is not comprehensive.

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's purpose: 'Report a bug, missing feature, or send feedback.' It also specifies the need to include the conversation array for reproduction, which is precise and distinct from sibling tools.

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 when to use the tool (for bugs, missing features, feedback) but does not explicitly state when to avoid it or how it differs from alternatives. It is clear enough for the intended use case.

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, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds the object scope (platform and adapter) and 'current' dynamic nature, but does not describe output format or other behavioral details. No contradiction found.

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, front-loaded sentence with no wasted words. It efficiently conveys the tool's purpose.

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 zero-parameter version-check tool with strong annotations, the description is complete. The return value is self-evident, and no output schema is necessary to understand the tool's behavior.

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 tool has zero parameters, so the baseline is 4. No parameter explanation is needed, and the description does not need to add parameter 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 states the specific action ('Show') and the exact resource ('current MCP platform and adapter versions'). It fully explains what the tool does and distinguishes it from siblings like authenticate or toolkit_info.

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?

No explicit when-to-use guidance or alternative tool is mentioned. The usage is implied by the version-query purpose, but the description does not explicitly articulate when the agent should choose this over other tools.

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, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-destructive read operation. The description adds value by specifying exactly what information is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. 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 a single, concise sentence that front-loads the purpose ('Returns the current toolkit state') and then enumerates the specific components. Every word earns its place; there is no fluff or repetition.

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 no parameters, no output schema, and simple annotations, the description is complete enough. It clearly states what the tool returns, which is the main thing an agent needs to know. It could potentially mention that the output is a summary/overview, but that's implied by 'current toolkit state'. The description is adequate for the tool's simplicity.

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 tool has zero parameters, and the schema description coverage is 100% (vacuously, since there are no properties). The description doesn't need to explain parameters, and it doesn't. The baseline for 0 params is 4, and the description appropriately focuses on the return value instead.

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's purpose: returning the current toolkit state, including installed MCPs, connection status, connected accounts, and catalog tool counts. It uses a specific verb ('Returns') and resource ('current toolkit state'), and it distinguishes itself from sibling tools by focusing on toolkit-level introspection rather than specific operations like authentication or worldcup data.

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 when to use this tool: when you need an overview of the toolkit's state, such as installed MCPs and their status. It doesn't explicitly state when not to use it or name alternatives, but given the sibling tools are mostly domain-specific (worldcup, marketplace, etc.), the context is clear enough. A slight deduction for not explicitly mentioning alternatives.

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 is consistent with the read-only annotation but does not add extra behavioral context beyond what is already declared. It mentions the content of the bracket (confrontos and classificados), which adds slight context but not substantial transparency.

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 and to the point, using two sentences to convey the tool's purpose and a usage example. It is well structured and free of unnecessary details.

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?

The description explains what the bracket includes and gives a query example, but it lacks explanation of the 'stage' parameter, making it incomplete for users who need to know how to filter by stage. However, the overall concept is simple and mostly covered.

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 has one parameter 'stage' with no description, and the tool description does not mention it at all. Since schema coverage is 0%, the description fails to compensate by explaining what 'stage' represents or how it filters the bracket.

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 provides the knockout bracket from the round of 16 to the final, including matchups and qualified teams. It is specific about the resource (bracket) and distinguishes it from sibling tools like groups, matches, and schedules.

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 explicitly gives a usage example ('como está o chaveamento') and implies it is the tool for bracket-related queries. This provides clear guidance on when to use this tool versus alternatives.

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 tool as read-only (readOnlyHint=true), idempotent, and non-destructive. The description adds no extra behavioral context beyond confirming it's about group composition, which aligns with the annotations. It doesn't discuss side effects, authorization, or other details, but for a read-only query tool, the annotations cover the essential safety profile.

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 in Portuguese, immediately stating the purpose and providing a relevant example. Every word contributes to understanding, and it's appropriately front-loaded with the main function.

