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 implies a mutation operation ('add'), but doesn't specify permissions needed, whether the addition is reversible, error conditions (e.g., if rule already in group), or rate limits. This is a significant gap for a tool that likely modifies data.

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 for a simple tool and front-loaded with the core action, 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 likely performs a mutation (adding a rule to a group), the lack of annotations and output schema means the description should do more. It doesn't explain what happens on success (e.g., confirmation message, updated group) or failure, leaving the agent with incomplete context for safe 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 schema description coverage is 100%, with clear descriptions for 'groupName' and 'ruleName' in the input schema. The description doesn't add any meaning beyond this (e.g., format examples, 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.

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

The description '将规则添加到分组' (Add rule to group) states a clear verb ('add') and resource ('rule to group'), which is better than a tautology. However, it doesn't specify what type of rule or group (e.g., filtering rules, security groups) or distinguish it from similar tools like 'removeRuleFromGroup' or 'addValueToGroup', making it somewhat 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. It doesn't mention prerequisites (e.g., the group and rule must exist), exclusions, or compare it to siblings like 'createRule' or 'removeRuleFromGroup', leaving the agent without usage context.

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 full burden. It only states the action 'add value to group' without disclosing behavioral traits like permissions needed, whether it's idempotent, error handling (e.g., if value/group doesn't exist), or side effects. 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 phrase '将值添加到分组', which is concise but under-specified—it lacks context and could be more informative. It's front-loaded but doesn't earn its place with useful details beyond the obvious. For a tool with 2 parameters and no annotations, more elaboration would be beneficial without sacrificing brevity.

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 (mutation with 2 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what happens after adding (e.g., success response, error cases), or how it interacts with sibling tools like 'getAllValues'. For a tool that modifies data, more context on behavior and outcomes 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?

Schema description coverage is 100%, with clear descriptions for both parameters ('分组名称' for groupName and '要添加的值名称' for valueName). The description adds no additional meaning beyond the schema, but with high coverage, the baseline is 3. Since there are only 2 parameters and the schema fully documents them, a score of 4 reflects adequate parameter understanding without extra description input.

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 '将值添加到分组' (add value to group) restates the tool name 'addValueToGroup' in Chinese, making it tautological. It doesn't specify what type of value or group, or what system this operates on, though the verb 'add' is clear. Compared to siblings like 'createValue' or 'removeValueFromGroup', it doesn't differentiate scope or behavior beyond the basic action.

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 on when to use this tool versus alternatives like 'createValue' (which might create a value independently) or 'removeValueFromGroup'. The description implies adding an existing value to a group, but doesn't state prerequisites (e.g., value/group must exist) or exclusions. Usage is implied from the name but not explicitly defined.

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 full burden for behavioral disclosure. '创建新分组' only indicates it's a creation operation without specifying what happens after creation, whether it requires specific permissions, if it's idempotent, what error conditions exist, or what the response contains. For a mutation tool with zero annotation coverage, this is severely inadequate.

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 - just three Chinese characters. While this could be considered under-specified rather than appropriately concise, it's front-loaded and contains no wasted words. The single phrase directly states the core function without unnecessary elaboration.

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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what a 'group' represents in this context, what happens after creation, or what the tool returns. Given the complexity implied by many sibling tools for managing groups, rules, and values, more context is needed for the agent to use this effectively.

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 'name' parameter clearly documented in Chinese. The description doesn't add any parameter information beyond what's in the schema. With complete schema coverage, the baseline score of 3 is appropriate since the schema does the heavy lifting for 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 '创建新分组' (Create new group) restates the tool name 'createGroup' with minimal elaboration. It specifies the verb 'create' and resource 'group', but doesn't distinguish it from sibling tools like 'createRule', 'createValue', or 'createValuesGroup'. The description is tautological rather than explanatory.

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, when not to use it, or how it relates to sibling tools like 'renameGroup', 'deleteGroup', or other group-related operations. There's complete absence of contextual usage information.

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. '创建新规则' only states the action without any information about permissions required, side effects, whether the creation is immediate or requires activation, error conditions, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is completely inadequate.

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 at just three Chinese characters. There's no wasted language or unnecessary elaboration. While this conciseness comes at the cost of completeness, as a standalone measure of brevity and structure, it's maximally efficient.

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 rule creation in a system with many sibling tools, no annotations, no output schema, and a minimal description, this is severely incomplete. The description fails to explain what rules are, what they control, how they relate to other entities (groups, values), or what the tool returns. It provides insufficient context for 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?

Schema description coverage is 100% with one parameter 'name' documented as '规则名称' (rule name) in the schema. The description adds no additional parameter information beyond what's already in the schema. According to the 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.

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

The description '创建新规则' (Create new rule) is a tautology that essentially restates the tool name 'createRule' in Chinese. While it indicates the tool creates rules, it doesn't specify what kind of rules, what system they belong to, or how they differ from sibling tools like 'updateRule' or 'createGroup'. The purpose is vague beyond the basic verb-object structure.

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 like 'updateRule', 'createGroup', 'addRuleToGroup', and 'deleteRule', there's no indication of prerequisites, appropriate contexts, or distinctions between creating a rule versus updating or adding to groups. This leaves the agent without direction for tool 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states '创建新的值' (Create new value), which implies a write/mutation operation but reveals nothing about permissions required, side effects, error conditions, rate limits, or what happens upon success. 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 extremely concise with just three Chinese characters ('创建新的值'), which translates to 'Create new value'. It is front-loaded with the core action and contains no unnecessary words or sentences. Every element earns its place, making it maximally efficient in terms of length.

