What Do They Know

Server Quality Checklist

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Latest release: v1.0.1
Disambiguation3/5
Tools are mostly distinct, but the presence of prompt-related tools (get_prompt, list_prompts) alongside FOI request tools creates ambiguity. An agent may confuse get_prompt as related to requests, and search_request_events and get_request_feed_items overlap in purpose.
Naming Consistency5/5
All tool names consistently follow the verb_noun pattern in snake_case (e.g., build_request_url, search_authorities). No mixing of styles or irregular patterns.
Tool Count5/5
8 tools is a reasonable number for an FOI request-focused server. It covers key operations without being overwhelming or too sparse.
Completeness2/5
The tool surface has significant gaps: there is no tool to directly retrieve full request details by slug, despite being referenced in descriptions. The lifecycle is incomplete without a 'get request' or 'list requests' tool.
Average 3.7/5 across 8 of 8 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 1 commit in the last 12 weeks
- Last stable release on May 7, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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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, idempotentHint, and openWorldHint, so the safety profile is clear. The description adds no additional behavioral context beyond 'build a URL', but it does not contradict annotations. Therefore, it meets the baseline given annotation coverage.
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?
The description is a single efficient sentence with no unnecessary words. While it is very short, it earns its place by stating the core function without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description does not mention what the tool returns (a URL). With 5 parameters and 0% schema description coverage, the description is far from complete; it lacks essential context for an agent to use parameters correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description provides no explanation of any parameters. The schema lists 5 parameters (authority_slug, title, default_letter, body, tags) with no semantic hints, and the description fails to add meaning such as what 'prefilled' entails or how parameters map to the URL.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool builds a prefilled request URL for WhatDoTheyKnow, specifying the verb 'build' and the resource 'prefilled request URL'. However, it does not distinguish this from sibling tools like 'create_request_record' which actually creates a record, leaving room for confusion about when to use which.
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?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention that this tool only generates a URL and does not submit a request, or that for actually creating a request one should use 'create_request_record'.
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 indicate destructive and open-world behavior. Description adds that it is 'experimental' and requires an API key, which provides extra context but not rich behavioral detail. 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?
Two concise sentences, the first stating purpose and the second a key requirement. Every word earns its place, and the purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (so return values need not be explained), the description omits parameter semantics and does not elaborate on what a 'request record' entails. For a creation tool with 4 required fields, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 4 required parameters with 0% schema description coverage. Description does not describe any parameters, leaving the agent uninformed about their semantics. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool creates a request via an experimental write API. The verb 'Create' and object 'request' are specific. It does not explicitly differentiate from siblings, but the purpose is unambiguous given the schema.
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?
Description mentions a prerequisite (WDTK_API_KEY) but provides no guidance on when to use this tool versus alternatives or when not to use it. With several sibling tools, more explicit usage context is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only mentions returning JSON with metadata but omits behavioral traits such as authentication needs, rate limits, or side effects. The tool is simple, but disclosure is minimal.
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 extremely concise: two short sentences that efficiently convey the purpose and output. No extraneous words.
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 tool's simplicity (no parameters, output schema exists), the description adequately covers the return value. However, it lacks any mention of error conditions or pagination, which might be needed for completeness.
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?
There are zero parameters, so the input schema is empty. The description adds no parameter info, but the baseline for 0 parameters is 4 according to the guidelines.
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 lists all available prompts, with a specific verb (List) and resource (prompts). It differentiates from sibling get_prompt by implying a full list rather than a single item.
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?
No guidance is provided on when to use this tool versus alternatives like get_prompt or other sibling tools. The description only states what it does, not the context or prerequisites.
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 destructive and open-world behavior. The description adds that it's experimental and requires WDTK_API_KEY, which are useful behavioral constraints 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core purpose and adding only essential authentication context. No extraneous text.
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?
Given the tool's simplicity and presence of an output schema, the description is mostly adequate but lacks parameter value hints, which limits completeness for an agent to correctly determine valid state values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should explain the parameters. It only mentions 'user-assessed state' but does not describe valid values for the 'state' parameter or the format of 'request_id'. This is insufficient for proper tool invocation.
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 updates the user-assessed state of a request, distinguishing it from sibling tools like create_request_record or build_request_url. The verb 'Update' and resource 'state of a request' are specific and unambiguous.
