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 disclosure. It mentions 'AI-filtered knowledge' but doesn't explain how this filtering works, what sources are consulted, response format, limitations, or potential side effects. For a tool that presumably queries knowledge bases, this leaves significant behavioral unknowns.

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 communicates the core functionality without unnecessary words. It's appropriately sized for the tool's apparent complexity, though it could potentially benefit from slightly more detail given the lack of annotations.

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 an output schema (which handles return values) and 100% schema coverage for parameters, the description's minimal approach is somewhat acceptable. However, for a tool that presumably provides complex AI-generated advice with no annotations about its behavior, the description feels incomplete - it doesn't explain what 'advanced project guidance' entails or how the AI filtering works.

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 adds no parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate since the schema handles parameter documentation adequately.

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

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

The description clearly states the tool's purpose as providing 'Advanced project guidance using AI-filtered knowledge from .knowledges directory', which includes both the verb ('guidance') and resource/mechanism ('AI-filtered knowledge'). It distinguishes from most siblings by focusing on advice rather than document/index operations, though it doesn't explicitly differentiate from 'ask_user_advice' which also provides advice.

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 this AI-filtered knowledge approach is preferable to other tools like 'search' or 'ask_user_advice', nor does it specify prerequisites or appropriate contexts beyond the vague 'project guidance' scope.

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. It discloses the tool's behavioral purpose (seeking human guidance) but lacks details about implementation specifics like how the request is presented to users, response format expectations, or any limitations. It adequately describes the core behavior but misses operational details.

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

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

The description is perfectly concise with two sentences that directly address purpose and usage guidelines. Every word serves a clear function with zero redundancy, making it easy to parse and understand 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 (5 parameters, no annotations, but with output schema), the description covers the essential purpose and usage context well. However, it could benefit from more behavioral details about how the interaction works since there's no annotation coverage. The existence of an output schema reduces the need to describe return values.

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 5 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for adequate but no 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 tool's purpose with specific verbs ('ask user for advice') and resources ('when agent encounters uncertainty, problems, or needs guidance'). It distinguishes this from sibling tools by focusing on human interaction rather than system operations like 'ask_mcp_advice' or data management tools in the sibling list.

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

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

The description provides explicit guidance on when to use this tool ('when you're unsure about something or need human input to proceed properly'). It implicitly distinguishes from alternatives by focusing on human advice rather than automated solutions, though it doesn't explicitly name alternatives like 'ask_mcp_advice'.

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. It discloses the batch nature, AI enhancement, and comprehensive processing, but doesn't mention important behavioral traits like whether this is a long-running operation, what happens on partial failures, authentication requirements, rate limits, or what 'comprehensive file processing' entails. It provides basic context but misses critical operational details.

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

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

The description is a single, efficient sentence that front-loads the core purpose. It could be slightly more structured by separating the core action from the enhanced features, but it wastes no words and clearly communicates the tool's value proposition 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?

Given the tool's complexity (batch processing with AI enhancement) and 100% schema coverage plus an output schema, the description provides adequate context. It clearly states what the tool does at a high level. The output schema existence means the description doesn't need to explain return values. However, for such a complex operation, more behavioral context would be helpful.

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

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

Schema description coverage is 100%, so the schema already fully documents all 8 parameters. The description adds no specific parameter information beyond what's in the schema. The baseline of 3 is appropriate when the schema does all the parameter documentation work, though the description could have added context about how parameters interact.

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 specific action ('batch index'), target resource ('all documents from a directory into Elasticsearch'), and distinguishes from siblings like 'index_document' (single document) and 'create_index' (empty index). It adds unique value with 'AI-enhanced metadata generation and comprehensive file processing' that differentiates it from simpler indexing 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 implies usage for bulk indexing directory contents with AI enhancement, but doesn't explicitly state when to use this vs alternatives like 'index_document' (single file) or 'create_index' (empty index). It provides context about batch processing but lacks explicit guidance on tool selection criteria 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 mentions AI-generated metadata and formatting, but doesn't cover critical aspects like whether this is a read-only or destructive operation, authentication requirements, rate limits, or what the output looks like. For a creation tool with zero annotation coverage, this leaves significant 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 clearly states the tool's purpose. It's appropriately sized and front-loaded with the core functionality. There's no wasted verbiage, though it could potentially benefit from slightly more detail given 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 the tool's complexity (9 parameters, creation operation) and the presence of an output schema, the description is moderately complete. It covers the basic purpose but lacks behavioral details that would be important for a creation tool. The output schema existence reduces the need to describe return values, but more context about the creation process would be helpful.

