wc26-mcp

Server Quality Checklist

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Latest release: v0.3.1
Disambiguation5/5
Each tool targets a distinct aspect of World Cup 2026 information (e.g., teams, venues, matches, news, odds), with no overlap in purpose. The descriptions clearly differentiate them, making it easy for an agent to select the correct tool.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using underscores (e.g., get_matches, compare_teams, what_to_know_now). The naming is uniform and predictable throughout the set.
Tool Count4/5
18 tools is slightly above the ideal range but still reasonable for a comprehensive World Cup information server. Each tool serves a specific function, and none feel redundant.
Completeness5/5
The tool set covers the full spectrum of World Cup 2026 information: teams, groups, schedule, matches, bracket, venues, fan zones, city guides, visa info, odds, news, injuries, historical data, and a temporal briefing. No obvious gaps exist for the domain.
Average 4.2/5 across 18 of 18 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 2 community issues answered or closed in the last 6 months
- 80 commits in the last 12 weeks
- Last stable release on March 1, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true. The description adds context about the data shown (round path, venues, dates) but does not elaborate on other behaviors like data recency or mock data. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler. First sentence states core purpose; second adds details and optional filtering. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple visualization tool with one optional parameter and no output schema, the description is nearly complete. It covers what the tool does and what it shows. Lacks only a note on return format, but that is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a well-documented round parameter. The description's mention of 'Optionally filter by a specific round' adds marginal value beyond the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Visualize' and clearly identifies the resource as 'FIFA World Cup 2026 knockout bracket'. It details the content shown (full path, group positions, venues, dates) and distinguishes itself from siblings like get_matches or get_groups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for viewing the bracket structure but does not provide explicit when-to-use or when-not-to-use guidance. No alternatives mentioned despite 17 sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds value by noting the tool checks for a scheduled 2026 match. However, it does not disclose other behavioral traits such as rate limits, required permissions, or potential data freshness issues. With annotations covering safety, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no wasted words. It front-loads the purpose and outputs, then provides usage examples, and finally mentions a specific feature. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately explains return values (meetings, stats, narrative). Parameter usage is well-covered. However, it lacks guidance on interpreting aggregate stats or narrative summary format. Given the tool's moderate complexity, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with descriptions for both required parameters. The description adds value by clarifying accepted formats (team ID or FIFA code, with examples like 'bra', 'ARG', 'england') and noting case-insensitivity, which aids correct parameter construction.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves head-to-head World Cup history between two teams, specifying return elements (tournament meetings, aggregate stats, narrative summary). It also mentions a special feature of checking for a scheduled 2026 match. This distinguishes it from siblings like compare_teams or get_team_profile by focusing on historical matchups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives (e.g., compare_teams). It implies usage for historical head-to-head data but lacks when-not or exclusion criteria. No alternatives are named or contrasted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds value beyond readOnlyHint annotation by detailing return payload (venue details, capacity, hours, etc.) and filtering behavior. Does not contradict annotations. Transparent about scope and limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with core purpose, followed by key return fields and filter options. No wasted words, though could be slightly more structured (e.g., bullet list). Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description fully compensates by listing return details (venue, capacity, hours, etc.) and all three optional filter parameters. Covers what the tool returns and how to use it, complete for a read tool with good annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description adds minor semantic detail (city case-insensitivity, venue_id returns fan zones for that stadium's city) but mostly restates schema. Adequate but not richly informative.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns 'Official FIFA Fan Festival and fan zone locations' with specific details. Verb 'Get' + resource 'Fan Zones' is precise and distinguishes from siblings like get_nearby_venues which cover different venue types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives guidance. The description implies usage for retrieving fan zone information but does not mention when not to use or compare with siblings. Adequate but missing exclusion context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the description correctly adds behavioral context like 'returns enriched match data' and timezone conversion, without contradiction. It does not detail other aspects (rate limits, auth) but that is acceptable given readOnlyHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-load the purpose, then list filters and return details. No redundancy or fluff; every sentence adds value. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main filtering, return content, and timezone option. However, it omits default behavior (all matches? limited?), output structure, and pagination. Mostly complete for typical use, but lacks a few details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter has a description. The tool description summarizes filters and mentions timezone conversion, but adds minimal new meaning beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Query FIFA World Cup 2026 matches' with specific filters (date, team, group, etc.) and return content (enriched match data, venue details, timezone conversion). It clearly distinguishes from siblings like get_schedule or get_teams by specifying the resource and output detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists available filters and output, but does not explicitly state when to use this tool versus alternatives (e.g., get_schedule for a simple list, get_standings for table). Lacks 'when to use' or 'when not to use' guidance, relying on implied context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description is not required to repeat that. The description adds value by specifying that the tool returns 'full venue details including capacity, coordinates, and notable events', which provides behavioral context 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, first sentence states the core purpose, second gives details on filtering and output. Every word earns its place with no redundancy. Front-loaded with the action verb 'Query'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple query tool with 3 optional parameters and no output schema, the description provides sufficient information about what the tool does and returns. However, it could be enhanced by mentioning how to choose between this and 'get_nearby_venues' for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with full descriptions for each parameter. The description does not add new meaning to the parameters beyond summarizing the filter options. Baseline score of 3 is appropriate as the schema already documents the parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Query', the resource 'venues', and specifies the context 'FIFA World Cup 2026'. It also lists the filter dimensions (country, city, region) and the output fields (capacity, coordinates, notable events). This distinguishes it from siblings like 'get_nearby_venues' which likely focuses on proximity-based queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for querying venues with optional filters, but it does not explicitly state when to use this tool versus alternatives like 'get_nearby_venues' or 'get_fan_zones'. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true, so the bar is lower. The description adds behavioral context: odds are 'illustrative' and 'aggregated from major bookmakers', implying they are not real-time and represent a composite. This adds value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the tool's main purpose, followed by a concise list of categories. No unnecessary words, and each sentence contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should at least hint at the return structure (e.g., list of odds entries). It mentions 'illustrative odds' but doesn't specify format or whether it's a single object or array. For a simple 2-param tool, it's adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning by linking the 'group' parameter to 'group-by-group predictions' and enumerating category values in context. This helps the agent understand the relationship between parameters and the tool's categories.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns FIFA World Cup 2026 betting odds and predictions, listing specific categories like winner, golden boot, groups, and dark horses. It is unique among sibling tools, which focus on teams, matches, schedules, etc., so no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining betting odds and predictions but does not explicitly state when to use this tool over alternatives like get_standings or get_matches. No when-not-to-use guidance or alternative tool references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the tool is read-only. The description adds context about the event (FIFA World Cup 2026) and scope (48 teams), which is useful. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the core purpose. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with optional filters and no output schema, the description provides sufficient context (event, scope, filters) to understand usage. It could mention expected output format briefly, but it's not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes both parameters. The description merely restates that filtering by team or status is possible, adding no new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it tracks player injuries for the FIFA World Cup 2026, using specific verbs 'track' and 'filter'. It distinguishes from sibling tools like get_teams or get_standings by focusing on injury data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates filtering by team or status, making the tool's purpose clear. However, it does not explicitly state when to use this tool versus alternatives, though the context of injury tracking is specific enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the readOnlyHint annotation by explaining that the tool returns matches organized by date, includes team names, venues, kick-off times in UTC and local venue time, and supports timezone conversion. No contradictions 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core purpose in the first sentence. Every sentence provides essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the output structure (daily matches with team names, venues, times in UTC and local) without needing an output schema. It covers optional parameters and default behavior. Minor missing details like empty responses for no matches are not critical for a schedule tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are documented. The description adds value by explaining that filtering by date range selects a subset of the full schedule and that the timezone parameter converts match times. This clarifies the effect of parameters beyond their schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the full FIFA World Cup 2026 schedule organized by date. It specifies that each day includes all matches with details, distinguishing it from sibling tools like get_matches (individual match details) or get_bracket (tournament bracket).