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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the write operation ('Add') but lacks critical details: whether this requires specific permissions, if it's idempotent (e.g., adding an existing tester), what happens on success/failure, or any rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple tool and front-loaded with the core action, making it easy to parse.

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 write operation with 4 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, idempotency, or error handling, nor does it explain what the tool returns. For a mutation tool, this leaves significant gaps for an agent 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?

Schema description coverage is 100%, so the schema already documents all four parameters (groupId, email, firstName, lastName) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. This 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 clearly states the action ('Add') and target resource ('a new tester to a beta group'), making the purpose immediately understandable. It distinguishes from the sibling tool 'remove_tester_from_group' by specifying the opposite operation. However, it doesn't explicitly differentiate from other sibling tools like 'list_group_testers' beyond the verb, which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing beta group), exclusions, or comparisons to sibling tools like 'list_group_testers' for checking existing testers. 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 states 'Create' implies a write operation but doesn't cover critical aspects like permissions required, whether the request is asynchronous, rate limits, or what happens after creation (e.g., report generation time). This leaves significant gaps in understanding the tool's behavior beyond basic intent.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for conciseness in tool descriptions.

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

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

For a tool that creates analytics report requests with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., async nature, permissions), expected outcomes, or error handling. Given the complexity of initiating analytics reports, more context is needed to guide the agent effectively beyond the basic action stated.

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 documentation for both parameters (appId and accessType with enum values). The description adds no additional parameter semantics beyond what's in the schema, such as explaining the implications of 'ONGOING' vs 'ONE_TIME_SNAPSHOT' in more detail. Given the high schema coverage, a baseline score of 3 is appropriate as the schema adequately handles 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 ('Create') and resource ('analytics report request for an app'), making the purpose evident. However, it doesn't explicitly differentiate this tool from sibling tools like 'list_analytics_reports' or 'download_analytics_report_segment', which would require mentioning it's specifically for initiating report generation rather than listing or retrieving existing ones.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an app ID), exclusions, or compare it to related tools like 'list_analytics_reports' for existing data, leaving the agent to infer usage context solely from the tool name and parameters.

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 'create' which implies a write/mutation operation, but doesn't disclose any behavioral traits such as required permissions, whether the creation is reversible, rate limits, or what happens on success/failure. For a creation 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, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration. This is an excellent example of conciseness for a straightforward tool.

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 (7 parameters, creation/mutation operation) and the lack of both annotations and an output schema, the description is insufficiently complete. It doesn't cover behavioral aspects, usage context, or what to expect upon creation. For a mutation tool with no structured safety or output information, the description should provide more guidance to compensate.

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-specific information beyond what's already in the input schema, which has 100% description coverage. It doesn't explain relationships between parameters (e.g., that 'earliestReleaseDate' is required only when 'releaseType' is 'SCHEDULED', though this is hinted in the schema). With high schema coverage, the baseline is 3, and the description doesn't add meaningful semantic context.

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 ('create') and resource ('new app store version for an app'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'list_app_store_versions' or 'update_app_store_version_localization', which would require mentioning it's specifically for creation rather than listing or updating.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing app or build), exclusions, or how it relates to sibling tools like 'create_bundle_id' or 'list_app_store_versions'. This leaves the agent with insufficient context for proper 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 the full burden of behavioral disclosure. It states 'Register a new bundle ID,' implying a write operation, but fails to mention permissions required, rate limits, side effects, or what happens on success/failure. This leaves critical behavioral traits undocumented for a creation tool.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without redundancy. It is front-loaded with the core action and resource, making it easy to parse quickly, with no wasted words or 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 creation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects like permissions, error handling, and return values, which are crucial for safe and effective use. The high schema coverage helps with inputs, but overall context remains insufficient.

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 documentation for all parameters (e.g., 'identifier' as the bundle ID string, 'platform' with enum values). The description adds no additional meaning beyond the schema, such as format examples or usage context, so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the action ('Register') and resource ('new bundle ID for app development'), making the purpose evident. It doesn't explicitly differentiate from sibling tools like 'list_bundle_ids' or 'get_bundle_id_info', but the verb 'Register' implies creation versus listing or retrieval, providing some implicit distinction.