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

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

The description adds minimal parameter semantics beyond what the schema provides. It mentions 'AI-generated metadata and formatting' which relates to the 'use_ai_enhancement' parameter, but doesn't explain how parameters interact or provide additional context. With 100% schema description coverage, the baseline is 3 as the schema already documents all parameters well.

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: 'Create a properly structured document template for knowledge base with AI-generated metadata and formatting.' It specifies the verb ('create'), resource ('document template'), and context ('knowledge base'), but doesn't explicitly differentiate from sibling tools like 'create_index' or 'create_index_metadata' which might serve related purposes.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'create_index' or 'index_document', nor does it specify prerequisites or exclusions. Usage is implied through the description 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 mentions the tool creates an index with optional configuration but fails to address critical behavioral aspects like required permissions, whether the operation is idempotent, potential side effects on existing indices, or error conditions. This leaves significant gaps for an AI 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 that front-loads the core action ('Create a new Elasticsearch index') and includes essential details about optional configurations. There is no wasted language, 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 that there is an output schema (which handles return values) and high schema coverage, the description is somewhat complete for basic understanding. However, as a mutation tool with no annotations, it lacks critical behavioral context like permissions or error handling, making it only minimally adequate.

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

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

The schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value by mentioning 'optional mapping and settings configuration', which aligns with the schema but doesn't provide additional semantic context beyond what's in the structured fields.

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 specific action ('Create a new Elasticsearch index') and distinguishes it from sibling tools like 'delete_index' or 'list_indices'. It specifies the resource type (Elasticsearch index) and mentions optional configuration aspects, making the purpose unambiguous.

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 'setup_elasticsearch' or 'create_index_metadata', nor does it mention prerequisites or exclusions. It merely states what the tool does without contextual usage instructions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates metadata documentation but doesn't describe what happens during execution—whether it overwrites existing metadata, requires specific permissions, returns confirmation or error details, or has side effects like indexing changes. This leaves significant gaps 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, well-structured sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action and context, making it easy to parse and understand 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 (9 parameters, creation operation) and the presence of an output schema, the description is minimally adequate. It states what the tool does but lacks behavioral details, usage context, and output expectations. With no annotations and a creation operation, more completeness would be beneficial, but the output schema mitigates some gaps.

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 the input schema provides. Since schema description coverage is 100%, the baseline score is 3. The description doesn't explain parameter relationships, dependencies, or usage examples, so it doesn't compensate for any gaps but doesn't need to given the comprehensive schema.

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

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

The description clearly states the tool's purpose: 'Create metadata documentation for an Elasticsearch index to ensure proper governance and documentation.' It specifies the verb ('create'), resource ('metadata documentation'), and context ('Elasticsearch index'), but doesn't explicitly differentiate from sibling tools like 'update_index_metadata' or 'delete_index_metadata'.

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 'update_index_metadata' for modifying existing metadata or 'delete_index_metadata' for removal, nor does it specify prerequisites or appropriate contexts for creation versus other 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 full burden but offers minimal behavioral insight. It mentions 'comprehensive options' but doesn't detail critical behaviors like permissions needed, impact on system performance during backup, whether snapshots are incremental, or error handling. This is inadequate for a mutation tool with complex operations.

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

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

The description is a single, efficient sentence that front-loads the core purpose. It avoids redundancy but could be slightly more structured by separating functional intent from capability notes.

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, mutation operation) and lack of annotations, the description is insufficiently complete. It doesn't address behavioral aspects like side effects or error cases, though the presence of an output schema mitigates some gaps by handling return values externally.

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 parameters are well-documented in the schema. The description adds little beyond implying scope ('Elasticsearch indices') and hinting at flexibility ('comprehensive options'), but doesn't clarify parameter interactions or provide examples, 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 ('Create a snapshot') and resource ('Elasticsearch indices'), specifying it's a backup operation. It distinguishes from sibling 'restore_snapshot' by focusing on creation rather than restoration, though it doesn't explicitly contrast with other backup-related 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?

No explicit guidance on when to use this tool versus alternatives. While it mentions 'comprehensive options and repository management,' it doesn't specify scenarios, prerequisites, or contrast with sibling tools like 'list_snapshots' or 'restore_snapshot' for backup workflows.