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 that this is a mutation tool (creating a value) with no annotations and no output schema, the description is incomplete. It fails to explain what the tool returns, what happens on success or error, or how it interacts with the system context (e.g., values in groups, rules). The description does not compensate for the lack of structured data, leaving significant gaps for an AI agent to understand the tool's behavior.

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 (the 'name' parameter is documented as '值名称' or 'value name'), so the schema already provides the necessary parameter information. The description adds no additional meaning about parameters beyond what the schema provides, which meets the baseline of 3 when schema coverage is high.

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 '创建新的值' (Create new value) is a tautology that essentially restates the tool name 'createValue' in Chinese. While it indicates a creation action, it doesn't specify what type of value is being created, what resource it operates on, or how it differs from sibling tools like 'createGroup' or 'createValuesGroup'. The purpose is vague and lacks differentiation from similar tools.

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. There are multiple sibling tools that involve values (e.g., 'addValueToGroup', 'deleteValue', 'renameValue', 'updateValue', 'getAllValues'), but the description offers no context about when 'createValue' is appropriate versus these other tools, nor any prerequisites or exclusions 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 of behavioral disclosure. '创建新的值分组' (Create new value group) implies a write/mutation operation, but it doesn't disclose any behavioral traits: no information about permissions required, whether creation is idempotent, what happens on conflicts, rate limits, or what the response contains. For a mutation 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 extremely concise - a single phrase in Chinese. While this avoids waste, it's arguably under-specified rather than optimally concise. It front-loads the core action but lacks necessary detail. Given the tool's complexity (a mutation operation), more content would be justified, but what's there is structured efficiently.

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 this is a mutation tool with no annotations, no output schema, and multiple similar sibling tools, the description is incomplete. It doesn't explain what a 'value group' is, how it relates to other entities (values, rules), what happens after creation, or provide any context for proper usage. The agent would struggle to use this tool correctly without additional information.

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 no parameter information beyond what the schema provides. With 100% schema description coverage (the 'name' parameter is documented in the schema as '分组名称' - group name), the baseline is 3. The description doesn't explain what constitutes a valid 'name', provide examples, or add any semantic context, so it meets but doesn't exceed the minimum.

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 '创建新的值分组' (Create new value group) is a tautology that essentially restates the tool name 'createValuesGroup' in Chinese. It doesn't specify what a 'value group' is, what resource it operates on, or how it differs from similar sibling tools like 'createGroup' or 'createValue'. The purpose is stated but lacks differentiation and specificity.

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 sibling tools like 'createGroup', 'createValue', 'addValueToGroup', and 'addRuleToGroup', there's no indication of when this specific tool is appropriate, what prerequisites exist, or what context it operates in. This leaves the agent guessing about tool 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. '删除分组' only indicates a destructive deletion operation but reveals nothing about permissions required, whether deletion is permanent/reversible, side effects (e.g., what happens to rules/values in the group), error conditions, or rate limits. This is critically inadequate for a destructive 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.

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

The description is maximally concise with just two Chinese characters. While severely under-specified, it contains no redundant or unnecessary words. Every character directly communicates the core action, making it technically efficient despite its 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?

For a destructive deletion tool with no annotations and no output schema, the description is completely inadequate. It fails to explain what gets deleted, prerequisites, consequences, or return values. Given the complexity of group management (with many sibling tools for rules and values), this minimal description leaves critical gaps for safe and correct tool 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?

Schema description coverage is 100% with the single parameter 'groupName' documented as '分组名称' (group name). The description adds no parameter information beyond what the schema provides. Since schema coverage is high (>80%), the baseline score of 3 applies even though the description contributes zero parameter semantics.

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 '删除分组' (delete group) is a tautology that restates the tool name 'deleteGroup' in Chinese. It provides no additional specificity about what kind of group is being deleted or what resources are affected. While it clearly indicates a deletion action, it doesn't distinguish this tool from sibling tools like 'deleteRule', 'deleteValue', or 'deleteValueGroup'.

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 absolutely no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., group must exist), exclusions, or relationships to sibling tools like 'createGroup', 'renameGroup', or 'deleteValueGroup'. The agent receives no contextual help for tool 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. '删除规则' implies a destructive deletion operation, but it doesn't specify whether this is permanent, reversible, requires specific permissions, affects related resources, or has side effects. For a mutation tool with zero annotation coverage, this is a critical 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 at just two characters, but this is under-specification rather than effective brevity. It fails to convey necessary information, making it inefficient despite its short length. Every sentence should earn its place, and this single phrase doesn't.

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 (a destructive deletion operation), lack of annotations, no output schema, and rich sibling toolset, the description is completely inadequate. It doesn't explain what a 'rule' is, the consequences of deletion, or how it fits within the broader system, leaving critical 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?

Schema description coverage is 100%, with the single parameter 'ruleName' documented as '要删除的规则名称' (the name of the rule to delete). The description adds no additional meaning beyond what the schema provides, such as format constraints or examples. 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 '删除规则' is a tautology that simply restates the tool name 'deleteRule' in Chinese. It provides no additional information about what resource is being deleted, what a 'rule' represents in this context, or how this differs from sibling tools like 'deleteGroup' or 'deleteValue'. The purpose is minimally stated but lacks specificity.