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, such as 'list_bundle_ids' for viewing existing IDs or 'get_bundle_id_info' for details on a specific ID. It lacks context on prerequisites, exclusions, or typical scenarios for registration, leaving 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?

With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a destructive operation, requires specific permissions, has side effects, or what the expected outcome is (e.g., confirmation message, error handling).

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

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

The description is a single, clear sentence with no wasted words. It's front-loaded and efficiently conveys 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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'disable' entails (e.g., reversible, immediate effect), error conditions, or return values, 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?

Schema description coverage is 100%, so the parameter 'capabilityId' is documented in the schema. The description doesn't add any extra meaning about the parameter beyond what's in the schema, such as format examples or where to find capability IDs.

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 ('disable') and target ('a capability for a bundle ID'), making the purpose understandable. However, it doesn't differentiate from the sibling tool 'enable_bundle_capability' beyond the opposite action, missing specific distinctions about when each is appropriate.

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

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

No guidance is provided on when to use this tool versus alternatives like 'enable_bundle_capability' or other bundle-related tools. The description lacks context about prerequisites, conditions for disabling, or what happens after disabling.

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 ('download') but doesn't mention permissions, rate limits, output format (e.g., file type, structure), or side effects. This is inadequate for a tool that likely involves data retrieval and potential constraints.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.

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

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the download returns (e.g., data format, file type) or behavioral aspects like error handling, which are crucial for an analytics tool. This leaves significant gaps for agent understanding.

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 'segmentUrl' clearly documented. The description adds no additional meaning beyond the schema, such as URL format examples or validation rules, so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the verb ('download') and resource ('data from an analytics report segment URL'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_analytics_report_segments' or 'create_analytics_report_request', which would require a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'list_analytics_report_segments' for listing segments or 'create_analytics_report_request' for generating reports. It lacks context on prerequisites or exclusions, leaving 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?

With no annotations provided, the description carries full burden for behavioral disclosure. 'Enable' implies a mutation/write operation, but the description doesn't specify whether this requires special permissions, what happens if the capability is already enabled, whether changes are reversible, or what the typical response looks like. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for what it communicates, though the brevity contributes to the lack of detail in other dimensions. Every word in the description serves a purpose.

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

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

For a mutation tool with 3 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what happens after enabling a capability, what errors might occur, or how this tool fits into broader workflows. The agent would need to guess about important behavioral aspects and outcomes.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, provide examples of valid 'settings' configurations, or clarify the meaning of 'enabling' a capability type. 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 states the action ('enable') and target ('capability for a bundle ID'), which provides a basic understanding of purpose. However, it's vague about what 'enable' entails operationally and doesn't distinguish this tool from its sibling 'disable_bundle_capability' beyond the verb difference. The description lacks specificity about what enabling a capability actually does in this context.

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

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

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., whether the bundle ID must exist first), appropriate contexts, or relationships with sibling tools like 'disable_bundle_capability' or 'create_bundle_id'. The agent receives no usage context beyond the literal description.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'gets' information (implying read-only), but doesn't mention authentication requirements, rate limits, response format, pagination, or error conditions. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the core functionality.

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

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

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'detailed information' means, what format the response takes, or any behavioral constraints. Given the complexity implied by the 'include' parameter with 14 relationship options, more context about the response structure would be valuable.

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 both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain what 'detailed information' includes or how the 'include' parameter affects the response. 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 verb ('Get') and resource ('detailed information about a specific app'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_bundle_id_info' or 'list_apps' which also retrieve app-related 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 'list_apps' for multiple apps and 'get_bundle_id_info' for different resource types, there's no indication of when this specific app info retrieval is preferred or required.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a 'Get' operation, implying read-only access, but doesn't clarify authentication requirements, rate limits, error conditions, or response format. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

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 without unnecessary words. Every element ('Get detailed information about a specific app store version localization') directly contributes to understanding the tool's function, with zero wasted content.

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 a read operation with one parameter, the description is insufficiently complete. It doesn't explain what 'detailed information' includes, potential return values, or operational constraints. For a tool in this context, more behavioral and output context is needed to adequately guide an 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 'localizationId' fully documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., format examples, sourcing hints), so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the verb ('Get detailed information about') and resource ('a specific app store version localization'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_app_store_version_localizations' or 'update_app_store_version_localization', which would require explicit comparison to achieve 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. It doesn't mention prerequisites (e.g., needing a localization ID from another operation), contrast it with 'list_app_store_version_localizations' for bulk retrieval, or specify scenarios where detailed information is needed versus basic listing.

