Promptopia MCP

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: add_multi_message_prompt and add_prompt handle different prompt creation formats, while apply_prompt, delete_prompt, get_prompt, list_prompts, and update_prompt cover specific CRUD operations. There is no overlap or ambiguity between tools.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., add_prompt, delete_prompt, list_prompts) with clear, descriptive names. The naming is uniform throughout, making it easy to understand each tool's function at a glance.
Tool Count5/5
With 7 tools, the server is well-scoped for managing prompts, covering creation (in two formats), retrieval, listing, updating, deletion, and application. This count is appropriate, providing comprehensive functionality without being overwhelming.
Completeness5/5
The tool set offers complete CRUD coverage for prompts, including both single-content and multi-message formats, along with an apply_prompt tool for variable substitution. There are no obvious gaps, enabling full lifecycle management of prompts.
Average 3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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?
No annotations are provided, so the description carries full burden. It states it 'adds a new' prompt, implying a creation/mutation operation, but doesn't disclose behavioral traits such as permissions needed, whether it's idempotent, error handling, or what happens on success (e.g., returns a prompt ID). This is a significant gap for a mutation tool with zero 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 front-loads the core action and key feature (role-based messages). There is zero waste, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a prompt ID or confirmation), error conditions, or interaction with sibling tools. Given the complexity of nested message structures and multiple siblings, more context is needed for effective use.
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%, so the schema fully documents parameters like 'name', 'description', and 'messages' with details on roles and content types. The description adds no additional meaning beyond implying role-based messages, which is already covered in the schema. Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('adds') and resource ('multi-message prompt'), specifying it creates a new prompt with role-based messages. It distinguishes from simpler 'add_prompt' by highlighting the multi-message aspect, though it doesn't explicitly contrast with all siblings like 'apply_prompt' or 'update_prompt'.
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. With siblings like 'add_prompt', 'apply_prompt', and 'update_prompt', the description lacks context on use cases, prerequisites, or distinctions, leaving the agent to infer 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?
No annotations are provided, so the description carries the full burden. It states this is an 'Adds' operation (implying creation/mutation) but doesn't disclose behavioral traits like required permissions, whether prompts are unique, error conditions, or what happens on success. The mention of 'single content format' adds minimal context about input constraints.
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 action. It could be slightly more informative but avoids unnecessary words, making it appropriately concise for a basic tool definition.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error handling, or how it interacts with sibling tools. For a mutation tool in a system with multiple prompt-related tools, more context is needed to guide effective use.
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%, so parameters are well-documented in the schema. The description adds no additional meaning about parameters beyond implying 'single content format' relates to the 'content' field, but this is vague and doesn't enhance understanding beyond the schema's details on variable formatting.
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 ('Adds') and resource ('a new prompt'), specifying it's for a 'single content format'. This distinguishes it from 'add_multi_message_prompt' which likely handles multiple messages. However, it doesn't explicitly mention what distinguishes it from 'update_prompt' or other siblings beyond format.
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 like 'add_multi_message_prompt', 'update_prompt', or 'apply_prompt'. It mentions 'single content format' but doesn't explain when that format is appropriate or what the alternatives are.
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 applies variables and returns a result, but doesn't explain critical behaviors like whether this is a read-only operation, if it modifies data, authentication needs, error handling, or rate limits. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.
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 any wasted words. It's appropriately sized and front-loaded, making it easy to grasp 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 complexity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the 'result' looks like (e.g., text output, structured data), potential side effects, or how it relates to sibling tools. For a tool that likely involves prompt execution, more context is needed to guide effective use.
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 schema description coverage is 100%, so the schema already documents both parameters ('id' and 'variables') with descriptions. The description adds no additional meaning beyond what the schema provides, such as examples of variable usage or format details. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('applies variables to a template prompt') and the outcome ('returns the result'), which is specific and understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'add_prompt' or 'update_prompt', which would require mentioning it's for executing/rendering prompts rather than managing them.
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 siblings like 'add_prompt', 'get_prompt', and 'update_prompt', it's unclear if this is for testing prompts, generating outputs, or another purpose. No context, 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.
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. While 'Deletes' implies a destructive mutation, the description doesn't specify whether this action is reversible, what permissions are required, whether it affects related data, or what happens on success/failure. For a destructive operation with zero annotation coverage, this is a significant gap.
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 - a single sentence with zero wasted words. It's front-loaded with the core action and resource. Every word earns its place, 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?