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 simple nature of the tool (one optional parameter, read-only), the description covers the core functionality and return content (teams and games per group). However, the lack of parameter documentation is a significant gap, as the agent cannot know how to specify a group. The example hints at using a country name but doesn't define the exact format or allowed values.

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 single parameter 'group' (type string) is not mentioned in the description at all. Schema description coverage is 0%, and since there are no enums or examples, the agent has no guidance on what values to pass (e.g., 'A', 'B', 'Brasil'). The description fails to compensate for the sparse schema, leaving the parameter entirely undocumented.

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 it provides the composition of groups (12 groups of 4 teams) with teams and games. It also includes a concrete use case ('quem está no grupo do Brasil'), making it specific to group queries and distinct from sibling tools like worldcup_matches or worldcup_bracket.

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 usage example ('Use para quem está no grupo do Brasil') that tells the agent when to call this tool. It doesn't mention when not to use it or name alternatives, but the context inferred from the example is sufficient for a simple tool.

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 read-only, idempotent, and non-destructive, so the description adds value by explaining default behavior (returns today's matches) and filter options. It does not contradict annotations; it merely supplements them with practical context like the date format.

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 compact yet information-dense: opens with the core purpose, then filters, default behavior, and usage examples—all in three short sentences. No fluff or redundancy, front-loaded with the most critical 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 moderate complexity (6 optional filters, no output schema), the description covers purpose, filters, default behavior, and example queries. It does not describe the return structure or timezone handling, but for a read-only simple query tool, it provides sufficient guidance for an agent to select and 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?

Schema coverage is 0%, so the description must compensate. It lists all filterable parameters (date, team, group, stage, status) and explicitly formats date as YYYY-MM-DD. It also implies filters are optional via the default behavior. However, it omits the 'timezone' parameter entirely, which is a notable gap.

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 it returns 2026 World Cup matches with score and time, and differentiates from sibling tools like schedule (which likely lacks scores) by emphasizing placar. It also specifies default behavior (today's matches) and example user queries, making the purpose 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?

It gives explicit use cases ('que horas joga o Brasil', 'jogos de hoje', 'qual foi o placar'), and states the default behavior without filters. However, it does not mention when to avoid this tool or how it compares to siblings like worldcup_schedule, only offering positive examples.

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 aligns with readOnly annotation by indicating read-only access to results, and adds the constraint of only finished games. No side effects are implied, matching destructiveHint false.

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 brief and to the point, consisting of two sentences that convey the core functionality without unnecessary verbosity.

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 output schema, the description explains it returns final scores, which is sufficient. It also clarifies scope (finished games) and gives usage examples, but could mention limitations like date range or that teams are country names.

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?

It states parameters can filter by date, team, or group, but lacks details on expected formats or combinations. The schema provides no descriptions, so the tool description partially compensates but remains vague.

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 final scores of finished games and provides usage examples, distinguishing it from sibling tools like schedule or matches.

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?

It explicitly suggests usage for queries like 'yesterday's results' and 'how did Brazil do', and mentions filterable fields, but doesn't explicitly state when to avoid using it (e.g., for upcoming matches).

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 (readOnlyHint, idempotentHint, destructiveHint) are consistent with the description's read-only nature. The description adds no contradictory info, but it also does not elaborate on side effects or special behaviors beyond 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 very concise, using two short sentences that clearly convey the purpose without unnecessary filler. It is well-structured and easy to parse.

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 annotations that establish read-only and idempotent behavior, and a clear purpose statement, the description is largely complete for basic usage. However, the lack of parameter detail and explicit filtering semantics leaves some ambiguity for more complex queries.

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 provides no descriptions for date, stage, or timezone, and the description only hints at date and stage ('por data', 'um dia, de uma fase'). The timezone parameter is not mentioned at all, leaving its meaning and format unclear.

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 provides the tournament schedule grouped by date, for a single day, a phase, or the entire World Cup. It distinguishes itself from sibling tools (e.g., results, standings) by focusing on the match schedule.

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 explicitly says to use it to see the match table for a day, phase, or entire cup, which gives clear usage direction. It does not explicitly contrast with alternatives, but the scope is evident from the sibling names and the wording.