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

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

With no annotations provided, the description carries full burden but only mentions the default behavior of downloading the screenshot. It doesn't disclose critical behavioral traits like authentication requirements, rate limits, error conditions, response format, or whether this is a read-only operation (though implied by 'get').

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?

Two sentences with zero waste - first states the core purpose, second clarifies the default behavior. Perfectly front-loaded with essential information in minimal space.

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 4-parameter tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'detailed information' includes beyond the screenshot, how the response is structured, or what happens when optional parameters are used. The schema covers parameter definitions well, but behavioral context is lacking.

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 parameters thoroughly. The description adds minimal value beyond the schema by mentioning the default download behavior, but doesn't provide additional context about parameter interactions or usage scenarios.

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

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

The description clearly states the verb ('Get detailed information') and resource ('beta feedback screenshot submission'), specifying it's for a specific submission. It distinguishes from sibling 'list_beta_feedback_screenshots' by focusing on individual retrieval rather than listing multiple items.

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 when detailed info about a specific screenshot is needed, but doesn't explicitly state when to use this vs alternatives like 'list_beta_feedback_screenshots' or other beta-related tools. No exclusions or prerequisites are mentioned.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'gets detailed information', implying a read-only operation, but doesn't cover aspects like authentication needs, rate limits, error handling, or what 'detailed information' entails (e.g., response format, pagination). This leaves significant gaps for an AI agent to understand how to invoke it correctly.

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 ('Get detailed information about a specific bundle ID') with zero waste. It's appropriately sized for a simple retrieval tool, making it easy for an AI agent to parse quickly.

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

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

Given the tool's moderate complexity (3 parameters, nested objects, no output schema) and lack of annotations, the description is minimally adequate but incomplete. It covers the basic purpose but fails to address behavioral aspects like response format or usage context, which are crucial for correct invocation. Without an output schema, the description should ideally hint at return values, but it doesn't.

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 parameters (bundleIdId, include, fields) with descriptions and enums. The description adds no additional meaning beyond what's in the schema, such as explaining the purpose of 'include' or 'fields' in practical terms. Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the verb 'Get' and the resource 'detailed information about a specific bundle ID', making the purpose understandable. However, it doesn't differentiate this tool from similar siblings like 'get_app_info' or 'list_bundle_ids', which would require mentioning it retrieves details for a single, specific bundle ID rather than listing or getting app information.

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. For example, it doesn't specify that this is for retrieving details of a single bundle ID (vs. 'list_bundle_ids' for multiple) or clarify its relationship to other get_* tools like 'get_app_info'. The description implies usage by stating 'specific bundle ID' but lacks explicit context 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets' information, implying a read-only operation, but doesn't cover critical aspects like authentication requirements, rate limits, error conditions, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every part contributing to understanding. No wasted verbiage or structural issues.

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 (3 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits, parameter usage, and output expectations, making it insufficient for an agent to fully understand how to invoke and interpret results. It should provide more context for a tool of this nature.

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 67% (2 of 3 parameters have descriptions), so the baseline is 3. The description adds no parameter semantics beyond what the schema provides—it doesn't explain what 'detailed information' corresponds to in the parameters or clarify usage of 'include' and 'fields'. It marginally meets the baseline without compensating for the coverage gap.

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

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

The description clearly states the verb ('get') and resource ('detailed information about a specific build action'), making the purpose understandable. It distinguishes from siblings like 'list_ci_build_actions' by focusing on a single action rather than listing multiple. However, it doesn't explicitly mention what 'detailed information' includes or contrast with other get_* 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. It doesn't mention prerequisites like needing a buildActionId, contrast with 'list_ci_build_actions' for bulk retrieval, or specify contexts where detailed info is needed. Usage is implied but not explicitly stated.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Get available analytics reports', which implies a read-only operation, but doesn't disclose other traits like pagination behavior, rate limits, authentication needs, or what 'available' means in terms of status or permissions. The description is minimal and lacks context beyond the basic action.