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions optional date range filtering and timezone conversion, implying when to use these features. However, it does not explicitly state when not to use this tool or suggest alternatives, such as using get_matches for specific match details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so behavioral safety is clear. The description adds that before the tournament starts it returns pre-tournament strength ratings, but does not specify what happens during or after the tournament, nor does it mention data freshness or update frequency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences tightly packed with all essential information: purpose, behavior before tournament, filtering options, and group range. No wasted words, and key details are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains what is returned (power rankings/strength ratings) and the basis (FIFA rankings, betting odds, predictions). It covers the main use case but does not detail the structure of the output (e.g., list of teams with numeric scores).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing a baseline of 3. The description adds value by specifying that groups are A-L and that omitting the parameter returns all 12 groups, as well as explaining that results include ratings based on FIFA rankings, betting odds, and predictions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and resource 'standings' (group power rankings) for the FIFA World Cup 2026. It distinguishes itself from sibling tools like 'get_groups' by specifying it returns rankings rather than just group information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the tool can filter by group (A-L) or return all 12 groups, providing clear context for when to use the optional parameter. However, it does not explicitly contrast with siblings like 'compare_teams' or 'get_historical_matchups', which could also involve ranking data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so description carries lower burden. It adds behavioral context by specifying output details (FIFA ranking, flag emoji) and available filters, consistent with a read-only query.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two front-loaded sentences with no wasted text. First sentence states purpose, second lists filters and output, making it efficient and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 optional params and no output schema, the description adequately conveys filters and output fields. It does not explicitly mention return format (e.g., list vs. single object), but the context implies a list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; description adds no new semantic meaning beyond listing the filters in natural language, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries FIFA World Cup 2026 teams, specifies resources (teams) and verb (query), lists filter criteria, and mentions returned details. It distinguishes from siblings like get_team_profile by focusing on list queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for when to use the tool (query teams with filters), but does not explicitly mention when not to use it or suggest alternative tools like get_team_profile or get_groups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already include readOnlyHint: true, so the description does not need to re-state safety. It adds value by detailing that it returns teams, venues, and match schedule for each group. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose followed by optional detail. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one optional parameter, no output schema, and readOnlyHint annotation, the description is complete. It clearly states what data is returned, making it sufficient for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning by clarifying that the group parameter is for a specific letter A through L and that omitting it returns all groups. This goes beyond the schema's description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get FIFA World Cup 2026 group details' and specifies the returned data (teams, venues, match schedule). It clearly distinguishes from sibling tools like get_teams or get_matches by focusing on groups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions optional filtering 'Optionally filter to a specific group' but does not provide explicit guidance on when to use this tool versus alternatives such as get_standings or get_matches. Usage is implied but not contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the description adds value by disclosing auto-daily updates and that it returns AI-generated summaries and source links, providing behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences covering purpose, sources, frequency, filtering, and output. No unnecessary words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only news tool with 3 optional params and no output schema, the description fully covers purpose, data sources, update frequency, filtering options, and output format. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions; the description adds minimal additional detail per parameter (e.g., 'filters news mentioning this team' for team). It provides usage context but does not significantly enhance semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves FIFA World Cup 2026 news from specific sources (ESPN, BBC Sport, Reddit), with auto-update and filtering capabilities. It is distinct from sibling tools like get_matches or get_schedule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains filtering by team, category, or both, and mentions default limit. However, it does not explicitly state when to use this tool over alternatives or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description's main behavioral contribution is detailing what is returned (coach, playing style, etc.). This adds transparency beyond annotations, although no additional traits like rate limits or authorization are mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines purpose and scope, second provides usage examples. No unnecessary words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema), the description sufficiently covers purpose, usage, and return structure. The readOnly annotation is present, and the listed attributes give a complete picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for the 'team' parameter. The description adds examples ('usa', 'BRA', 'arg') and notes case-insensitivity, providing extra meaning beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'detailed profile for any FIFA World Cup 2026 team', and lists specific returned attributes (coach, playing style, etc.), distinguishing it from sibling tools like 'get_teams' which likely returns a list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives usage guidance on how to specify the team (by ID or FIFA code) but does not explicitly state when to use this tool versus alternatives like 'get_teams' or 'compare_teams'. Usage context is implied but not differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the tool is safe. The description adds that it automatically detects tournament phase, which is behavioral context. It does not detail output format, but for a briefing 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences with no fluff, front-loading the purpose and then providing optional usage details. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool (2 optional params, no output schema), the description is mostly complete. It explains the core functionality, optional overrides, and automatic detection. Could hint at return format, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters already documented. The description adds value by explaining the date parameter is for simulating different days and timezone for local times, reinforcing and extending the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides a zero-query temporal briefing for FIFA World Cup 2026, automatically detecting the current phase. It distinguishes itself from sibling tools like get_matches or get_standings by being a concise summary, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'No parameters needed — just brief me' and explains optional parameters for date simulation and timezone. It implies usage for quick overviews but does not explicitly list when not to use it or mention alternative tools, though the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and description matches a read operation. Adds behavioral context that it returns visa/ESTA/eTA requirements. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, information front-loaded. Each sentence serves a clear purpose: what the tool returns and how to use parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with 2 parameters, no output schema, read-only. Description sufficiently explains input options and output intent, leaving no ambiguity for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions; description adds value by explaining acceptable formats for 'team' (ID, FIFA code, country name) and case-insensitivity, and clarifies 'host_country' is optional filter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specifies verb 'Returns', resource 'visa/ESTA/eTA requirements', and scope ('for any team's nationals entering the three host countries'). Distinct from sibling tools like 'get_matches' or 'get_standings'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear usage context: for World Cup travelers needing entry requirements. Accepts multiple identifier types and optional filtering. Does not explicitly mention when not to use, but sibling tools cover other domains.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. Description adds context about the data returned (e.g., rankings, odds, injuries) and input flexibility, enhancing transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first covers purpose and data, second covers input flexibility. No wasted words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description lists all key data categories (rankings, odds, players, etc.), making the tool's behavior and return value clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value by noting case-insensitivity and providing specific examples (e.g., 'bra', 'ARG', 'england'), which clarifies input format beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Side-by-side comparison of any two FIFA World Cup 2026 teams' and lists specific attributes (rankings, odds, key players, etc.), distinguishing it from single-team tools like get_team_profile or focused tools like get_historical_matchups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies use for comprehensive two-team comparison but does not explicitly state when not to use it or mention alternatives among many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. Description adds behavioral detail about return content and case-insensitivity, but doesn't discuss API limits or caching. Value added beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy, front-loaded with purpose and details included efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description fully covers tool behavior with one parameter and no output schema, listing return sections and input variations, making it complete for an agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description enhances understanding by explaining that 'city' accepts venue IDs, city names, or metro areas and is case-insensitive, adding clarity beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves a travel guide for FIFA World Cup 2026 host cities, specifying return content and input formats. This is distinct from sibling tools like get_venues or get_matches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use (for any host city) and acceptable inputs, but doesn't explicitly exclude non-host cities or mention alternatives. However, context with sibling tools makes usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds that it returns distance in miles and kilometers and is sorted by distance, which is valuable behavioral context beyond what annotations provide. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with the main action first. Every sentence adds value: purpose, usage guidance, return format. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema, no nested objects), the description is fully complete. It covers purpose, usage context, return data format, and parameter details, leaving no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds further value: for 'venue', it suggests using get_venues to see all IDs; for 'limit', it adds the default value of all 15. This enriches understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it finds venues near a given World Cup venue, sorted by distance. It uses specific verb 'Find' and resource 'venues', and the phrase 'near a given World Cup venue' distinguishes it from sibling tools like get_venues that list all venues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly mentions 'useful for planning multi-match trips,' providing a clear use case. It does not, however, specify when not to use or explicitly name alternatives, but the context is clear and helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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