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 mentions the source (GitHub) and that personas are free, but fails to disclose key behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, pagination, or what the output format looks like. For a tool with no annotations, 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 that conveys the core purpose without unnecessary details. It is front-loaded and wastes no words, though it could benefit from slightly more structure (e.g., separating key points) for clarity.

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 lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., list of personas, details), behavioral constraints, or how it integrates with sibling tools. For a tool with one parameter and no structured output, 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.

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

The schema description coverage is 100%, with the parameter 'category' fully documented in the schema. The description does not add any additional meaning or examples beyond what the schema provides (e.g., how categories affect browsing). Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

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 ('browse') and resource ('community persona collection'), specifying that it's free personas shared on GitHub. It distinguishes from siblings like 'list_personas' by focusing on community rather than local personas, though not explicitly. However, it could be more specific about what 'browse' entails (e.g., searching or viewing).

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?

No explicit guidance on when to use this tool versus alternatives like 'list_personas' or 'suggest_persona'. The description implies usage for exploring community personas, but lacks context on prerequisites, exclusions, or comparisons with sibling tools, leaving the agent to infer usage scenarios.

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 mentions sequential execution and step-by-step processing but doesn't describe what happens during execution (e.g., error handling, state persistence between personas, performance characteristics, or authentication requirements). This leaves significant gaps for a tool that appears to orchestrate multiple operations.

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 communicates the core concept without unnecessary words. It's appropriately sized for what it does cover, though it could be more informative.

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 orchestrating multiple personas, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how errors are handled, or what 'step-by-step processing' entails in practical terms, leaving the agent with inadequate information for proper 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 schema has 100% description coverage, so the parameters are well-documented in the structured schema. The description doesn't add any meaningful information about parameter usage beyond what's already in the schema descriptions, maintaining the baseline score of 3.

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 executes multiple personas sequentially for step-by-step processing, which provides a basic purpose. However, it's somewhat vague about what '페르소나' (personas) are in this context and doesn't distinguish this tool from sibling tools like 'create_persona' or 'update_persona' that also involve personas.

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. It doesn't mention prerequisites, appropriate scenarios, or how it differs from other persona-related tools like 'suggest_persona' or 'list_personas'.

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. While '생성합니다' (creates) implies a write/mutation operation, there's no information about permissions needed, whether creation is idempotent, what happens on duplicate names, or what the response contains. For a creation tool with zero annotation coverage, this is insufficient.

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 states the core functionality without any wasted words. It's appropriately sized for a simple creation 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 creation tool with no annotations and no output schema, the description is too minimal. It doesn't address what happens after creation, whether there are validation rules, how the created persona can be used, or any error conditions. Given the complexity of persona management and the existence of multiple sibling tools, more context would be helpful.

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?

Schema description coverage is 100%, so both parameters are well-documented in the schema itself. The description doesn't add any additional meaning about the parameters beyond what's already in the schema descriptions. This meets the baseline expectation when schema does the heavy lifting.

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 ('새로운...생성합니다' - creates new) and resource ('페르소나 프로필' - persona profile), making the purpose immediately understandable. It doesn't distinguish from siblings like 'update_persona' or 'install_community_persona', but the verb+resource combination is specific enough for basic understanding.

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?

No guidance is provided about when to use this tool versus alternatives like 'update_persona', 'install_community_persona', or 'chain_personas'. The description simply states what the tool does without context about appropriate use cases or prerequisites for creating a persona.

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 deletes a persona profile, implying a destructive mutation, but doesn't cover critical aspects like whether deletion is permanent, requires specific permissions, has side effects, or what happens to associated data. This leaves significant gaps for a mutation tool.

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 purpose with zero 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 complexity as a destructive mutation with no annotations, no output schema, and incomplete behavioral disclosure, the description is inadequate. It fails to address key contextual elements like deletion permanence, error conditions, or return values, leaving the agent with insufficient information for safe and effective 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 schema description coverage is 100%, with the single parameter 'name' documented as '삭제할 페르소나 이름' (name of the persona to delete). The description adds no additional meaning beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.

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 ('삭제합니다' - deletes) and the resource ('페르소나 프로필' - persona profile), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'update_persona' or 'chain_personas' in terms of scope or effect, 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?

No guidance is provided on when to use this tool versus alternatives like 'update_persona' or 'list_personas', nor does it mention prerequisites or consequences. The description merely states what it does without contextual usage instructions.

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. It mentions 'local data only', which adds some context about data scope, but doesn't disclose other behavioral traits like whether it's read-only (implied by '조회합니다' but not explicit), performance characteristics, error conditions, or return format. For a tool with zero annotation coverage, this is insufficient.

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 Korean sentence with a brief parenthetical clarification. Every word earns its place by stating the action and a key constraint. It's front-loaded with the main purpose and efficiently structured.