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?

There is no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the rule must exist or be disabled first), exclusions, or relationships to sibling tools like 'disableRule', 'removeRuleFromGroup', or 'deleteGroup'. The description offers zero contextual usage information.

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. '删除值' only indicates a destructive deletion action but reveals nothing about side effects (e.g., whether deletion is permanent, affects dependencies), authentication needs, error conditions, or response format. For a mutation tool with zero annotation coverage, this is critically inadequate.

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 phrase '删除值', which is extremely concise but under-specified rather than efficiently informative. It lacks any structure (e.g., front-loaded purpose, usage notes) and fails to convey necessary details for a deletion tool. Conciseness should not come at the cost of clarity, making this score low.

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 (a destructive deletion with no annotations or output schema), the description is completely inadequate. It doesn't explain what 'value' refers to, the consequences of deletion, error handling, or return values. Sibling tools like 'getAllValues' suggest a value management system, but the description provides no context to integrate this tool meaningfully.

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 '值名称' (value name) in the schema. The description adds no additional meaning about the parameter (e.g., format constraints, examples, or relationship to other tools). Since the schema fully describes the parameter, the baseline score of 3 is appropriate, but the description doesn't compensate or enhance 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 '删除值' (delete value) is a tautology that merely restates the tool name 'deleteValue' in Chinese. It doesn't specify what kind of value is being deleted (e.g., configuration value, database entry), what resource it operates on, or how it differs from sibling tools like 'deleteGroup' or 'deleteValueGroup'. While the verb is clear, the object is too vague for meaningful 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. It doesn't mention prerequisites (e.g., whether the value must exist), exclusions (e.g., cannot delete system values), or relationships to sibling tools like 'deleteValueGroup' or 'getAllValues'. Without any context, an agent would struggle to choose this tool appropriately.

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 but provides none. It doesn't indicate whether this is a destructive operation (though 'delete' implies it), what permissions are required, whether the deletion is permanent or reversible, what happens to associated values or rules, or what the response looks like. This is inadequate 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 extremely concise at just three Chinese characters, with zero wasted words. While this conciseness comes at the expense of completeness, the description itself is efficiently structured as a single, clear phrase.

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 destructive deletion tool with no annotations and no output schema, the description is completely inadequate. It provides minimal context about what the tool does and offers no information about behavior, consequences, alternatives, or expected outcomes. This leaves critical gaps for an agent trying to understand and use this tool safely.

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 'groupName' clearly documented in the schema as '分组名称' (group name). The description adds no additional parameter information beyond what the schema provides, so the baseline score of 3 is appropriate given the schema handles the 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 '删除值分组' (Delete value group) is a tautology that essentially restates the tool name 'deleteValueGroup' in Chinese. While it correctly identifies the verb ('delete') and resource ('value group'), it provides no additional specificity about what this operation entails or how it differs from similar tools like 'deleteGroup' or 'deleteValue'.

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 offers no guidance on when to use this tool versus alternatives. With multiple deletion-related sibling tools (deleteGroup, deleteRule, deleteValue, removeValueFromGroup), there's no indication of what distinguishes deleting a 'value group' from deleting other entities or when this specific deletion operation is appropriate.

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 full burden for behavioral disclosure. '禁用规则' implies a mutation (disabling), but it doesn't describe what happens when a rule is disabled (e.g., stops applying, remains in system), whether it's reversible (via enableRule), permission requirements, side effects, or error conditions. For a mutation tool with zero annotation coverage, this is inadequate.

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 (two characters) but under-specified rather than efficiently informative. While it's front-loaded with the core action, it lacks necessary context for a mutation tool. Conciseness should not come at the cost of clarity, making this borderline adequate but with significant gaps.

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 this is a mutation tool with no annotations, no output schema, and 27 sibling tools, the description is incomplete. It doesn't explain what 'disable' entails operationally, how it differs from similar tools, or what to expect after invocation. The high sibling count increases complexity, making the minimal description insufficient for proper tool selection and 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 with 'ruleName' clearly documented as '规则名称' (rule name). The description adds no parameter information beyond what the schema provides. According to scoring rules, with high schema coverage (>80%), the baseline is 3 even with no param info in description, which applies here.

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 '禁用规则' (disable rule) is a tautology that restates the tool name 'disableRule' in Chinese. It doesn't specify what type of rule, what system it operates on, or what 'disable' means operationally. While it includes a verb+resource, it lacks specificity and doesn't distinguish from sibling tools like 'enableRule' or 'setAllRulesState' beyond the basic action.

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., rule must exist), when-not-to-use scenarios (e.g., vs. deleteRule), or explicit alternatives like 'enableRule' for toggling or 'setAllRulesState' for bulk operations. With 27 sibling tools including related ones, this lack of differentiation is problematic.

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. '启用规则' only states the action without explaining what enabling does (e.g., activates a rule for interception, changes its state, requires specific permissions), whether it's reversible, potential side effects, or response format. For a mutation tool with zero annotation coverage, this is a critical gap that leaves the agent guessing about 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 phrase '启用规则', which is extremely concise but under-specified rather than efficiently informative. It lacks necessary details for a mutation tool, making it more of an omission than effective brevity. Every sentence should earn its place, but here the single phrase fails to provide adequate value.

