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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description does not disclose any behavioral traits such as whether this is a read-only or mutation operation, what permissions are required, how suggestions are generated, or any rate limits. It lacks essential context for safe and effective use.

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

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

The description is a single, efficient sentence with no wasted words. It is appropriately sized and front-loaded, stating the core action and outcome. However, it could be more structured by including key details, but it earns high marks for brevity.

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

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

Given the complexity of analyzing translation context and providing suggestions, with no annotations and no output schema, the description is incomplete. It doesn't explain what 'suggestions' entail, the format of the output, or any behavioral constraints. This leaves significant gaps for the agent to understand the tool's full context.

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

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

The input schema has 100% description coverage, with clear documentation for both parameters ('key' and 'target_locale'). The description does not add any meaning beyond what the schema provides, such as explaining the format of 'key' or valid values for 'target_locale'. Baseline score of 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 'Analyze translation context and provide suggestions' states a general purpose but lacks specificity. It mentions 'translation context' and 'suggestions' but doesn't specify what kind of analysis or suggestions are provided, nor does it differentiate from siblings like 'validate_translations' or 'translate_key'. The description is vague rather than 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. It doesn't mention prerequisites, context for analysis, or comparisons to siblings such as 'validate_translations' or 'translate_key'. There is no explicit or implied usage scenario, leaving the agent without 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?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose whether this is a read-only operation, if it requires specific permissions, what the output format looks like, or if it has performance implications. The description only states what it does, not 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 directly states the tool's purpose without unnecessary words. It's appropriately sized for a tool with clear parameters documented elsewhere.

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 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what constitutes 'missing' or 'outdated', how results are presented, or any behavioral constraints. The agent lacks critical context about what to expect from this operation.

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 all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema descriptions. This meets the baseline of 3 when schema coverage is high.

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

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

The description clearly states the tool's purpose with a specific verb ('identify') and resource ('missing or outdated translations across locales'). It distinguishes itself from siblings like 'validate_translations' (which likely checks correctness) and 'translate_key/namespace' (which perform translation). However, it doesn't explicitly differentiate from 'analyze_translation_context' which might have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when to prefer 'validate_translations' for correctness checks, or when 'analyze_translation_context' might be more appropriate. The agent must infer usage from the purpose 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 states the tool 'gets' and 'detects', implying a read-only operation, but doesn't clarify permissions, rate limits, or what 'detect' entails (e.g., automatic inference vs. explicit retrieval). This leaves significant gaps for a tool that interacts with configuration settings.

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 ('Get current configuration'). It could be slightly more structured by separating the 'detect' aspect, but it avoids waste and is appropriately sized for a simple 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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'configuration' includes (e.g., translation settings, workspace defaults) or what the return format looks like, which is critical for a tool with potential complexity in configuration data.

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

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

The input schema has 100% description coverage, documenting the single parameter 'source' with its enum values and default. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('current configuration'), and it adds scope by mentioning 'workspace settings'. However, it doesn't explicitly differentiate from sibling tools like 'set_workspace_config' or 'analyze_translation_context', 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 sibling tools like 'set_workspace_config' for updates or 'analyze_translation_context' for related configuration analysis, leaving the agent with no context for tool selection.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool saves translations but doesn't reveal critical traits: whether this is a destructive write operation (overwrites existing files), what permissions are required, how errors are handled (e.g., invalid locales), or what happens on success (e.g., confirmation message). The description is minimal and lacks operational 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 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 ('Save'). Every word earns its place, making it easy to parse quickly.

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

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

Given the tool's complexity (a write operation with no annotations and no output schema), the description is insufficiently complete. It doesn't address behavioral risks (e.g., file overwrites), success/failure responses, or integration with sibling tools (e.g., whether to validate first). For a mutation tool in a translation management context, more operational guidance is needed to ensure safe and correct usage.

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 single parameter 'translations' as an array of objects with key, locale, and translation fields. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain format expectations (e.g., locale codes like 'en-US'), validation rules, or batch size limits. Baseline 3 is appropriate given 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 ('Save') and resource ('translations to locale files'), making the purpose immediately understandable. It distinguishes from siblings like 'validate_translations' or 'find_missing_translations' by focusing on persistence rather than analysis or discovery. However, it doesn't specify whether this creates new translations or updates existing ones, 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 like 'translate_key' or 'translate_namespace'. There's no mention of prerequisites (e.g., whether translations must be validated first), nor any indication of when not to use it (e.g., for single translations vs. batches). The context 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 full burden for behavioral disclosure. 'Update' implies a mutation operation, but it doesn't specify permissions required, whether changes are reversible, rate limits, or what happens to existing settings not included in the partial update. This leaves significant gaps for a tool that modifies configuration.