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 (analytics tool with no output schema and no annotations), the description is incomplete. It doesn't explain what statistics are returned, the format of the data, or any behavioral expectations beyond the local data scope. For a tool that presumably returns structured analytics data, this leaves significant gaps 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 tool has 0 parameters, and schema description coverage is 100% (though empty). The description doesn't need to compensate for missing parameter documentation. It appropriately doesn't discuss parameters, so a baseline of 4 is warranted as it doesn't add or detract from parameter understanding.

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 verb ('조회합니다' - retrieves/checks) and resource ('페르소나 사용 통계' - persona usage statistics), making the purpose understandable. It distinguishes itself from siblings by focusing on analytics rather than creation, deletion, or listing of personas. However, it doesn't explicitly differentiate from potential analytics siblings that might exist in other contexts.

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 with the parenthetical '(로컬 데이터만)' - 'local data only', which implies a scope limitation. However, it doesn't specify when to use this tool versus alternatives like 'list_personas' for basic listing or other potential analytics tools. No explicit when-not-to-use or alternative tool references are provided.

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 but offers minimal behavioral insight. It mentions installation into a local collection, hinting at a write operation, but lacks details on permissions, side effects, error conditions, or what 'installation' entails (e.g., copying, linking, or modifying).

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 purpose without redundancy. It's appropriately sized and front-loaded, with no wasted words.

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 tool with no annotations, no output schema, and a write-like operation ('install'), the description is incomplete. It lacks information on what happens after installation, potential conflicts, or how this tool interacts with siblings like 'create_persona' or 'list_personas'.

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?

Schema description coverage is 100%, with the single parameter 'name' documented as 'name of the community persona to install'. The description adds no additional parameter semantics beyond this, so it meets the baseline for high schema coverage without compensating value.

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 ('install') and target resource ('community persona'), specifying it's installed 'into the local collection'. However, it doesn't distinguish this from sibling tools like 'create_persona' or 'update_persona', 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?

No guidance is provided on when to use this tool versus alternatives like 'create_persona' or 'browse_community'. The description implies installation from a community source, but it doesn't specify prerequisites, exclusions, or contextual triggers for selection.

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. While '조회합니다' implies a read operation, it doesn't specify whether this requires authentication, what format the list returns, whether there's pagination, or any rate limits. The description provides minimal behavioral context beyond the basic 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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized for a simple listing 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 listing tool with no output schema, the description provides the basic purpose but lacks important context. It doesn't describe what information is returned about each persona, whether the list is filtered or complete, or how this differs from similar tools. The absence of annotations means the description should do more to explain behavioral aspects.

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 baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the empty input schema is self-explanatory for a simple listing operation.

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 ('조회합니다' - retrieves/views) and resource ('사용 가능한 모든 페르소나 목록' - list of all available personas). It distinguishes from siblings like create_persona or delete_persona by being a read operation. However, it doesn't explicitly differentiate from similar listing tools like browse_community or suggest_persona.

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?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention when this tool should be used instead of browse_community or suggest_persona, nor does it provide any context about prerequisites or appropriate situations for its use.

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. It mentions 'triggered activation only,' which hints at conditional behavior, but doesn't disclose other traits like whether it's read-only, what happens on failure, or if there are rate limits. This leaves significant gaps for a tool that analyzes and suggests.

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 purpose and a key behavioral note. It's front-loaded with the main action and avoids unnecessary words, making it highly concise and well-structured.

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 (analyzing context to suggest personas) and lack of annotations or output schema, the description is insufficient. It doesn't explain what a 'persona' entails, how suggestions are generated, or what the output looks like, leaving the agent with incomplete guidance.

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 input schema has 100% description coverage, with the 'context' parameter documented as 'conversation context or question content to analyze.' The description adds no additional parameter details beyond this, so it meets the baseline of 3 without compensating further.

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: analyzing conversation context to suggest suitable personas. It specifies the action ('analyze' and 'suggest') and resource ('personas'), though it doesn't explicitly differentiate from siblings like 'list_personas' or 'create_persona'.

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 some usage context by mentioning 'triggered activation only,' implying this tool should be used when a specific trigger condition is met. However, it doesn't specify what triggers it or when to use alternatives like 'list_personas' for browsing or 'create_persona' for manual creation.

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. While '수정합니다' implies a mutation operation, it doesn't specify whether this requires specific permissions, what happens to unchanged fields, if changes are reversible, or any rate limits. For a mutation 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 with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration. Every word earns its place, making it highly concise and well-structured.

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 mutation tool with no annotations and no output schema, the description is incomplete. It lacks crucial context such as behavioral traits (e.g., permissions, side effects), usage guidelines, and output expectations. The high schema coverage doesn't compensate for these gaps in a tool that modifies 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?

Schema description coverage is 100%, meaning the input schema already fully documents both parameters ('name' and 'content'). The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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 ('수정합니다' - modifies/updates) and the resource ('기존 페르소나 프로필' - existing persona profile), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'create_persona' or 'delete_persona' beyond the 'existing' qualifier, which is why it doesn't reach a perfect 5.

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. It doesn't mention prerequisites (e.g., needing an existing persona), exclusions, or comparisons to siblings like 'create_persona' for new personas or 'delete_persona' for removal. This leaves 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.