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 (a mutation operation affecting rule states), lack of annotations, no output schema, and rich sibling tools, the description is incomplete. It doesn't explain what enabling a rule does, how it differs from other state-changing tools, or what to expect in return. For a tool in this context, the description is severely inadequate.

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 'ruleName' documented as '规则名称' (rule name). The description adds no parameter information beyond what the schema provides. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 '启用规则' (Enable rule) is a tautology that essentially restates the tool name 'enableRule' in Chinese. While it indicates the action (enable) and resource (rule), it doesn't specify what type of rules, what enabling entails, or how this differs from similar tools like 'toggleMultiRuleMode' or 'setAllRulesState' that also affect rule states. The purpose is minimally stated but lacks differentiation from siblings.

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., whether the rule must exist or be disabled first), when not to use it, or how it compares to sibling tools like 'disableRule', 'setAllRulesState', or 'toggleMultiRuleMode'. Without any context, an agent would struggle to choose this tool appropriately.

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 full burden. It states a read operation ('获取' - get), implying it's likely non-destructive, but doesn't disclose behavioral traits such as permissions needed, rate limits, response format, or whether it returns all values at once (e.g., pagination). This is inadequate for a tool with no annotation coverage.

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

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

The description is a single, efficient sentence in Chinese ('获取所有规则的值'), which is appropriately concise and front-loaded. There's no wasted text, though it could benefit from more detail given the lack of other context.

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 no annotations, no output schema, and low complexity (0 parameters), the description is incomplete. It doesn't explain what 'rules' and 'values' mean in this system, the return format, or how it differs from similar tools like 'getRules'. For a read operation in a server with many siblings, more 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, and schema description coverage is 100% (though empty). The description doesn't add parameter details since there are none, which is appropriate. Baseline is 4 for 0 parameters, as no compensation is needed.

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 '获取所有规则的值' (Get all rule values) states a verb ('获取' - get) and resource ('规则的值' - rule values), providing a basic purpose. However, it's vague about what 'rules' and 'values' refer to in this context, and it doesn't distinguish from siblings like 'getRules' or 'getInterceptInfo'. It avoids tautology but lacks specificity.

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, context, or exclusions, and with siblings like 'getRules' available, there's no indication of how this differs (e.g., whether it retrieves values only vs. full rule details). This leaves usage unclear.

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. The description only states what the tool does (gets timestamp) without mentioning any behavioral traits like whether it's read-only, if it has side effects, performance characteristics, or error conditions. 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.

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

The description is a single, efficient Chinese phrase that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple, parameterless tool and is front-loaded with the essential information.

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 simplicity (0 parameters, no output schema), the description is minimally complete. However, without annotations or output schema, it doesn't specify what format the timestamp returns (e.g., Unix timestamp, ISO string) or any behavioral context. For a tool that likely returns data, more detail about the return value would improve completeness.

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 fully documents the absence of parameters. The description doesn't need to compensate for any parameter gaps. A baseline of 4 is appropriate since there are no parameters to explain, and the description correctly implies no input is needed.

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 '获取当前本地时间戳' (Get current local timestamp) clearly states the tool's purpose with a specific verb ('获取' - get) and resource ('当前本地时间戳' - current local timestamp). It distinguishes itself from all sibling tools which are related to rules, groups, values, and proxy/interception management, making its purpose distinct. However, it doesn't specify the format or units of the timestamp, 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 implies usage context (when you need the current local timestamp) but doesn't provide explicit guidance on when to use this tool versus alternatives. No sibling tools appear to offer similar timestamp functionality, so there's no need for differentiation, but the description lacks any explicit usage instructions, 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. It mentions that output is base64-encoded, which is useful, but fails to describe critical behaviors: whether this is a read-only operation, what the return format looks like (e.g., list of objects), if there are rate limits, or authentication requirements. 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.

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

The description is a single, efficient sentence that front-loads the core purpose ('获取URL的拦截信息') and adds a crucial detail about base64 encoding. There is no wasted verbiage, and every word contributes to understanding the tool's function.

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 interception tools and the lack of both annotations and an output schema, the description is incomplete. It doesn't explain what 'intercept information' entails (e.g., headers, body, timing), how results are structured, or behavioral constraints. For a tool that likely returns sensitive network data, more context is needed to use it effectively.

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 the schema already documents all three parameters (url, count, startTime) with descriptions. The tool description adds no additional parameter semantics beyond what's in the schema, such as explaining regex usage for the url parameter or default behaviors for optional parameters. Baseline 3 is appropriate when 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 ('获取' meaning 'get') and resource ('URL的拦截信息' meaning 'intercept information of URL'), specifying that both requests and responses are base64-encoded. It distinguishes itself from siblings like getRules or getWhistleStatus by focusing specifically on URL interception data rather than rules or system status.

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 is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, such as needing interception to be enabled (via toggleHttpInterception or toggleHttpsInterception), or differentiate it from other data retrieval tools like getRules or replayRequest. Usage context is implied but not 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does ('get all rules & groups') without any information about permissions, rate limits, side effects, or response format. This leaves critical behavioral traits undocumented, making it inadequate for safe and effective use.

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 phrase in Chinese that directly states the tool's purpose without any fluff. It's front-loaded with the core action and resources, making it efficient and easy to parse. Every word earns its place by conveying essential information.