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 wasted words. It's front-loaded with the core action and target, making it easy to parse quickly.

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

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

Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error conditions, or return values, which are critical for safe usage. Sibling tools suggest a translation context, but this isn't leveraged to clarify the tool's role.

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 ('config' as a partial TranslationConfig object and 'scope' with enum values). The description adds no additional parameter semantics beyond what's in the schema, such as examples of config fields or scope implications, meeting 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 ('Update') and the target ('workspace-specific translation settings'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_configuration' or 'save_translations' which might also involve configuration or translation settings.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when-not-to-use scenarios, or how it relates to siblings like 'get_configuration' (for reading) or 'save_translations' (which might overlap in 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions translating a key but does not explain how the translation is performed (e.g., via API, database lookup, or external service), what happens on failure, whether it's idempotent, or any rate limits. The description is minimal and lacks critical behavioral details for a tool with 5 parameters.

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 appropriately sized for its purpose, with no redundant or verbose elements. Every part of the sentence contributes to understanding the 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 (5 parameters, no annotations, no output schema), the description is incomplete. It does not explain the translation process, return values, error handling, or how it integrates with sibling tools. For a tool that likely interacts with a translation system, more context is needed to ensure proper usage and 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?

Schema description coverage is 100%, so the input schema already documents all 5 parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as examples of key formats or locale code standards. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

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

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

The description states the tool's purpose as translating a specific translation key to target language(s), which is clear but vague. It specifies the action (translate) and resource (translation key) but lacks detail on what translation entails or how it differs from sibling tools like translate_namespace. The purpose is understandable but not specific enough to distinguish it 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 does not mention sibling tools like translate_namespace or analyze_translation_context, nor does it specify prerequisites, exclusions, or contextual cues for selection. Usage is implied by the tool name alone, with no explicit instructions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal insight. It states the tool translates keys but doesn't explain how (e.g., via API calls, with rate limits, requiring authentication), what happens on failure, or if it modifies data in-place. This is inadequate for a tool that likely performs write operations, leaving critical behavioral traits unspecified.

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

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

The description is extremely concise—a single, clear sentence that front-loads the core action ('translate all keys') and target ('within a specific namespace/file'). There is no wasted verbiage or redundancy, making it easy to parse quickly.

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

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

Given the complexity of a translation tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral aspects (e.g., side effects, error handling), usage context relative to siblings, and expected outcomes, leaving gaps that could hinder correct tool invocation in a real-world scenario.

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 (mode, namespace, source_locale, target_locales). The description adds no additional semantic context beyond implying 'namespace' refers to a file or grouping, which is already covered in the schema. This meets the baseline for high schema coverage but doesn't enhance understanding.

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

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

The description clearly states the action ('translate') and target ('all keys within a specific namespace/file'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'translate_key' (which translates individual keys) or 'find_missing_translations' (which only identifies gaps), leaving some ambiguity about when to choose this bulk operation over 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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'all keys' but doesn't clarify if this is for batch processing, initial setup, or updates, nor does it reference sibling tools like 'translate_key' for single-key operations or 'find_missing_translations' for detection-only tasks. This lack of context makes it harder for an agent to select the right tool.

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. 'Validate' implies a read-only or analysis operation, but the description doesn't specify if this tool modifies data, requires specific permissions, has side effects, or provides detailed output. It lacks context on what 'quality and consistency' entails, such as error reporting or scoring, making it insufficient for a mutation-aware agent.

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: 'Validate translation quality and consistency'. It is front-loaded with the core purpose, has zero waste, and is appropriately sized for the tool's complexity. Every word earns its place, making it highly concise and well-structured.

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

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

Given the tool has no annotations and no output schema, the description is incomplete. It doesn't explain what 'validate' entails in terms of behavior, output format, or error handling. With 2 parameters and siblings offering related functionality, more context is needed to guide an agent effectively, such as whether this is a read-only check or has implications for translation workflows.

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

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

The input schema has 100% description coverage, with clear documentation for 'checks' and 'target_locales'. The description adds no additional meaning beyond the schema, as it doesn't explain parameter interactions, default behaviors, or examples. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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

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

The description states the tool's purpose as 'Validate translation quality and consistency', which is clear but somewhat vague. It specifies the action (validate) and domain (translations) but doesn't distinguish it from sibling tools like 'analyze_translation_context' or 'find_missing_translations', nor does it specify what resources are being validated. This is adequate but lacks specificity.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'find_missing_translations' and 'analyze_translation_context', it's unclear if this tool is for pre-save validation, post-translation checks, or general quality assurance. There are no explicit when/when-not statements or named alternatives, leaving usage ambiguous.

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