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 the experimental nature and API key requirement, providing some usage context. However, it offers no explicit guidance on when to use this tool versus alternatives, nor does it state 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the output is a JSON with a 'messages' array, which is useful. However, it does not disclose other behavioral traits such as idempotency, error handling for missing prompts, or performance characteristics. The name 'get' implies read-only, but it's not explicitly stated.
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 long, front-loading the purpose and then efficiently covering the return format and argument semantics. Every sentence serves a clear purpose 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?
Given the presence of an output schema, the description does not need to detail the return structure further. It covers the essential aspects: purpose, output format, and argument format. It could mention what happens if the prompt is not found, but that may be handled by the output schema. Overall, it is fairly complete for a simple retrieval 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?
The input schema already covers both parameters with descriptions. The description adds value by clarifying that 'arguments' should be a dict mapping argument names to values, which is not explicit in the schema. This helps the agent understand the expected format of the object parameter.
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 'Get a prompt by name', which is a specific verb+resource. It distinguishes itself from the sibling 'list_prompts' which lists all prompts, making it clear this retrieves a single prompt. The optional arguments are also mentioned.
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 explains that arguments should be a dict mapping names to values, but does not provide guidance on when to use this tool versus alternatives like 'list_prompts'. It implies usage through the input format but lacks explicit when-to-use or when-not-to-use advice.
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 convey readOnly, idempotent, and openWorld nature. Description adds search-specific behavior (case-insensitive, substring match, limit). No contradictions. Would benefit from mentioning result ordering or empty result handling, but adequate.
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?
Description is concise (three lines plus example), front-loaded with purpose, then behavior, then example. 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with 2 parameters, rich annotations, and an output schema, the description covers search behavior, limit, and next steps. Could mention no-result case, but overall complete enough.
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 has 0% description coverage, so description must compensate. It explains `query` as search term and `limit` as max results, but lacks details like default limit behavior or allowed input format. Basic semantics provided but not comprehensive.
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 'Search' and the resource 'WhatDoTheyKnow public authorities by name'. It specifies behavior (case-insensitive substring match), defines return limit, and distinguishes from siblings like build_request_url by indicating the slug as a next step.
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 gives clear examples and explains when to use this tool (to find authorities) and how to proceed with the slug. However, it lacks explicit guidance on when not to use it versus alternative tools, though the purpose is unambiguous.
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, idempotentHint, and openWorldHint. The description adds that it returns up to `limit` AtomEntry objects and describes the navigation flow (link field). This provides behavioral context beyond the annotations without contradiction.
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 with three paragraphs: purpose, usage guidance, and examples. Every sentence adds information; no fluff. Information is well 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 the presence of annotations and output schema, the description covers the main purpose, result shape, and follow-up steps. It lacks details on sorting or pagination, but the examples and next-step guidance make it fairly 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 0%, so description must compensate. It explains `limit` indirectly ('Returns up to limit') and gives query examples for `search_expression`. However, it does not formally define the query syntax beyond examples, leaving some ambiguity.
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 specifies the action 'search' and the resource 'WhatDoTheyKnow's feed-based event index' to find FOI requests. It distinguishes from siblings like search_authorities and get_request_feed_items (for full detail). The verb 'Search' and resource 'event index' are specific.
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 explicitly states when to call ('find FOI requests matching a query expression') and provides next steps (use link field, call get_request_feed_items for full detail). Example expressions aid usage. However, it does not explicitly state when not to use or compare directly with all 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, idempotentHint, openWorldHint. Description adds that output contains link field with URL and advises follow-up, but doesn't mention potential limitations or side effects.
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, purpose first, no fluff. 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?
Despite having output schema, description provides context on how to use returned data. Covers main purpose, alternative, and follow-up. Sibling tools are different, so no confusion.
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?
With 0% schema coverage, description implicitly explains request_slug via 'specific FOI request' but does not mention the limit parameter, leaving some gap.
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?
Clearly states the tool returns parsed Atom feed entries for a specific FOI request as structured objects, distinguishing it from raw XML resource and sibling tools like search_request_events.
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 tells when to use (over raw resource) and provides follow-up instructions (use slug for full detail), giving clear context and alternatives.
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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