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 doesn't explain what 'all rules & groups' entails (e.g., format, structure, or scope), nor does it address behavioral aspects like read-only nature or potential errors. For a tool in a complex system with many siblings, more context is needed to ensure 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, as there are none. This meets the baseline for tools with no parameters, as the schema fully covers the absence of inputs.

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 '获取所有规则&分组' (Get all rules & groups) clearly states the verb ('get') and resources ('rules' and 'groups'), making the purpose unambiguous. It distinguishes from siblings like 'getAllValues' or 'getInterceptInfo' by specifying the exact resources. However, it doesn't explicitly mention that it retrieves both rules and groups together, which could be slightly more specific.

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, context for usage, or differentiate from similar tools like 'getAllValues' or 'getInterceptInfo'. The agent must infer usage based on the name alone, which is insufficient for optimal tool selection.

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

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. While '获取' (get) implies a read operation, the description doesn't disclose any behavioral traits like whether this requires authentication, has rate limits, returns real-time vs cached data, or what format the status information comes in. For a status-checking tool with zero annotation coverage, this is inadequate.

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 exactly what the tool does with zero wasted words. It's appropriately sized for a simple tool with no parameters 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?

Given the tool's simplicity (0 parameters, no output schema) and lack of annotations, the description is incomplete. It doesn't explain what 'status' means in this context (e.g., running/stopped, metrics, configuration state) or what format the information returns. For a status tool that could have various interpretations, more 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 baseline is 4. The description appropriately doesn't waste space discussing nonexistent parameters, though it could theoretically mention that no configuration is needed for this status check.

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 ('获取' meaning 'get') and resource ('whistle服务器的当前状态' meaning 'whistle server's current status'), providing a specific verb+resource combination. However, it doesn't differentiate from siblings like 'getCurrentTimestamp' or 'getInterceptInfo' which also retrieve status-like information, 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 no guidance on when to use this tool versus alternatives. With siblings like 'getCurrentTimestamp' and 'getInterceptInfo' that might retrieve related status information, there's no indication of when this specific status check is appropriate versus other getter tools.

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. The description only states the action ('remove rule from group') without any information about side effects (e.g., whether this affects rule functionality, if it's reversible, or what happens to the rule after removal), permissions required, or error conditions. This is inadequate 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.

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

The description is a single, efficient phrase ('将规则移出分组') that directly conveys the tool's purpose without unnecessary words. It's appropriately sized for a simple operation and front-loaded with the core action, 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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks crucial behavioral context (e.g., what 'remove' entails, side effects, or return values) and doesn't compensate for the absence of structured fields. While concise, it fails to provide enough information 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.

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

Schema description coverage is 100% (the 'ruleName' parameter is documented in the schema as '规则名称' - rule name), so the baseline is 3. The description doesn't add any parameter details beyond what the schema provides, such as format examples or constraints, but it doesn't need to since the schema is complete. No parameters are omitted or misunderstood.

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 '将规则移出分组' (Remove rule from group) clearly states the action (remove) and target (rule from group), which is better than a tautology. However, it doesn't specify what 'group' refers to in this context or differentiate from sibling tools like 'removeValueFromGroup', leaving some ambiguity about the exact resource being manipulated.

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., the rule must already be in a group), when not to use it, or refer to related tools like 'addRuleToGroup' or 'deleteRule' for context. The agent must infer usage from the tool name 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 only states the action ('remove value from group') without explaining effects (e.g., whether this is destructive, if it requires permissions, or what happens to the value afterward). For a mutation tool with zero annotation coverage, this is a critical 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 phrase that is overly concise to the point of under-specification. It lacks structure and fails to convey essential details, making it inefficient rather than appropriately brief. Every word should add value, but here it merely repeats the tool name.

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 severely incomplete. It doesn't explain what the tool returns, error conditions, or behavioral traits. For a tool that modifies data, this leaves the agent with insufficient context to use it correctly.

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 'valueName' documented as '值名称' (value name). The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema already provides adequate parameter information.

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 '将值移出分组' (remove value from group) is a tautology that restates the tool name without adding specificity. It doesn't clarify what type of 'value' or 'group' is involved, nor does it distinguish this tool from sibling tools like 'removeRuleFromGroup' or 'deleteValue'. The purpose is stated but lacks meaningful 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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., the value must exist in a group), exclusions, or related tools like 'addValueToGroup' or 'deleteValue'. The description offers no context for appropriate usage.

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. '重命名分组' only states the action without any information about permissions required, whether the rename is atomic/reversible, error conditions (e.g., duplicate names), side effects, or what happens upon success/failure. For a mutation tool with zero annotation coverage, this is inadequate.

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 with just three characters in Chinese ('重命名分组'), which translates to 'Rename group'. It's front-loaded with the core action and resource, with zero wasted words. While under-specified, it's not verbose.

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, no output schema, and multiple similar siblings, the description is incomplete. It doesn't address behavioral aspects, usage context, or distinguish itself from other rename tools. The 100% schema coverage helps with parameters, but overall completeness is poor for 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%, with both parameters ('groupName' and 'newName') clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides. According to 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.

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

The description '重命名分组' (Rename group) is a tautology that merely restates the tool name 'renameGroup'. It specifies the verb (rename) and resource (group) but doesn't distinguish this tool from its sibling 'renameRule', 'renameValue', or 'renameValueGroup', all of which perform similar rename operations on different resource types. The description lacks specificity about what kind of group is being renamed.

