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 what the tool does ('stop all audio + system mute') without disclosing behavioral traits such as whether this is reversible, requires permissions, affects other processes, or has side effects. For a potentially disruptive tool, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (one short phrase) and front-loaded with the core action, making it easy to parse. Every word earns its place by conveying essential purpose without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's potential complexity (emergency system-level audio control) and lack of annotations or output schema, the description is incomplete. It fails to address critical context like reversibility, error handling, or confirmation requirements, which are essential for safe agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately omits parameter details, earning a baseline score of 4 for not adding unnecessary information beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 ('긴급 음소거' translates to 'emergency silence') and resources ('모든 오디오 중지' means 'stop all audio' and '시스템 음소거' means 'system mute'). It distinguishes from siblings like 'stop_speech' by implying broader system-level action beyond just speech.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'stop_speech' or 'kill_all_tts'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from the 'emergency' label without clear operational boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 it 'checks' status, implying a read-only operation, but doesn't specify what 'status' includes (e.g., active/inactive, errors, performance metrics), whether it requires authentication, or if there are rate limits. For a tool with zero annotation coverage, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence in Korean: '현재 TTS 상태를 확인합니다.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple status-check tool. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on what 'status' entails or behavioral context. Without annotations or output schema, the description should ideally provide more completeness about the return value or usage context, but it's not entirely incomplete for such a simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline expectation. No additional value is required or provided beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '현재 TTS 상태를 확인합니다' translates to 'Check current TTS status.' This is a specific verb ('check') + resource ('TTS status') combination. However, it doesn't explicitly differentiate from sibling tools like 'test_tts' or 'stop_speech,' which prevents 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.

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 'test_ts' (likely for testing) and 'stop_speech' (for stopping), there's no indication of when this status check is appropriate versus those actions. No explicit when/when-not or alternative recommendations are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 performs '강제 종료' (force termination), which implies a destructive operation, but doesn't specify whether this is reversible, what side effects might occur, or what permissions are required. For a potentially destructive tool 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.

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 any unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a potentially destructive tool with no annotations and no output schema, the description is inadequate. It doesn't explain what '강제 종료' entails, whether there are confirmation steps, what happens to ongoing processes, or what the return value might be. Given the complexity implied by 'force termination' and the lack of structured documentation, more behavioral context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description doesn't need to explain any parameters, and it correctly doesn't attempt to do so. This meets the baseline expectation for a zero-parameter tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('강제 종료합니다' - force termination) and target ('모든 TTS 관련 프로세스' - all TTS-related processes). It uses specific verbs and identifies the resource being acted upon. However, it doesn't explicitly differentiate from sibling tools like 'stop_speech' or 'emergency_silence', 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.

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 'stop_speech' or 'emergency_silence'. There's no mention of prerequisites, appropriate contexts, or warnings about when not to use it. The agent must infer usage from the tool name and description alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 reads text aloud but does not describe any behavioral traits such as whether it interrupts ongoing speech, requires specific permissions, has rate limits, or what happens on invocation (e.g., does it play immediately or queue?). For a tool with no annotation coverage, this leaves significant gaps in understanding its operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—a single sentence that directly states the tool's function without any fluff. It is front-loaded and wastes no words, making it efficient for quick comprehension. Every part of the sentence earns its place by clearly conveying the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of having multiple sibling tools and no annotations or output schema, the description is incomplete. It does not address how this tool fits among alternatives, what behavioral outcomes to expect, or any error conditions. For a tool that likely involves audio output and potential system interactions, more context is needed to use it effectively without trial and error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description implies a 'text' parameter but does not add meaning beyond what the input schema provides. With 0% schema description coverage, the schema only defines 'text' as a required string without details. The description does not compensate by explaining constraints (e.g., length limits, language support) or usage context. However, with only one parameter, the baseline is higher, but it fails to enhance understanding beyond the basic schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: converting text to speech ('텍스트를 음성으로 읽어줍니다' translates