For a destructive deletion tool with no annotations and no output schema, the description is inadequate. It doesn't explain what constitutes a valid prompt ID, whether deletion is permanent, what confirmation (if any) is required, what happens to prompt versions or dependencies, or what the tool returns. Given the complexity of a deletion operation and the lack of structured metadata, the description should provide more complete context.
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 schema description coverage is 100%, with the single parameter 'id' fully documented in the schema as 'ID of the prompt to delete'. The description adds no additional parameter information beyond what's already in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
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 ('Deletes') and the resource ('a prompt by its ID'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other deletion operations that might exist in the system or explain what distinguishes deleting a prompt from other prompt operations like 'update_prompt' or 'apply_prompt'.
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 'update_prompt', 'get_prompt', and 'list_prompts', there's no indication of when deletion is appropriate versus modification or retrieval. No prerequisites, warnings, or alternative tools are mentioned.
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 updates prompts, implying mutation, but doesn't address critical aspects like required permissions, whether changes are reversible, error handling, or rate limits. The mention of format conversion adds some context, but overall, it lacks sufficient detail for a mutation tool with zero 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 that front-loads the core action and key feature (format support). There's no wasted verbiage, though it could be slightly more structured (e.g., separating purpose from usage notes). It earns its place by conveying essential information concisely.
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 (mutation with 4 parameters, nested objects in 'messages', no output schema, and no annotations), the description is inadequate. It doesn't explain return values, error cases, or behavioral nuances like how partial updates are handled. For a tool that modifies data without structured safety hints, more completeness is needed to guide the agent effectively.
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%, so the schema fully documents all parameters (id, name, description, messages). The description adds minimal value beyond this, only implying that 'messages' can handle format conversion. No additional syntax, constraints, or examples are provided, making the baseline score appropriate.
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 ('Updates') and resource ('an existing prompt'), specifying it handles both single content and multi-message formats. It distinguishes from siblings like 'add_prompt' (creation) and 'delete_prompt' (removal), though not explicitly named. However, it doesn't fully differentiate from 'add_multi_message_prompt' which might also handle multi-message formats, preventing a perfect score.
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 like 'add_prompt' for creation or 'apply_prompt' for usage. It mentions format support but doesn't specify prerequisites (e.g., needing an existing prompt ID) or exclusions (e.g., not for new prompts). This leaves the agent with minimal context for selection among siblings.
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 'Gets a prompt,' implying a read-only operation, but doesn't specify whether it requires authentication, what happens if the ID is invalid (e.g., returns an error or null), or any rate limits. 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 with zero waste: 'Gets a prompt by its ID.' It is appropriately sized and front-loaded, efficiently conveying the core purpose without unnecessary details.
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 low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context on usage, behavioral traits, or output, making it incomplete for effective agent use without additional inference or trial.
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 schema description coverage is 100%, with the single parameter 'id' fully documented in the schema as 'ID of the prompt to retrieve.' The description adds no additional meaning beyond this, such as format examples (e.g., UUID) or constraints, so it meets the baseline of 3 where the schema does the heavy lifting.
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 ('Gets') and resource ('a prompt') with a specific identifier ('by its ID'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'list_prompts' or 'apply_prompt', which would require mentioning this is for retrieving a single prompt by ID rather than listing multiple or applying one.
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 that this is for retrieving a single prompt by ID, as opposed to 'list_prompts' for multiple prompts or 'apply_prompt' for using a prompt, nor does it specify prerequisites like needing a valid prompt ID.
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 full burden but only states the action without behavioral details. It doesn't disclose whether this is a read-only operation, how results are returned (e.g., pagination, sorting), or any constraints like rate limits or authentication needs, which is inadequate for a tool with zero 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 with zero waste, front-loading the core action. It avoids redundancy and is appropriately sized for a simple list operation, making it easy for an agent 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 incomplete. It doesn't explain what 'lists' entails (e.g., format, structure, or limitations of the returned prompts), leaving gaps in understanding the tool's behavior and results for a read operation.
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 doesn't add parameter details, which is appropriate, earning a baseline score of 4 for not introducing unnecessary information.
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 ('Lists') and resource ('all available prompts'), making the purpose immediately understandable. It distinguishes from siblings like 'get_prompt' (singular) and 'add_prompt' (creation), though it could be more specific about scope or format to reach a perfect score.
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 like 'get_prompt' (for a single prompt) or 'apply_prompt' (for execution). It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from tool names alone.
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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