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., the group must exist), exclusions (e.g., cannot rename to an existing name), or when to choose other rename tools like 'renameRule' or 'renameValueGroup'. With multiple rename siblings in the context, this omission is significant.

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. '重命名规则' implies a mutation operation but doesn't specify whether this requires special permissions, whether the rename is reversible, what happens to references to the old rule name, or what the tool returns. For a mutation tool with zero annotation coverage, this is insufficient behavioral information.

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 at just two characters in Chinese ('重命名规则'), which translates to 'Rename rule'. While it's under-specified in terms of content, as a standalone statement it's front-loaded and wastes no words. Every character serves the core purpose statement.

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 this is a mutation tool with no annotations, no output schema, and multiple similar rename operations in the sibling list, the description is incomplete. It doesn't explain what happens after renaming, error conditions, or how this differs from 'updateRule'. The combination of mutation nature and lack of structured metadata requires more descriptive content.

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 both parameters clearly documented in the schema ('规则的新名称' for newName and '规则现有名称' for ruleName). The description adds no additional parameter information beyond what the schema provides, 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.

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

The description '重命名规则' (Rename rule) is a tautology that restates the tool name 'renameRule' without adding specificity. It doesn't explain what type of rule is being renamed, what system this operates in, or how it differs from sibling tools like 'renameGroup' or 'renameValue'. The purpose is stated but lacks distinguishing details.

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, when this operation is appropriate, or how it relates to similar tools like 'updateRule' or other rename operations in the sibling list. There's complete absence of usage context.

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. '重命名值' implies a mutation operation, but it doesn't specify whether this requires special permissions, what happens if the value doesn't exist or the new name conflicts, whether the change is reversible, or any rate limits. For a mutation tool with zero annotation coverage, this leaves critical behavioral traits undocumented.

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 with just two characters ('重命名值'), which is appropriately sized for such a simple concept. It's front-loaded with the core action and wastes no words. While it's under-specified in content, it earns full marks for conciseness as every character serves the purpose of stating the tool's function.

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 that this is a mutation tool with no annotations, no output schema, and multiple similar sibling tools, the description is incomplete. It doesn't explain what happens after renaming, what type of value is affected, or how this differs from other rename operations. The description fails to provide the contextual information needed for an agent to use this tool effectively in its ecosystem.

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 clear parameter documentation ('值现有名称' for existing name, '值的新名称' for new name). The description adds no additional semantic information beyond what the schema already provides. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline score 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.

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

The description '重命名值' (Rename value) is a tautology that restates the tool name without adding specificity. It doesn't clarify what type of 'value' is being renamed (e.g., configuration value, data value, parameter value) or distinguish this from sibling tools like renameGroup or renameRule. The purpose is vague and lacks the verb+resource specificity needed for clear 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?

The description provides no guidance on when to use this tool versus alternatives. There are multiple rename-related sibling tools (renameGroup, renameRule, renameValueGroup), but the description doesn't indicate what makes this tool different or when it should be chosen over those alternatives. No context, prerequisites, or exclusions are mentioned.

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. '重命名值分组' implies a mutation operation (renaming), but it doesn't disclose any behavioral traits: no information about permissions required, whether the rename is reversible, what happens to references to the old name, error conditions, or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral 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 at just three Chinese characters. While this represents under-specification rather than ideal conciseness, according to the scoring framework, conciseness is evaluated separately from completeness. The description contains zero wasted words and is front-loaded with the core action.

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 this is a mutation tool with no annotations, no output schema, and multiple similar sibling tools, the description is incomplete. It doesn't explain what happens after renaming, whether there are constraints on the new name, how to handle errors, or how this differs from other rename operations. The agent would struggle to use this tool correctly without additional context.

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 clear parameter descriptions in Chinese ('分组现有名称' for groupName and '分组的新名称' for newName). The tool description adds no additional parameter semantics beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no parameter information in the description.

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 '重命名值分组' (Rename value group) is a tautology that essentially restates the tool name 'renameValueGroup' in Chinese. It doesn't specify what type of value group is being renamed or provide any distinguishing context from sibling tools like renameGroup or renameValue. While the verb 'rename' is clear, the description lacks specificity about the resource being renamed.

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 absolutely no guidance on when to use this tool versus alternatives. There are multiple sibling tools that rename different entities (renameGroup, renameRule, renameValue), but the description doesn't help an agent understand when renameValueGroup is appropriate versus these other rename operations. No context, prerequisites, or exclusions are mentioned.

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 adds valuable context: the tool doesn't return results directly ('本接口请求后不会直接返回结果'), requiring a separate call to 'getInterceptInfo'. This is crucial for understanding the asynchronous or multi-step nature of the operation. However, it lacks details on permissions, rate limits, or error handling, which are important for a tool that likely involves network requests.

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 concise and front-loaded, stating the main purpose in the first part: '在whistle中重放捕获的请求'. The second sentence adds critical behavioral context about result retrieval. There's no wasted text, and both sentences earn their place by providing essential information without redundancy.

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 (a tool for replaying network requests with 5 parameters) and no annotations or output schema, the description is moderately complete. It covers the purpose and a key behavioral trait (indirect result retrieval), but lacks details on error cases, performance implications, or integration with other tools like 'toggleHttpInterception'. For a tool with no structured safety or output info, more context would be beneficial.