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

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

The description is a single, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to understand at a glance. Every part of the sentence earns its place by specifying the tool's purpose.

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

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

Given the tool has 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., what 'available' entails, error handling), doesn't explain the return format or structure of reports, and provides minimal guidance on usage. For a tool with moderate complexity and no structured support, the description should do more to compensate.

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 67%, with parameters like 'reportRequestId' and 'filter.category' well-described in the schema. The description adds no additional parameter semantics beyond implying the tool is for a 'specific report request', which aligns with the required 'reportRequestId'. Since schema coverage is moderate, the description doesn't compensate for gaps but doesn't detract either, meeting the baseline.

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

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

The description clearly states the verb 'Get' and resource 'available analytics reports', specifying it's for a 'specific report request'. It distinguishes from siblings like 'create_analytics_report_request' (creation vs. retrieval) and 'list_analytics_report_segments' (reports vs. segments), though it doesn't explicitly contrast with other list tools like 'list_apps' or 'list_beta_groups'.

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 by specifying 'for a specific report request', suggesting it should be used when you have a reportRequestId. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'list_analytics_report_segments' or other list tools, nor does it mention 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. It mentions that segments 'contain download URLs', which adds useful context about the return data. However, it lacks details on permissions, rate limits, pagination, or error handling, which are critical for a tool that likely accesses analytics 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 that front-loads the core purpose and includes a key detail about download URLs. There is no wasted text, and it is appropriately sized for the tool's complexity.

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 and no output schema, the description is minimal but covers the basic purpose. It lacks details on behavioral traits, error cases, or output structure, which would be helpful for an analytics tool. However, it's adequate as a starting point for a read-only operation with clear parameters.

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 fully documents the parameters (reportId and limit). The description does not add any meaning beyond what the schema provides, such as explaining the format of reportId or how segments are ordered. Baseline 3 is appropriate as the schema handles 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 verb 'Get' and resource 'segments for a specific analytics report', specifying it retrieves segments with download URLs. It distinguishes from the sibling 'list_analytics_reports' by focusing on segments of a report rather than listing reports themselves, but doesn't explicitly differentiate from 'download_analytics_report_segment'.

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

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

No guidance is provided on when to use this tool versus alternatives like 'download_analytics_report_segment' or 'list_analytics_reports'. The description implies usage for retrieving segments with URLs but doesn't specify contexts, 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets a list' which implies a read-only operation, but doesn't mention pagination behavior, rate limits, authentication requirements, or what format the list returns. For a tool with zero annotation coverage, 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 gets straight to the point with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core purpose immediately.

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 (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't address what the list contains, how results are structured, whether there's pagination, or any behavioral aspects. While the tool isn't complex, the description leaves too many operational questions unanswered for 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?

The input schema has 100% description coverage, with the 'limit' parameter fully documented in the schema itself. The description adds no additional 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.

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

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

The description clearly states the verb ('Get') and resource ('list of all apps in App Store Connect'), making the purpose immediately understandable. It distinguishes from siblings like 'get_app_info' by focusing on listing rather than retrieving detailed information about a specific app. However, it doesn't explicitly differentiate from other list tools like 'list_app_store_versions' beyond the resource name.

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 when to choose 'list_apps' over 'get_app_info' for detailed app data, or when to use it versus other list tools like 'list_app_store_versions'. There's no context about prerequisites, authentication needs, or typical use cases.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation (implying read-only), but doesn't mention pagination behavior, rate limits, authentication requirements, error conditions, or what format the localizations are returned in. For a list operation with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple list operation and front-loads 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?

For a list operation with good schema coverage but no annotations and no output schema, the description is minimally adequate. It states what the tool does but lacks important context about return format, pagination, and differentiation from similar tools. The absence of output schema means the agent won't know what structure to expect from the response.

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 well-documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., it doesn't explain what an 'app store version' is or provide context about localization types). Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the verb ('Get') and resource ('all localizations for a specific app store version'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'get_app_store_version_localization' (singular vs. plural), which could cause confusion about when to use each tool.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get_app_store_version_localization' or 'list_app_store_versions'. It doesn't mention prerequisites, context for usage, or any exclusions, leaving the agent to infer usage patterns from tool names alone.