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 performs a deletion but omits critical details: whether this is irreversible, what permissions are required, how errors are handled (e.g., if the document doesn't exist), or any rate limits. For a destructive operation, 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, direct sentence with zero wasted words. It front-loads the core action ('Delete') and efficiently specifies the target and method ('a document from Elasticsearch index by document ID'), making it easy to parse and understand 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 complexity (a destructive operation with 2 parameters), the description is minimally complete but lacks depth. While an output schema exists (reducing need to explain return values), the absence of annotations and insufficient behavioral details leaves gaps in understanding the tool's full impact and usage context.

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

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

Schema description coverage is 100%, with both parameters (index and doc_id) clearly documented in the schema. The description adds no additional semantic context beyond what the schema provides (e.g., format examples or constraints), so it meets the baseline for adequate but not enhanced 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 specific action ('Delete') and resource ('a document from Elasticsearch index by document ID'), distinguishing it from sibling tools like delete_index (which deletes entire indices) or get_document (which retrieves documents). It precisely communicates the tool's function without ambiguity.

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 delete_index or batch operations. It lacks context about prerequisites (e.g., needing an existing index/document), exclusions, or typical scenarios for document deletion, leaving the agent to 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 the action is 'permanent' which is crucial context, but doesn't mention required permissions, whether the operation is reversible, potential impacts on dependent resources, error conditions, or confirmation requirements. For a destructive 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 communicates the core purpose with zero wasted words. It's appropriately sized for a single-parameter tool and front-loads the essential information about what the tool does and its permanent nature.

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 destructive operation with no annotations but with an output schema (which presumably handles return values), the description provides the minimum viable information about what the tool does. However, for a permanent deletion tool, it should ideally include more warnings about data loss, prerequisites, or confirmation requirements to be considered complete.

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

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

The schema description coverage is 100% (the single parameter 'index' is fully described in the schema as 'Name of the Elasticsearch index to delete'), so the baseline is 3. The description doesn't add any additional parameter semantics beyond what the schema already provides, such as index naming conventions, wildcard support, or validation rules.

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 specific action ('Delete') and target resource ('an Elasticsearch index and all its documents'), distinguishing it from sibling tools like delete_document (which deletes individual documents) and delete_index_metadata (which deletes metadata only). The inclusion of 'permanently' adds important scope 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?

The description implies this should be used for deleting entire indices rather than individual documents (contrasted with delete_document), but doesn't explicitly state when to use this vs. alternatives like delete_index_metadata or provide guidance on prerequisites, recovery options, or warnings about data loss. The context is implied but not explicitly articulated.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Delete' implies a destructive operation, the description doesn't clarify whether this is reversible, what permissions are required, what happens to the index itself (just metadata), or any rate limits/constraints. This is inadequate for a destructive tool with zero annotation coverage.

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

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

The description is a single, efficient sentence that directly states the tool's purpose with zero wasted 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 this is a destructive operation with no annotations but has an output schema (which handles return values), the description is minimally adequate. However, for a delete operation that could have significant consequences, more context about what 'metadata documentation' entails and how this differs from deleting the index itself 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 fully documents the single parameter 'index_name'. The description adds no additional meaning about parameter usage, constraints, or examples beyond what's in the schema. With high schema coverage, baseline 3 is appropriate.

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

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

The description clearly states the action ('Delete') and target ('metadata documentation for an Elasticsearch index'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this from sibling tools like 'delete_index' or 'update_index_metadata', which would require more specific 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. With sibling tools like 'delete_index' (deletes the entire index) and 'update_index_metadata' (modifies metadata), there's clear potential for confusion, but the description offers no comparison or context for choosing between them.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks status and provides detailed configuration information, but doesn't clarify if this is a read-only operation, what permissions are needed, whether it affects system state, or how it handles errors. For a status-checking 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 clearly conveys the tool's purpose without unnecessary words. It is front-loaded with the core action and resources, making it easy to parse. Every part of the sentence earns its place by specifying what is checked and what information is provided.

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

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

Given the tool's complexity (simple status check with 0 parameters), the description is adequate but incomplete. It lacks behavioral details (e.g., read-only nature, error handling) and usage context, which are important since no annotations are provided. However, the presence of an output schema means the description doesn't need to explain return values, keeping it from being lower.

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

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

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, and it appropriately doesn't mention any. Since there are no parameters, the baseline is high, but it doesn't reach 5 as it could have noted the lack of parameters explicitly, though this isn't required.