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 all parameters well-documented (e.g., 'url' as required, 'method' defaults to GET). The description doesn't add any parameter-specific semantics beyond what the schema provides, such as explaining how 'body' or 'headers' should be formatted for replay. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema handles most of the 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 clearly states the tool's purpose: '在whistle中重放捕获的请求' (replay captured requests in whistle). It specifies the verb ('重放' - replay) and resource ('捕获的请求' - captured requests), making the action clear. However, it doesn't differentiate from sibling tools like 'toggleHttpInterception' or 'getInterceptInfo', which are related to request handling but serve different purposes.

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 explicit guidance on when to use this tool: for replaying captured requests in whistle. It also specifies a critical follow-up action: '需要使用getInterceptInfo接口获取结果' (need to use getInterceptInfo interface to get results), which clarifies the workflow. However, it doesn't mention when not to use it or alternatives among siblings, such as other interception-related tools.

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 full burden. It mentions enabling/disabling but doesn't disclose behavioral traits like whether this requires specific permissions, if it's reversible, what happens to existing rule states, or any rate limits. For a mutation tool with zero annotation coverage, this is inadequate.

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 Chinese that directly states the purpose without unnecessary words. It's appropriately sized and front-loaded, with zero 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 this is a mutation tool with no annotations, no output schema, and 1 parameter, the description is incomplete. It doesn't cover behavioral aspects like permissions, reversibility, or response format, which are crucial 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?

Schema description coverage is 100%, so the schema already documents the 'disabled' parameter fully. The description doesn't add any meaning beyond what the schema provides, such as explaining the implications of setting true/false beyond the basic definition. Baseline 3 is appropriate 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 ('控制' meaning control) and target ('所有规则的启用状态' meaning enabled state of all rules), specifying it's about enabling/disabling. It doesn't explicitly differentiate from sibling tools like 'disableRule' or 'enableRule' which affect individual rules, but the scope difference is implied.

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 for bulk control of rules, but doesn't explicitly state when to use this versus alternatives like 'disableRule' or 'enableRule' for individual rules, or mention prerequisites or exclusions. The context is clear but lacks explicit guidance.

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 action ('enable or disable') but doesn't reveal critical details such as whether this requires specific permissions, if changes are reversible, potential side effects (e.g., on performance or compatibility), or what happens after invocation. For a mutation 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 extremely concise—a single phrase in Chinese that directly conveys the tool's function without any wasted words. It's front-loaded and efficiently communicates the core action, earning a high score for brevity and 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 tool's complexity (a mutation operation with no annotations and no output schema), the description is incomplete. It lacks information on behavioral traits, return values, error handling, or how it integrates with the system (e.g., Whistle proxy context from sibling tools). For a toggle tool that likely affects system behavior, more 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 input schema has 100% description coverage, with the single parameter 'enabled' clearly documented as a boolean for enabling/disabling HTTP/2. The description doesn't add any meaning beyond what the schema provides (it just restates the tool's purpose), 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.

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

The description clearly states the action ('启用或禁用' meaning 'enable or disable') and the resource ('HTTP/2'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'toggleHttpInterception' or 'toggleHttpsInterception', which have similar toggle patterns but different targets.

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, context (e.g., when HTTP/2 should be enabled/disabled), or how it relates to sibling tools like 'toggleProxy' or other toggle functions. 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the toggle action but doesn't explain effects (e.g., what happens when enabled/disabled, permissions required, side effects like network changes, or error conditions). This is inadequate for a tool that likely alters system 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 Chinese that directly states the tool's purpose with zero waste. 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 complexity of toggling HTTP interception (a potentially impactful system change), no annotations, and no output schema, the description is incomplete. It lacks details on behavior, outcomes, or error handling, which are crucial 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.

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

Schema description coverage is 100%, with the parameter 'enabled' clearly documented in the schema as a boolean for enabling/disabling HTTP interception. The description doesn't add any meaning beyond this, so it meets the baseline of 3 without compensating or detracting.

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 '启用或禁用HTTP拦截' clearly states the action (toggle) and resource (HTTP interception) in Chinese, which translates to 'Enable or disable HTTP interception.' It's specific about what the tool does but doesn't differentiate from sibling tools like 'toggleHttpsInterception' or 'toggleProxy,' which handle related but distinct functions.

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, context (e.g., when HTTP interception is needed), or exclusions, leaving the agent to infer usage from the tool name alone among many siblings.

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 states the tool enables or disables HTTPS interception, implying a mutation operation, but doesn't disclose behavioral traits such as permissions required, side effects, whether changes are reversible, or rate limits. 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.

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

The description is a single, efficient sentence in Chinese that directly states the tool's function without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks information about what the tool returns, error conditions, or the impact of toggling HTTPS interception (e.g., on security or performance). The description should provide more context to 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 schema description coverage is 100%, with the single parameter 'enabled' clearly documented in the schema as a boolean for enabling/disabling HTTPS interception. The description doesn't add any meaning beyond what the schema provides, so the baseline score of 3 is appropriate given the schema handles the 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 clearly states the action ('启用或禁用' meaning 'enable or disable') and the resource ('HTTPS拦截' meaning 'HTTPS interception'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'toggleHttpInterception' or 'toggleProxy', which have similar toggle patterns but target different resources.

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 'toggleHttpInterception' or 'toggleProxy', nor does it mention prerequisites or exclusions. It's a basic functional statement without context about appropriate 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?

