goodbook-mcp

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
There is significant overlap between tools like find_recipe_standards, get_cooking_guidelines, and search_food_standards, which all seem to retrieve similar types of information about recipes, guidelines, and standards. However, the descriptions provide some differentiation, such as get_food_safety_info focusing on safety/hygiene and list_sections/get_section_content being more structural. The overlapping purposes could lead to confusion when selecting the right tool for a query.
Naming Consistency4/5
The tool names follow a consistent verb_noun pattern with snake_case throughout, such as find_recipe_standards and get_cooking_guidelines. All tools start with verbs like 'find', 'get', 'list', or 'search', which is predictable and readable. There are no deviations in naming conventions, making it easy to parse the tool set at a glance.
Tool Count5/5
With 6 tools, the count is well-scoped for a server focused on food service standards and recipes. This number is neither too thin nor too heavy, allowing for a focused set of operations without overwhelming an agent. Each tool appears to serve a distinct purpose within the domain, making the count appropriate for the server's apparent scope.
Completeness4/5
The tool set covers core operations for accessing food standards, recipes, safety info, and document structure, providing good coverage for retrieval and search within the domain. However, there are minor gaps, such as no tools for updating or managing standards (e.g., create or modify operations), which might limit agents in more dynamic workflows. Overall, it supports essential querying tasks effectively.
Average 3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'finds' information, implying a read-only operation, but doesn't address critical aspects like whether it requires authentication, has rate limits, returns structured data, or handles errors. This leaves significant gaps in understanding how the tool behaves.
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 that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more informative without losing conciseness.
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?
Given the lack of annotations and output schema, the description is incomplete for a tool with two parameters. It doesn't explain what the tool returns (e.g., recipe details, preparation steps), how results are formatted, or any behavioral traits, making it inadequate for full contextual understanding.
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?
The description implies parameters related to dishes but doesn't detail them beyond 'specific dishes'. With 50% schema description coverage (one parameter documented, one not), the description adds minimal value over the schema, which already documents 'dish_name' well. It doesn't compensate for the undocumented 'cuisine_type' parameter.
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?
The description clearly states the tool's purpose with specific verbs ('find standardized recipes and preparation methods') and resources ('for specific dishes'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_food_standards' or 'get_cooking_guidelines', which might have overlapping functionality.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or specific contexts for usage, leaving the agent to infer based on tool names alone without explicit direction.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves guidelines but offers no details on permissions, rate limits, response format, or potential side effects. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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 that directly states the tool's purpose without unnecessary words. It is front-loaded and clear, though it could benefit from additional structure or bullet points if more details were included.
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?
Given the complexity (2 parameters, no output schema, no annotations), the description is incomplete. It lacks information on return values, error handling, and how parameters interact, making it insufficient for an agent to fully understand the tool's context and usage.
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 50%, with 'dish_type' documented but 'section' lacking a description. The tool description implies parameters relate to dishes or cooking methods, adding some context beyond the schema, but it doesn't fully compensate for the undocumented 'section' parameter or provide detailed semantics.
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?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('cooking guidelines and standards'), and specifies the target ('for specific dishes or cooking methods'). However, it doesn't explicitly differentiate from sibling tools like 'find_recipe_standards' or 'get_food_safety_info', which appear related but have distinct purposes.
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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'find_recipe_standards' and 'get_food_safety_info' available, there is no indication of how this tool differs in context or when it should be preferred over others, leaving usage ambiguous.
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 provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information but doesn't mention whether it's read-only, requires authentication, has rate limits, or what the output format might be. This is inadequate for a tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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?
Given the lack of annotations and output schema, the description is insufficient. It doesn't explain what the tool returns, potential errors, or behavioral traits, leaving gaps in understanding for an AI agent despite the simple parameter schema.
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?
The input schema has 100% description coverage, with the 'topic' parameter well-documented. The description adds no additional parameter details beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without extra value.
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?
The description clearly states the action ('Get') and the resource ('food safety information and hygiene standards'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'find_recipe_standards' or 'search_food_standards', which might overlap in domain.
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 such as 'find_recipe_standards' or 'search_food_standards'. The description lacks context about specific use cases or exclusions, leaving the agent to infer usage.
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 provided, the description carries the full burden of behavioral disclosure. It states the action ('Get content') but doesn't reveal any behavioral traits such as whether this is a read-only operation, potential rate limits, error conditions, or the format of returned content. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly, though it could benefit from additional context for completeness.
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?
Given the tool's complexity (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, usage guidelines, and parameter nuances, making it inadequate for an agent to fully understand how to invoke the tool correctly or interpret results, especially without an output schema to clarify return values.
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 50%, with 'section_name' documented but 'limit' lacking a description. The description adds minimal value beyond the schema by implying content retrieval but doesn't clarify parameter semantics, such as what 'section_name' refers to (e.g., exact match vs. substring) or how 'limit' affects results. It partially compensates but doesn't fully address the coverage gap.
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?
The description clearly states the verb ('Get') and resource ('content from a specific section of the food standards document'), making the purpose evident. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_sections' or 'search_food_standards', which might also retrieve content or sections, leaving some ambiguity about its unique role.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing to know the section name beforehand, or compare it to siblings like 'list_sections' for browsing sections or 'search_food_standards' for broader searches, leaving the agent without context for tool selection.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'searches' but doesn't describe what the search returns (e.g., list of results, full documents, snippets), whether it's paginated, if there are rate limits, or any authentication requirements. This leaves significant gaps for a search tool.
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 that front-loads the core purpose. It could be slightly more structured (e.g., by explicitly mentioning parameters), but it avoids redundancy and wastes no words.
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?
Given the lack of annotations, no output schema, and incomplete parameter documentation (50% coverage), the description is insufficient. It doesn't explain what the tool returns, how results are formatted, or behavioral traits like search scope or limitations, making it inadequate for a search tool with multiple sibling alternatives.
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 50% (only 'query' has a description). The description mentions 'search for specific food preparation standards, recipes, or cooking guidelines', which adds context that the 'query' parameter should target these topics, but doesn't clarify the 'section' parameter (which has an empty description in the schema). This partially compensates but doesn't fully address the coverage gap.
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?
The description clearly states the tool's purpose with specific verbs ('search for') and resources ('food preparation standards, recipes, or cooking guidelines'), and identifies the source ('food service literature'). However, it doesn't explicitly differentiate from sibling tools like 'find_recipe_standards' or 'get_cooking_guidelines', which appear to have overlapping domains.
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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'find_recipe_standards', 'get_cooking_guidelines', and 'get_food_safety_info', there's no indication of how this tool differs in scope or context, leaving the agent to guess based on tool names alone.
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 provided, the description carries the full burden of behavioral disclosure. It states the action ('List all available sections') but doesn't add context such as whether this is a read-only operation, if it requires authentication, rate limits, or what the output format might be. This leaves significant gaps in understanding the tool's behavior.
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 a single, clear sentence that efficiently conveys the tool's purpose without any wasted words. It is front-loaded and appropriately sized for a simple tool, making it easy to parse and understand quickly.
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 (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It states what the tool does but lacks behavioral context and usage guidelines, which are important even for simple tools to ensure correct invocation and integration with siblings.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose, which aligns with the baseline for zero parameters.
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?
The description clearly states the verb ('List') and resource ('sections in the food service standards document'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_section_content' or 'search_food_standards', which might also involve sections, so it doesn't fully achieve sibling distinction.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the name alone, which is insufficient for optimal tool selection.
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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