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: 'Check status of Elasticsearch and Kibana containers with detailed configuration information.' It specifies the verb ('check status'), resources ('Elasticsearch and Kibana containers'), and scope ('detailed configuration information'). However, it doesn't explicitly differentiate from sibling tools like 'server_status' or 'get_config', which might have overlapping functionality, 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. It doesn't mention prerequisites, timing, or comparisons to sibling tools such as 'server_status' or 'get_config', leaving the agent to infer usage context. This lack of explicit direction reduces its effectiveness in tool selection.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'formatted display,' hinting at how the output is presented, but doesn't disclose critical behaviors like whether this is a read-only operation, potential errors (e.g., if config.json is missing), or performance aspects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that front-loads the key action ('Get the complete configuration') and adds useful detail ('from config.json file with formatted display'). There is no wasted verbiage, making it highly concise and well-structured for quick understanding.

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

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

Given the tool's simplicity (0 parameters, output schema exists), the description is reasonably complete. It specifies the source ('config.json file') and output format ('formatted display'), and the output schema will detail return values. However, for a tool with no annotations, it could better address behavioral aspects like error handling or read-only nature to enhance completeness.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details beyond the schema, but with no parameters, this is acceptable. It implies the tool retrieves configuration without requiring inputs, which aligns with the empty 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 ('Get') and resource ('complete configuration from config.json file'), specifying it retrieves the entire configuration. It distinguishes from siblings like 'reload_config' or 'validate_config' by focusing on retrieval rather than modification or validation. However, it doesn't explicitly differentiate from 'update_config' or 'reset_config' beyond the verb choice.

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, such as whether the config file must exist, or compare it to siblings like 'reload_config' (which might refresh config) or 'validate_config' (which checks validity). Usage is implied by the verb 'Get' 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 but only states the basic operation. It doesn't disclose behavioral traits like error handling (e.g., if document doesn't exist), performance characteristics, authentication needs, or rate limits. For a read operation with zero annotation coverage, this is inadequate.

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

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

Single sentence with zero waste - every word contributes to understanding the tool's purpose. Front-loaded with the core action and resource.

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 2 parameters with full schema coverage and an output schema exists, the description is minimally complete for purpose. However, as a read operation with no annotations, it should ideally mention what happens on failure (e.g., document not found) or return format 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 fully documents both parameters. The description adds no additional meaning beyond what the schema provides (e.g., no examples, format details, or constraints). Baseline 3 is appropriate when schema does all the work.

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 specific action ('retrieve'), resource ('document from Elasticsearch index'), and method ('by document ID'). It distinguishes from siblings like search (which queries), list_indices (which lists indices), and delete_document (which removes).

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 you need a specific document by ID, but doesn't explicitly state when to use alternatives like search (for queries) or list_indices (for index contents). 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: 'smart duplicate prevention' and 'intelligent document ID generation' (which imply AI-driven logic), validation errors to avoid, and the recommendation to use another tool first. However, it doesn't explicitly mention mutation effects (e.g., data persistence) or error-handling specifics, leaving some 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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second sentence provides a crucial recommendation. Both sentences earn their place by adding value—no wasted words or redundancy. The structure is clear and efficient.

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

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

Given the tool's complexity (7 parameters, mutation operation) and no annotations, the description does well by covering purpose, usage guidelines, and key behaviors. However, with an output schema present, it doesn't need to explain return values. It could be more complete by explicitly stating it's a write operation or mentioning error cases, but it's largely adequate for the 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 7 parameters thoroughly. The description adds minimal value beyond the schema: it mentions 'smart duplicate prevention' (hinting at 'check_duplicates' and 'use_ai_similarity') and 'intelligent document ID generation' (related to 'doc_id'), but doesn't provide additional syntax or format details. 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 tool's purpose with specific verbs ('index a document into Elasticsearch') and resources ('document'), distinguishing it from siblings like 'create_document_template' (preparation) and 'delete_document' (removal). It explicitly mentions key features like 'smart duplicate prevention' and 'intelligent document ID generation' that differentiate its 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 explicit guidance on when to use this tool vs. alternatives: it recommends using 'create_document_template' first to avoid validation errors, which directly addresses when to use a sibling tool. It also includes a tip about setting 'force_index' to True to avoid multiple tool calls, offering practical usage advice.