No annotations are provided, so the description carries the full burden. It states the action ('启用或禁用' - enable/disable) but lacks details on behavioral traits like permissions needed, side effects (e.g., impact on other rules or system state), rate limits, or what happens on success/failure. For a mutation 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 in Chinese ('启用或禁用多规则模式') that directly conveys the tool's purpose with zero waste. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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 (a mutation with no annotations and no output schema), the description is incomplete. It lacks information on what multi-rule mode entails, how it interacts with other tools (e.g., 'getRules' or 'setAllRulesState'), and what the expected outcome or return values are. This makes it inadequate 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.

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

The input schema has 100% description coverage, with the parameter 'enabled' documented as '是否启用多规则模式' (whether to enable multi-rule mode). The description doesn't add any meaning beyond this, as it only restates the tool's purpose without elaborating on parameter usage or constraints. Baseline 3 is appropriate when schema coverage is high.

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 '启用或禁用多规则模式' (Enable or disable multi-rule mode) clearly states the verb ('启用或禁用' - enable/disable) and the resource ('多规则模式' - multi-rule mode). It's specific about what the tool does, though it doesn't explicitly distinguish from sibling tools like 'setAllRulesState' or 'toggleHttpInterception' that also toggle states.

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, context, or exclusions, such as when multi-rule mode is applicable compared to other toggle tools like 'toggleHttpInterception' or state-setting tools like 'setAllRulesState'.

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 '启用或禁用' (enable or disable) implies a state change operation, the description doesn't disclose what the proxy does, what gets affected, whether this requires special permissions, or what the expected behavior is. For a state-changing 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 phrase that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple toggle operation.

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 state-changing tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'whistle代理' (whistle proxy) actually does, what systems or traffic it affects, or what the expected outcome of toggling it would be. Given the complexity of proxy operations and the lack of structured data, the description should provide more context.

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 'enabled' clearly documented as '是否启用代理' (whether to enable the proxy). The description doesn't add any parameter information beyond what the schema already provides, so it meets the baseline for high schema coverage.

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 '启用或禁用whistle代理' clearly states the action (toggle/enable/disable) and the target resource (whistle proxy). It uses specific verbs and identifies the resource, but doesn't distinguish this from sibling tools like 'toggleHttpInterception' or 'toggleHttpsInterception' which also toggle proxy-related features.

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. There are multiple toggle-related sibling tools (toggleHttpInterception, toggleHttpsInterception, toggleHttp2, toggleMultiRuleMode), but the description doesn't explain when this specific proxy toggle should be used versus those other toggle operations.

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 'update' implying a mutation, but does not disclose any behavioral traits such as permissions required, whether changes are reversible, side effects, error handling, or rate limits. 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.

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

The description is a single phrase '更新规则内容', which is extremely concise and front-loaded. However, it is under-specified rather than efficiently informative, lacking necessary details for a mutation tool. It earns a 4 for brevity but loses points for not using its minimal space effectively.

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 mutation operation, lack of annotations, no output schema, and multiple sibling tools, the description is incomplete. It fails to address key aspects like what 'rule content' includes, how updates affect the system, or what the tool returns. This inadequacy hinders effective agent 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?

Schema description coverage is 100%, with both parameters ('ruleName' and 'ruleValue') documented in the schema. The description adds no meaning beyond the schema, as it does not explain parameter relationships, formats, or examples. Baseline score of 3 applies since the schema does the heavy lifting, but no extra value is provided.

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 '更新规则内容' (Update rule content) restates the tool name 'updateRule' in Chinese, making it essentially tautological. It specifies the verb 'update' and resource 'rule content' but lacks specificity about what 'rule content' entails or how it differs from similar tools like 'renameRule' or 'disableRule'. No sibling differentiation is provided.

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 offers no guidance on when to use this tool versus alternatives. With siblings like 'renameRule', 'disableRule', 'setAllRulesState', and 'updateValue', there is no indication of prerequisites, context, or exclusions. Usage is implied only by the generic term 'update', 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.

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. '更新值内容' implies a mutation operation, but it doesn't disclose any behavioral traits such as whether this requires specific permissions, if it's idempotent, what happens on failure, or if it affects other system components. 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 extremely concise with a single phrase '更新值内容', which is front-loaded and wastes no words. However, this brevity borders on under-specification, as it lacks necessary details for clarity and completeness. While efficient, it doesn't fully earn its place by providing sufficient value beyond the tool name.

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 fails to explain what the tool returns, error conditions, or how it interacts with the system (e.g., updating values in a configuration or database). The high schema coverage helps with parameters, but overall context is lacking 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 input schema has 100% description coverage, with parameters 'name' (值名称 - value name) and 'value' (新值内容 - new value content) clearly documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the 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 '更新值内容' (update value content) is a tautology that essentially restates the tool name 'updateValue' in Chinese. While it indicates a general update action on values, it doesn't specify what type of values are being updated (e.g., configuration values, database values) or how this differs from sibling tools like 'renameValue' or 'updateRule'. The purpose is vague and lacks differentiation from alternatives.

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. There are no mentions of prerequisites, context, or comparisons to sibling tools such as 'renameValue' (which might change the name only) or 'updateRule' (which updates rules instead of values). Without any usage instructions, the agent has no basis for selecting this tool appropriately.

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