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

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 'Get all app store versions' but doesn't mention whether this is a read-only operation, if it requires authentication, how results are paginated (beyond the limit parameter), or what the output format looks like. For a list operation with no annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of it earns its place by clearly stating the tool's function, making it highly concise and well-structured.

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

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

Given the complexity (3 parameters with nested objects) and lack of annotations or output schema, the description is incomplete. It doesn't address behavioral aspects like pagination, authentication needs, or error handling, which are crucial for an agent to use this tool effectively. The schema covers parameters well, but the description fails to provide necessary context beyond the basic purpose.

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 fully documents all parameters (appId, limit, filter). The description adds no additional meaning beyond implying filtering by app, which is already covered in the schema. This meets the baseline of 3 where the schema does the heavy lifting, but the description doesn't enhance parameter understanding.

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

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

The description clearly states the action ('Get all') and resource ('app store versions for a specific app'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_app_info' or 'list_apps', which might also retrieve app-related information, so it doesn't fully distinguish itself 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 like 'get_app_info' or 'list_apps'. It lacks context about prerequisites, such as needing an app ID, or exclusions, such as not being suitable for retrieving single versions. This leaves the agent without clear usage direction.

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 this is a list operation, implying read-only behavior, but doesn't disclose pagination behavior, rate limits, authentication requirements, or what happens if no feedback exists. The description adds minimal behavioral context beyond the basic 'list' action.

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?

Two sentences that efficiently convey the purpose and key parameter usage. The first sentence states what the tool does and what it includes; the second clarifies the app identification options. No wasted words, though it could be slightly more structured with bullet points for the included content.

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

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

For a tool with 12 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the return format, pagination, error conditions, or how the optional filters interact. The agent would need to rely heavily on the input schema alone, missing important behavioral 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%, so the schema already documents all 12 parameters thoroughly. The description adds that you can 'identify the app using either appId or bundleId', which clarifies the relationship between these two parameters, but doesn't provide additional semantic context beyond what's in the schema. 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 verb ('List') and resource ('beta feedback screenshot submissions for an app'), and specifies the content includes 'feedback with screenshots, device information, and tester comments'. It doesn't explicitly differentiate from sibling tools like 'get_beta_feedback_screenshot' (singular vs. plural), but the plural 'list all' indicates a collection operation.

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 retrieving beta feedback with screenshots, but doesn't explicitly state when to use this tool versus alternatives like 'get_beta_feedback_screenshot' (singular) or other feedback-related tools. It mentions identifying the app using 'appId or bundleId', which provides some context but no explicit exclusions or comparisons to 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 full burden. It states it 'gets a list' but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, or what 'all' entails (e.g., completeness guarantees). This is inadequate for a list operation without annotation support.

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 front-loaded with the core purpose and appropriately sized for a simple list tool, making it easy to parse quickly.

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

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

Given the tool's low complexity (1 optional parameter, no output schema), the description is minimally adequate. However, without annotations or output schema, it lacks details on return format or behavioral constraints, leaving gaps for an AI agent to infer.

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 fully documents the 'limit' parameter. The description adds no parameter-specific information beyond what the schema provides, meeting the baseline for high coverage but not adding extra value.

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

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

The description clearly states the verb ('Get') and resource ('list of all beta groups'), specifying both internal and external groups. It distinguishes from siblings like 'list_group_testers' or 'list_users' by focusing on beta groups specifically, though it doesn't explicitly contrast with them.

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. While siblings like 'list_group_testers' or 'list_apps' exist, the description doesn't mention them or specify contexts where this tool is preferred, leaving 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool lists build runs 'including git commit information', which hints at read-only behavior and output content. However, it fails to disclose critical traits such as pagination (implied by 'limit' parameter but not explained), rate limits, authentication requirements, error handling, or whether it's a safe read operation. For a tool with 6 parameters and no annotations, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does ('List build runs') and key output details ('including git commit information'), with zero redundancy or fluff. Every part of the sentence 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 tool's complexity (6 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits (e.g., safety, performance), output format (beyond mentioning git commit info), and usage context. Without annotations or an output schema, the description should provide more guidance on what to expect when invoking the tool, but it falls short, leaving the agent with insufficient context for reliable use.