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, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds the specific data fields returned (points, wins, etc.) and the example, providing useful behavioral context beyond what annotations offer. No contradiction exists.

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: the first defines the resource and content, the second gives a direct usage example. No filler or redundancy. Front-loaded with the core purpose.

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?

The tool is simple with a single parameter and no output schema. The description explains what data is returned and provides a usage example, covering the essentials. It could mention whether a group is required, but given low complexity, it is sufficiently complete.

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 0% for the 'group' parameter, so the description must compensate. It gives an example ('grupo C') implying the parameter is a group identifier, but does not specify format, allowed values, or whether it's optional. This is marginal but better than nothing, hence a 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 the tool returns group standings (classificação) with specific fields (points, games, wins, draws, losses, goal difference). It also provides an example query ('como está a tabela do grupo C') that clarifies the resource. This distinguishes it from siblings like worldcup_groups or worldcup_matches, making the purpose 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 explicitly says 'Use para ...' with an example, giving a clear when-to-use context. It does not mention when not to use or name alternative tools, but the example strongly implies usage for group standings queries. Given the sibling set, this is adequate 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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful domain context—48 teams, FIFA ranking, confederation—and the parameter-dependent behavior of returning a specific profile. It does not describe output format or edge cases, but for a simple read-only list tool this is acceptable.

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, front-loads the primary function, and contains no filler. Every word serves a purpose, and the parameter hint is placed clearly.

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 two-optional-parameter read-only tool with good annotations, the description is nearly sufficient. Missing details are the behavior of the `confederation` parameter, what happens when no parameters are provided, and output shape. Since there is no output schema, a bit more guidance would improve completeness.

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 0%, so the description carries the burden. It explains `team` ('perfil de uma seleção específica') but leaves `confederation` completely unexplained. This is a partial compensation: one parameter gains meaning, but the other still relies on the agent's inference from the property name.

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's purpose: it lists the 48 participating World Cup teams with FIFA ranking and confederation, and can provide a profile for a specific team via the `team` parameter. It is distinct enough from sibling tools like worldcup_matches or worldcup_groups, though it does not state an explicit verb like 'list' or 'get'.

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 implied rather than explicit: 'Passe team para o perfil de uma seleção específica' indicates when to use the team parameter. However, there is no guidance about when to prefer this tool over alternatives, nor any mention of what the `confederation` parameter is for.

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 the tool as read-only, idempotent, and non-destructive, so the description does not need to repeat that. It adds some useful context by noting the scope of the 16 stadiums in the US, Mexico, and Canada and the fields city, capacity, and matches. Still, it does not describe filter semantics when both parameters are passed or how invalid values are handled.

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, compact sentence that front-loads the core subject, then provides filtering instructions. Every phrase adds useful information: the 16 venues, the countries involved, the relevant fields, and the optional filters. There is no unnecessary repetition or 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 that this is a read-only venue query tool with no required parameters and no output schema, the description covers the important return content: city, capacity, and matches per venue. It is probably enough for an agent to decide whether and how to call the tool. Minor gaps remain around exact output shape and filtering edge cases, but the overall context is adequate.

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 includes only `city` and `venue` without descriptions, so the description adds value by saying these are filters. However, it stops short of explaining accepted value formats, whether the filters are exclusive or combinable, or whether partial names are valid. This is enough to imply usage but not enough to fully compensate for the lack of schema documentation.

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 as World Cup host stadiums and says the data includes city, capacity, and each venue's matches. It distinguishes this tool from siblings like worldcup_teams and worldcup_matches by focusing on venues. However, it lacks an explicit operative verb such as 'lists' or 'returns,' so it stops short of the highest clarity standard.

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 tells the user to pass `city` or `venue` to filter, which gives practical guidance for using the filter parameters. It does not explicitly compare this tool to sibling tools or state when to prefer it over worldcup_matches, worldcup_schedule, or worldcup_teams. Thus usage context is present but alternatives are not addressed.

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