football-docs

Server Quality Checklist

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Latest release: v0.9.1
Disambiguation5/5
Each tool has a clearly distinct purpose: listing providers, searching docs, comparing providers, resolving entities and IDs, retrieving provider docs, and requesting updates. No overlap in functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., list_providers, resolve_entity, search_docs), making them predictable.
Tool Count5/5
With 7 tools, the set is well-scoped for the domain of football data documentation, covering all essential operations without being excessive.
Completeness5/5
The tool surface covers listing, searching, comparing, resolving entities and provider IDs, and updating docs. No obvious gaps for the intended use case of exploring football data providers.
Average 4.2/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 112 commits in the last 12 weeks
- Last stable release on August 11, 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.
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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 indicate readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. The description adds 'provenance-bearing docs' implying reliability, but doesn't expand on behavior like error handling or data format.
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: one for core function, one for usage context. No wasted words. Front-loaded with the action and resource.
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 covers purpose, usage order, and filtering. No output schema exists, but the description doesn't explain return format. However, for a straightforward retrieval tool with good annotations, it is largely complete.
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 descriptions for each parameter. The description reiterates filtering options (topic, category) and emphasizes 'resolved provider,' adding context but not compensating for low coverage since coverage is already high.
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 'retrieve' and resource 'provider docs', specifying filtering by topic or category. It distinguishes from siblings by mentioning 'resolved provider' and referencing resolve_provider_id as a prerequisite.
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 'Use after resolve_provider_id when you know which provider to inspect and want provenance-bearing docs.' This gives a clear usage context and prerequisite. It does not explicitly state when not to use, but the context is sufficient.
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 and destructiveHint=false, so safety is covered. The description adds that it returns 'most relevant documentation chunks,' implying ranking but not elaborating on how results are ordered or paginated.
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 concise (three sentences), front-loaded with the main purpose, and each sentence adds value 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 covers the tool's purpose, scope (football data provider docs), and output (chunks). It is adequate given the presence of annotations and full schema, though it could mention that search spans all indexed providers.
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 detailed parameter descriptions including examples. The tool description does not add further meaning beyond the schema, so baseline 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 clearly states it searches 'football data provider documentation' and lists specific use cases (event types, qualifier IDs, etc.). This distinguishes it from sibling tools like get_provider_docs (retrieval) and list_providers (listing).
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 'Use for finding...' which provides clear when-to-use context. However, it does not mention when not to use it or point to alternative sibling tools like get_provider_docs for full documentation access.
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 (readOnlyHint=true, destructiveHint=false) indicate safe read operation. The description adds context by specifying 'compare' and 'specific data type or concept', aligning with annotations. No behavioral traits like response format or limitations are disclosed, but annotations cover safety.
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 an example, no wasted words. Efficiently communicates purpose and usage.
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?
The tool has 2 parameters and no output schema. The description is minimal and lacks any mention of return format or behavior, which is a notable gap given no output schema. It is adequate but not fully complete.
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 descriptions for both parameters (topic and providers) including examples. The description's example ('shot events') adds minimal extra meaning; baseline 3 is appropriate as schema does the heavy lifting.
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 compares providers for a specific data type/concept, with an example. The name 'compare_providers' aligns with this purpose, and it is distinct from sibling tools like list_providers and get_provider_docs.
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 implies usage for comparing representations across providers via an example, but lacks explicit when-to-use or when-not-to-use guidance, such as mention of alternative tools like search_docs for finding docs. It is clear but not exhaustive.
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 indicate non-read-only and non-destructive. Description adds that it's a queued request, not an immediate modification, which is crucial behavioral context. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each purposeful: states action, gives usage context, and adds behavioral note. No unnecessary words, front-loaded with key information.
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 simplicity (4 params, no output schema), the description covers purpose, usage scenarios, and queuing behavior. Lacks detail on return value or confirmation, but sufficient for agent decision-making.
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?
Input schema has 100% coverage with clear descriptions for each parameter. The description does not add new parameter information beyond what the schema provides, meeting baseline but not exceeding.
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 'Request' and the resource 'provider's documentation', specifying actions (add, update, recrawl). It distinguishes from sibling tools like get_provider_docs or search_docs which are read-only.
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?
Explicitly states when to use: 'when you notice docs are outdated, a provider is missing, or you know of a better documentation source.' It also notes requests are queued, implying delayed action. Missing explicit when-not-to-use or alternatives among 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 declare readOnlyHint, openWorldHint, and destructiveHint. The description adds value by mentioning fuzzy match on name and aliases, and cross-provider resolution. It does not contradict 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 core purpose, followed by usage example. Every word contributes meaning. No fluff.
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 mentions the result (cross-provider IDs) and entity types. It lacks details on return format or pagination, but the complexity is moderate and annotations fill 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 tool description reiterates the purpose of name and provider but does not add significant 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 the verb ('resolve'), resource ('football entity'), and outcome ('cross-provider IDs'). It distinguishes from siblings by specifying the mapping use case and listing providers.
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 states when to use: 'when you need to map between...' and 'when you need to look up...'. It does not provide explicit exclusion scenarios or directly reference alternatives like compare_providers, but the context is clear enough.
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 and destructiveHint=false, so the description's additional behavioral context is minimal. It adds that resolution maps to a canonical key, which is consistent. No contradictions, but no extra behavioral details like error handling or idempotency.
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 states the action concisely, second lists usage examples. No wasted words. Front-loaded with the core purpose.
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 (one param, no output schema, read-only), the description fully covers what an agent needs: purpose, when to use, and input examples. No gaps.
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% and the schema description already defines the query parameter. The tool description adds concrete examples (e.g., Stats Perform, Opta F24) that help clarify acceptable input values, enhancing semantic understanding 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 the tool's purpose: resolving a provider name/alias to a canonical key. It specifies the verb 'resolve', the resource (provider name to key), and lists numerous examples, leaving no ambiguity.
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?
Explicitly says 'Use when users mention brands, vendors, products, or aliases' with specific examples. Implies it's a preprocessing step for searching. Lacks explicit exclusion criteria but provides clear guidance on when to invoke.
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 and destructiveHint=false, so the agent knows this is a safe read operation. Description adds that it lists providers and their metadata, which is consistent and sufficient. No additional behavioral traits needed beyond what's disclosed.
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, both front-loaded with purpose and usage. Every word earns its place with no redundancy or filler. Highly efficient.
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 zero parameters, no output schema, and a simple list operation, the description fully covers what the tool does and how to use it. No gaps remain.
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?
No parameters defined (0 params), so baseline is 4 per scoring guidelines. Description does not need to add param info since schema coverage is 100% and there is nothing to describe.
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 uses specific verb 'List' and clearly identifies resource as 'all indexed football data providers' with included attributes (document count, coverage categories). This distinguishes it from sibling tools like search_docs and get_provider_docs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use to understand what documentation is available. Call this first to see what providers are indexed before searching.' This provides clear context and implies alternatives (e.g., search_docs for searching).
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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