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

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

The description adds minimal semantic context beyond the input schema. It implies that parameters relate to filtering and including git commit data, but doesn't elaborate on how 'ciProductId' maps to workflows or what 'git commit information' entails. With 67% schema description coverage (4 out of 6 parameters have descriptions in the schema), the baseline is 3, as the schema does most of the heavy lifting. The description doesn't compensate for the 33% coverage gap (e.g., 'fields' object details are only in the schema).

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

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

The description clearly states the action ('List') and resource ('build runs for a specific workflow/CI product'), including the scope of information returned ('including git commit information'). It distinguishes itself from siblings like 'list_ci_build_actions' or 'list_workflows' by focusing on build runs rather than actions or workflows themselves. However, it doesn't explicitly differentiate from 'list_ci_test_results' or 'list_ci_issues', which might be related but not identical.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid ciProductId), exclusions, or comparisons to sibling tools like 'list_ci_build_actions' or 'list_workflows'. The agent must infer usage from the tool name and parameters alone, which is insufficient for optimal 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 the full burden of behavioral disclosure. It states the tool 'finds and lists' bundle IDs, implying a read-only operation, but lacks details on permissions, rate limits, pagination, or response format. This is a significant gap for a tool with multiple parameters and no output schema.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly.

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

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

Given the tool's complexity (4 parameters, nested objects, no output schema) and lack of annotations, the description is incomplete. It doesn't explain the response structure, error handling, or behavioral traits like pagination, which are crucial for effective tool use in this 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 75%, providing good documentation for parameters like 'limit', 'sort', and 'include'. The description adds no additional parameter semantics beyond what's in the schema, but the schema's coverage is sufficient to meet the baseline score of 3 for adequate parameter understanding.

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

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

The description clearly states the action ('Find and list') and resource ('bundle IDs that are registered to your team'), providing a specific purpose. However, it doesn't explicitly differentiate from sibling tools like 'list_apps' or 'get_bundle_id_info', which could also involve bundle IDs, so it doesn't reach the highest 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, such as 'get_bundle_id_info' for detailed info on a single bundle ID or 'list_apps' for broader listings. There's no mention of prerequisites, exclusions, or contextual usage, leaving the agent to infer based on tool names alone.

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

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 only states what the tool does operationally ('List build actions') without mentioning pagination behavior (implied by 'limit'), rate limits, authentication requirements, error conditions, or what the response structure looks like. This is inadequate for a tool with 6 parameters and no output schema.

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 without unnecessary words. Every part earns its place by specifying the action, resource, and scope concisely.

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 (6 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It lacks details on response format, error handling, pagination beyond the 'limit' parameter, and how filtering/sorting interacts with the listed action types. This leaves significant gaps for an AI agent to use the tool 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 description adds minimal value beyond the input schema, which has 67% coverage. It mentions 'build actions' and 'build run', which aligns with the 'buildRunId' parameter, but doesn't explain the purpose of filtering, sorting, or inclusion options. With moderate schema coverage, the baseline is 3, as the schema does most of the work without description enhancement.

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

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

The description clearly states the verb ('List') and resource ('build actions'), with specific examples of action types (analyze, build, test, archive) and the scope ('for a specific build run'). However, it doesn't differentiate from sibling tools like 'list_build_runs' or 'get_ci_build_action', which would require a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'list_build_runs' (for broader context) or 'get_ci_build_action' (for a single action). There's no mention of prerequisites, exclusions, or typical use cases beyond the basic functionality.

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

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states it 'List issues and errors' but doesn't disclose pagination behavior (though schema implies limit/default), rate limits, authentication needs, or what happens with missing IDs. It lacks context on response format, error handling, or whether it's read-only/destructive.

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. Every word earns its place with no redundancy or fluff. It's appropriately sized for a list operation tool.

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 7 parameters, no annotations, no output schema, and nested objects, the description is incomplete. It doesn't address complexity like filter/fields usage, response structure, or error cases. For a tool with rich input options and no structured output documentation, more guidance 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 71%, so the schema documents most parameters well. The description adds no parameter-specific semantics beyond implying 'build run or build action' context for IDs. It doesn't explain parameter interactions, defaults beyond schema, or usage examples. Baseline 3 is appropriate given schema does 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 verb ('List') and resource ('issues and errors'), specifying they come from 'a build run or build action'. It distinguishes from siblings like 'list_ci_test_results' by focusing on issues/errors rather than test results. However, it doesn't explicitly differentiate from all sibling tools, just implies scope.

