MCP Make Sound
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation2/5
The tool set has significant ambiguity, as 'play_sound' appears to be a general-purpose tool that can handle what the three specific tools (error, info, warning) do, making it unclear when to choose one over the other. This overlap could easily lead to misselection by agents, as the specific tools seem redundant given the customizable 'play_sound'.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with 'play_' as the prefix, using snake_case throughout. This predictability makes it easy for agents to parse and understand the naming conventions without confusion.
Tool Count3/5With 4 tools, the count is borderline for the server's purpose of playing sounds. It feels slightly thin, as the domain might benefit from more specific or varied sound operations, but it's not extreme. The tools cover basic sound types, though the overlap reduces the effective utility of having four separate tools.
Completeness3/5The tool set covers basic sound playback for error, info, warning, and customizable sounds, which aligns with the server's name 'Make Sound'. However, there are notable gaps, such as missing operations like listing available sounds, stopping sounds, or adjusting volume, which could limit agent workflows in more complex scenarios.
Average 3/5 across 4 of 4 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'customizable parameters' but fails to explain key traits like whether playback is blocking or non-blocking, error handling (e.g., if a file path is invalid), or system dependencies (e.g., TTS availability). 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('play various types of sounds'). It avoids redundancy but could be more structured by explicitly mentioning the parameter types (e.g., system, TTS, file) to enhance clarity without adding unnecessary length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of handling multiple sound types (system, TTS, file) with no annotations or output schema, the description is incomplete. It lacks details on behavioral aspects like playback effects, error responses, or how outputs are handled, making it insufficient for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear details for all parameters, including enums and requirements. The description adds minimal value beyond this, as it only vaguely references 'customizable parameters' without elaborating on their semantics or interactions, aligning with the baseline score for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'play[s] various types of sounds with customizable parameters', which clarifies the action (play) and resource (sounds) but is vague about scope and differentiation. It does not specify what 'various types' means or how it differs from sibling tools like play_error_sound, leaving room for ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the sibling tools (play_error_sound, play_info_sound, play_warning_sound). The description implies general sound playback but offers no context for choosing between this and more specific tools, leading to potential misuse.
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 action ('Play') but doesn't describe what happens—e.g., whether it's audible, requires permissions, has side effects, or how it interacts with the system. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, achieving maximum clarity in minimal space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given 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), the description is minimal but adequate for basic understanding. However, with no annotations and no output schema, it lacks details on behavior, effects, or return values, which could be important for an agent to use it correctly in context. It's incomplete for a tool that might have auditory or system-level implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. Baseline is 4 for zero parameters, as there's nothing to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Play') and the resource ('a warning system sound'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings (play_error_sound, play_info_sound, play_sound) beyond specifying 'warning' versus other sound types, which is somewhat implicit but not explicit about distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 its siblings or alternatives. It implies usage for warning scenarios but doesn't specify contexts, exclusions, or comparisons with other sound-playing tools, leaving the agent to infer based on the name 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 of behavioral disclosure. It states the action ('Play') but doesn't describe what 'Play' entails (e.g., audio output, duration, system requirements) or any side effects (e.g., interruptions, permissions needed). 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.
Conciseness5/5Is 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 any wasted words. It's front-loaded and appropriately sized for a simple tool, 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.
Completeness3/5Given 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 minimally adequate. It states what the tool does but lacks details on behavioral context (e.g., how the sound is played, any system dependencies). For such a straightforward tool, this is acceptable but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 mention parameters, which is correct for a parameterless tool, earning a high baseline score for not adding unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Play') and resource ('error system sound'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'play_warning_sound' or 'play_info_sound' beyond the 'error' qualifier, which is why it doesn't 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 Guidelines2/5Does 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 'play_warning_sound' or 'play_sound'. It lacks explicit context, exclusions, or comparisons to sibling tools, leaving the agent to infer usage based on the 'error' keyword 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 full burden for behavioral disclosure. It states the action ('play') but doesn't describe what happens when invoked (e.g., audible output, system behavior, permissions needed, or side effects). This leaves significant gaps for 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.
Conciseness5/5Is 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 any wasted words. It's appropriately sized for a simple, parameterless tool and is front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with no output schema, the description adequately covers the basic purpose. However, it lacks behavioral context (e.g., what 'play' entails, system requirements, or error conditions) that would be helpful given the absence of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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, maintaining focus on the tool's purpose without unnecessary detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Play an informational system sound' clearly states the action (play) and resource (informational system sound). It distinguishes from sibling tools like 'play_error_sound' and 'play_warning_sound' by specifying the type of sound, though it doesn't explicitly differentiate from the generic 'play_sound' tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'play_error_sound', 'play_warning_sound', or 'play_sound'. It doesn't specify appropriate contexts, exclusions, or prerequisites for usage.
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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