to 'Reads text aloud as speech'). It specifies the verb ('read') and resource ('text'), making the purpose unambiguous. However, it does not differentiate from siblings like speak_fast or speak_slow, which offer variations on the same core function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 multiple sibling tools (e.g., speak_fast, speak_quiet, speak_short, speak_slow), there is no indication of how this default 'speak' differs in context, speed, volume, or other parameters. It lacks any mention of prerequisites, exclusions, or comparative use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions 'fast speed' which hints at performance, but doesn't cover critical aspects like whether this is a read-only operation, if it requires specific permissions, rate limits, or what happens to ongoing speech. For a TTS 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence in Korean that directly states the tool's function without any wasted 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (TTS operation with speed control), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain return values, error conditions, or how 'fast speed' is implemented, leaving the agent with insufficient context for reliable use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description implies the 'text' parameter by stating it reads text, adding meaning beyond the schema which has 0% description coverage. However, it doesn't provide details on text format, length limits, or language support. With only one parameter and low schema coverage, the description compensates adequately but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description '텍스트를 빠른 속도로 읽어줍니다' (reads text at a fast speed) clearly states the tool's function with a specific verb ('reads') and resource ('text'), plus a behavioral modifier ('fast speed'). It distinguishes from siblings like 'speak_slow' and 'speak_quiet' by specifying speed, but doesn't fully differentiate from 'speak' which might imply normal speed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'speak_slow', 'speak_quiet', or 'speak'. It mentions 'fast speed' but doesn't specify scenarios where fast speech is appropriate or when other tools should be preferred, leaving usage context entirely implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 reads text at low volume, which implies a read-only operation, but doesn't disclose other traits: whether it requires TTS to be initialized, if it queues speech or interrupts current speech, rate limits, error conditions, or what happens if no text is provided. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence in Korean that directly states the tool's function. It's front-loaded with the core action ('reads text at a low volume') and has no redundant or unnecessary words. Every part of the sentence earns its place by specifying the action and key behavioral trait (low volume).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (speech synthesis with volume control), no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks details on prerequisites (e.g., TTS status), behavioral nuances (e.g., interaction with other speech tools), error handling, and output format. The description provides a basic purpose but doesn't compensate for the missing structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions '텍스트' (text) as the input, aligning with the single parameter 'text' in the schema. Schema description coverage is 0%, so the schema provides no additional param details. The description adds basic semantics by indicating the parameter is text to be read, but doesn't specify constraints like length, language, or format. With 0% schema coverage, the description partially compensates but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '텍스트를 작은 볼륨으로 읽어줍니다' (reads text at a low volume). It specifies the verb ('reads') and resource ('text'), and distinguishes it from siblings like 'speak' (likely normal volume) and 'speak_slow'/'speak_fast' (different speech characteristics). However, it doesn't explicitly mention it's for TTS/speech synthesis, which could be inferred from sibling tools but isn't stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through '작은 볼륨으로' (at a low volume), suggesting this tool should be used when quiet speech is needed versus normal-volume alternatives. However, it doesn't explicitly state when to use this tool versus siblings like 'speak' or 'speak_slow', nor does it mention prerequisites or exclusions (e.g., whether it requires TTS to be active). The guidance is implied but not comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions '즉시' (immediately), hinting at low latency, but doesn't cover other important aspects like whether this requires audio output permissions, how errors are handled, or if it interrupts other speech. For a tool with zero annotation coverage, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence in Korean that conveys the core functionality and key constraint. It's front-loaded with the main action and includes the critical character limit without any unnecessary words. Every part of the sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is adequate but not complete. It covers the basic purpose and parameter constraint but lacks details on behavioral traits, error handling, or output format. For a simple tool, it meets minimum viability but could be more informative.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context for the single parameter 'text' by specifying it must be '짧은 텍스트' (short text) with a '100자 이하' (100 characters or less) limit. Since schema description coverage is 0% (no descriptions in the schema), this compensates well by clarifying the parameter's constraints beyond just its type, though it doesn't detail format or encoding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '짧은 텍스트를 즉시 읽어줍니다 (100자 이하)' translates to 'Reads short text immediately (100 characters or less)'. This specifies the verb ('reads'), resource ('short text'), and scope ('100 characters or less'), making it clear what the tool does. It doesn't explicitly distinguish from siblings like 'speak', 'speak_fast', etc., but the character limit provides some differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through the character limit ('100자 이하' meaning 100 characters or less), suggesting this tool is for short texts. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'speak' or 'speak_fast', nor does it mention exclusions or prerequisites. The implied context is helpful but incomplete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 reads text slowly, implying it's a read-only operation, but doesn't cover aspects like whether it requires specific permissions, how it handles errors, if it's rate-limited, or what the output format is (e.g., audio, status). The description is minimal and lacks critical behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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 is appropriately sized for a simple tool, though it could be more informative. The structure is straightforward and front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (simple text-to-speech with one parameter), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain the output (e.g., whether it plays audio, returns a status, or has side effects), error handling, or how it interacts with sibling tools. The description is too minimal to be fully helpful for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not add any meaning beyond what the input schema provides. The schema has 1 parameter ('text') with 0% description coverage, and the tool description does not explain what 'text' should contain (e.g., plain text, formatted text, length limits) or provide examples. With low schema coverage, the description fails to compensate for the lack of parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose ('텍스트를 천천히 읽어줍니다' translates to 'Reads text slowly'), which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'speak', 'speak_fast', or 'speak_quiet', leaving the distinction unclear. The purpose is understandable but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'speak', 'speak_fast', or 'speak_quiet'. There is no mention of specific contexts, exclusions, or prerequisites for using this tool over others in the sibling list. Usage is implied by the name but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 tool stops speech but doesn't describe what 'stop' means operationally (pause vs terminate, immediate vs graceful), whether it requires specific permissions, what happens to queued speech, or what response to expect. For a zero-parameter tool with no annotations, this leaves significant behavioral questions unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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 for a simple, zero-parameter tool and gets straight to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no output schema, the description provides the basic purpose but lacks important context. It doesn't explain what constitutes 'speech' in this context, whether the stop is reversible, what confirmation (if any) is provided, or how this differs from similar sibling tools. Given the tool's apparent simplicity, the description is minimally adequate but could be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty parameter set.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('중지합니다' - stops) and target ('현재 재생 중인 모든 음성' - all currently playing speech), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'emergency_silence' or 'kill_all_tts' which may have similar functions, 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal guidance - it implies usage when speech is currently playing, but offers no explicit when/when-not instructions or alternatives. There's no mention of when to use this versus similar tools like 'emergency_silence' or 'kill_all_tts', nor any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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. 'TTS 시스템 테스트' suggests a read-only diagnostic operation, but it doesn't specify whether this test is destructive (e.g., interrupts current speech), has side effects (e.g., generates audio output), requires specific permissions, or provides detailed results. The description lacks critical behavioral context for a tool in a TTS system with control siblings like 'kill_all_tts' and 'stop_speech.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise ('TTS 시스템 테스트'), which is efficient for a simple tool. However, it's under-specified rather than appropriately sized—it lacks necessary detail about what the test entails. While front-loaded, it doesn't earn its place by providing sufficient value beyond the tool name. Conciseness here borders on inadequacy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a TTS system with multiple control tools (e.g., 'kill_all_tts', 'speak'), no annotations, no output schema, and 0 parameters, the description is incomplete. It doesn't explain what the test does, what it returns, or how it interacts with other tools. For a diagnostic tool in this context, more information is needed to understand its role and outcomes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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% (though trivial since there are no parameters). The description doesn't need to add parameter semantics, as there are none to document. A baseline of 4 is appropriate for a parameterless tool, as the description cannot compensate for missing parameter info that doesn't exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'TTS 시스템 테스트' (TTS system test) is a tautology that essentially restates the tool name 'test_tts' in Korean. While it indicates this is a testing operation related to TTS, it doesn't specify what the test actually does (e.g., validates functionality, checks quality, runs diagnostics) or what resource it tests. It distinguishes minimally from siblings by focusing on testing rather than speaking or controlling TTS, but remains vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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_tts_status' (for checking status) or 'speak' (for actual TTS output). There's no indication of prerequisites, expected outcomes, or scenarios where testing is appropriate (e.g., after configuration changes, during troubleshooting). Usage is implied only by the word 'test,' which is insufficient for clear decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.