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 is provided. The description doesn't mention prerequisites, when-not scenarios, or compare with similar tools like 'list_ci_test_results'. The input schema hints at alternatives with 'provide either buildRunId or buildActionId', but the description itself offers no 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?

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states it 'lists' test results, implying a read-only operation, but doesn't cover pagination (though 'limit' in schema helps), rate limits, authentication needs, error conditions, or what the response structure looks like. For a tool with 7 parameters and no annotations, 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 front-loads the core purpose ('List test results') without unnecessary words. It's appropriately sized for a listing tool, with zero wasted text, making it easy for an agent to parse quickly.

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

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

Given the tool's complexity (7 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits (e.g., pagination, errors), output format, or usage context. While the schema covers many parameters, the description doesn't compensate for the gaps in behavioral transparency or provide enough guidance for effective tool selection.

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

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

The description mentions 'from a build run or build action', which aligns with the 'buildRunId' and 'buildActionId' parameters in the schema, adding some context. However, with 71% schema description coverage, the schema already documents most parameters well (e.g., 'limit', 'sort', 'filter', 'include', 'fields'). The description doesn't add significant meaning beyond what the schema provides, such as explaining parameter interactions or use cases.

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 ('List test results') and the resource source ('from a build run or build action'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'list_ci_build_actions' or 'list_build_runs', which list different resources rather than test results specifically.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a build run/action ID), compare it to similar tools (like 'list_ci_issues' for issues vs. test results), or specify scenarios where it's appropriate. The input schema hints at alternatives via 'provide either buildRunId or buildActionId', but this isn't stated in the description itself.

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. 'Get a list' implies a read-only operation, but it doesn't mention pagination behavior, rate limits, authentication requirements, or what happens when no devices exist. For a tool with 4 parameters and no annotation coverage, this is insufficient behavioral context.

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

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

The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a listing operation and front-loads 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?

For a read-only listing tool with 4 parameters, no output schema, and no annotations, the description provides basic purpose but lacks important context about return format, pagination, error conditions, and relationship to sibling tools. It's minimally adequate but leaves significant gaps for an agent to use the tool 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 description mentions 'all devices' which implies no filtering by default, but doesn't explain the 4 available parameters (limit, sort, filter, fields). With 50% schema description coverage, the schema documents some parameters well but others minimally. The description adds little value beyond what the schema provides, meeting the baseline for moderate 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 clearly states the verb ('Get') and resource ('list of all devices registered to your team'), making the purpose immediately understandable. It doesn't distinguish from sibling tools (like 'list_apps' or 'list_users'), but it's specific enough to understand what the tool does without being tautological.

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 'list_' sibling tools available (like list_apps, list_users, list_beta_groups), there's no indication of when this specific device listing tool is appropriate versus other listing 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves a list but doesn't mention whether it's read-only, paginated, rate-limited, or requires specific permissions. For a list operation with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

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

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

The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action and resource, making it easy to parse quickly. Every word serves a functional purpose in the description.

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 simple list tool with 2 parameters and 100% schema coverage but no annotations or output schema, the description is minimally adequate. It states what the tool does but lacks behavioral context, usage guidance, and output information. The description meets basic requirements but leaves room for improvement given the tool's straightforward nature.

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

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

The description implies a 'groupId' parameter by mentioning 'specific beta group', but doesn't add meaning beyond what the schema already provides (100% coverage). It doesn't explain the 'limit' parameter or provide context like default behavior beyond the schema's documentation. Baseline 3 is appropriate since the schema fully documents parameters.

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 ('Get a list') and resource ('all testers in a specific beta group'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_users' or 'list_devices' which might also involve testers, though the beta group context provides some implicit distinction.

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 sibling tools like 'list_users' or 'list_beta_groups', nor does it specify prerequisites such as needing an existing beta group ID. The context is limited to the beta group scope without further 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?

With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention whether this is a read-only operation, potential side effects, error conditions, or output format, which 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 with zero waste. It's appropriately sized and front-loaded with the core purpose, making it easy for an agent to parse quickly.

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

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

Given the tool's simplicity (one parameter, no output schema, no annotations), the description is minimally adequate but lacks depth. It explains what the tool does but omits behavioral context and usage guidance, which are important even for simple tools.

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 single parameter. The description adds no additional meaning about the parameter beyond what the schema provides, maintaining the baseline score for high schema coverage.

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

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

The description clearly states the verb ('List') and resource ('all available schemes'), specifying the context ('in an Xcode project or workspace'). It distinguishes from siblings by focusing on schemes, but doesn't explicitly differentiate from similar list tools like list_apps or list_bundle_ids beyond the resource type.

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. The description doesn't mention prerequisites, timing, or comparisons to other tools, leaving the agent to infer usage solely from the purpose.

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 only states the basic purpose. It doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what the response format looks like. For a list operation with 4 parameters, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized and 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 has 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how results are structured, or provide context about the App Store Connect team environment. For a list operation with filtering capabilities, more guidance 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 description adds no parameter information beyond what the schema provides. With 75% schema description coverage (3 of 4 parameters have descriptions), the baseline is 3. The description doesn't compensate for the 25% gap or provide additional context about parameter interactions or usage patterns.

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 ('Get a list') and resource ('all users registered on your App Store Connect team'), providing specific verb+resource pairing. However, it doesn't differentiate from sibling tools like 'list_group_testers' or 'list_devices' which also list different types of entities, so it misses full sibling differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or suggest other tools for different scenarios (e.g., filtering users by specific criteria beyond what parameters allow).

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 only states what the tool does ('List all...') without mentioning permissions, rate limits, pagination, response format, or error handling. For a tool with 5 parameters and no output schema, 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, 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 (5 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits, parameter usage, and response handling, making it inadequate for an agent to fully understand how to invoke and interpret results from this tool.

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

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

The description adds no parameter-specific information beyond what's in the input schema. With 60% schema description coverage (3 out of 5 parameters have descriptions), the baseline is 3, as the schema does moderate lifting but the description doesn't compensate for gaps like the 'filter' or 'fields' object details.

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

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

The description clearly states the verb ('List') and resource ('App Store Connect workflows (CI products) and their associated apps'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'list_apps' or 'list_build_runs', which also list resources in the same domain, so it doesn't fully distinguish itself 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. It doesn't mention prerequisites, context, or compare to sibling tools like 'list_apps' or 'list_build_runs', leaving the agent with no usage direction beyond the basic purpose.

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 is a removal (implying mutation/destructive), but doesn't specify whether this requires special permissions, is reversible, has side effects, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it immediately scannable and understandable. Every word earns its place.

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

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

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after removal (e.g., confirmation message, error responses), doesn't mention dependencies or prerequisites, and provides no behavioral context. The agent would need to guess about success criteria and side effects.

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 doesn't add any parameter-specific information beyond what's already in the schema (which has 100% coverage). Both parameters are documented in the schema with clear descriptions. The description implies the parameters are needed but doesn't explain their format, source, or relationships, 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 clearly states the action ('Remove') and the target ('a tester from a beta group'), making the purpose immediately understandable. It doesn't explicitly differentiate from its sibling 'add_tester_to_group', but the verb 'Remove' versus 'Add' provides implicit distinction. The description avoids tautology by specifying what's being removed from what.

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 tester must already be in the group), error conditions, or relationships with other tools like 'list_group_testers' for verification. 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states it's an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that front-loads the core action ('update') and resource. There's zero waste—every word contributes directly to stating the tool's purpose without redundancy or fluff.

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 on behavioral traits (e.g., side effects, error handling), usage context, and expected outcomes. While concise, it doesn't compensate for the missing structured data, leaving the agent with insufficient guidance 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%, with all three parameters well-documented in the schema (localizationId, field with enum values, value). The description adds no additional parameter semantics beyond what's in the schema, such as formatting examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the verb ('update') and resource ('a specific field in an app store version localization'), making the purpose unambiguous. It distinguishes itself from siblings like 'get_app_store_version_localization' by specifying it's an update operation rather than a retrieval. However, it doesn't explicitly differentiate from other update-like tools that might exist in the broader context.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing localization), exclusions (e.g., which fields cannot be updated), or related tools like 'create_app_store_version' or 'list_app_store_version_localizations' for context. Usage is implied through the action but not explicitly framed.

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