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. It discloses the tool lists indices with statistics (document count and size), which is useful behavioral context. However, it does not mention potential side effects, permissions required, or rate limits, leaving gaps for a read operation.

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

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

The description is a single, efficient sentence that front-loads the purpose ('List all available Elasticsearch indices') and adds key details ('with document count and size statistics'). Every word earns its place with zero waste.

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

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

Given the tool's low complexity (0 parameters, read-only operation) and the presence of an output schema (which handles return values), the description is mostly complete. It specifies what is listed and what statistics are included, but could benefit from more behavioral context like permissions or limitations.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents inputs. The description adds no parameter info, which is acceptable here as there are no parameters to explain. Baseline is 4 for zero parameters, as no additional semantics are needed.

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

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

The description clearly states the verb ('List') and resource ('all available Elasticsearch indices'), specifying the exact scope. It distinguishes from siblings like 'elasticsearch_status' (general status) and 'list_snapshots' (different resource) by focusing on indices with statistics.

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 needing to enumerate indices with metadata, but does not explicitly state when to use it versus alternatives like 'elasticsearch_status' for broader system info or 'search' for querying data. It provides clear context but lacks explicit exclusions or named alternatives.

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 'detailed information and status' but doesn't specify what that includes (e.g., snapshot names, sizes, states, timestamps) or behavioral traits like pagination, rate limits, error handling, or authentication needs. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond basic listing.

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 ('List all snapshots') and adds relevant details ('with detailed information and status'). There's no wasted text, and it's appropriately sized for the tool's complexity. However, it could be slightly more structured by separating key points, but it remains clear and direct.

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 (2 parameters, no annotations, but with an output schema), the description is adequate but incomplete. It covers the basic purpose but lacks usage guidelines, detailed behavioral context, and parameter insights. The presence of an output schema means the description doesn't need to explain return values, but it should still address when and how to use the tool effectively, which it falls short on.

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 ('repository' and 'verbose') well-documented in the input schema. The description adds minimal value beyond the schema, as it doesn't explain parameter interactions (e.g., how 'verbose' affects output) or provide additional context like example repository names. Baseline 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate with extra insights.

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 ('snapshots in an Elasticsearch repository'), specifying the scope ('all snapshots') and additional details ('with detailed information and status'). It distinguishes from siblings like 'create_snapshot' and 'restore_snapshot' by focusing on listing rather than creating or restoring. However, it doesn't explicitly differentiate from other list tools (e.g., 'list_indices'), which slightly limits sibling 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 prerequisites (e.g., repository existence), exclusions (e.g., when not to use it), or comparisons with related tools like 'list_indices' or 'elasticsearch_status'. Usage is implied by the action but lacks explicit context for agent decision-making.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool reloads and reinitializes components, implying a system-wide impact, but doesn't disclose critical details like whether this causes service interruption, requires specific permissions, has side effects on existing operations, or what 'reinitialize' entails.

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 ('reload configuration') and provides essential context ('from config.json file', 'reinitialize all components with updated settings'). Every word earns its place with no redundancy.

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

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

Given this is a system reconfiguration tool with no annotations but with an output schema (which handles return values), the description is minimally adequate. It explains what the tool does but lacks important context about behavioral impact, safety considerations, and differentiation from sibling tools like 'reset_config'.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description appropriately doesn't add parameter information beyond what's already covered, maintaining a baseline score of 4 for zero-parameter tools.

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

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

The description clearly states the tool's purpose with specific verbs ('reload configuration', 'reinitialize all components') and identifies the resource ('config.json file'). It distinguishes from siblings like 'get_config' (read-only) and 'update_config' (modify config), but doesn't explicitly mention these distinctions in the text.

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

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

No guidance is provided about when to use this tool versus alternatives like 'reset_config' or 'update_config'. The description implies usage after config file changes but doesn't specify prerequisites, timing considerations, 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 that the tool 'overwrites current config', indicating a destructive mutation, which is useful context. However, it lacks details on permissions required, error handling, or confirmation steps, leaving gaps in behavioral understanding 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 that front-loads the core action ('Reset config.json to defaults from config.default.json') and adds clarifying details ('manual reset - overwrites current config') without any wasted words. Every part of the sentence contributes to understanding the tool's purpose and behavior.

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

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

Given the tool's complexity (a destructive reset operation), the description is reasonably complete: it explains what the tool does and its overwriting behavior. With an output schema present, the description does not need to detail return values. However, for a mutation tool with no annotations, it could benefit from more context on side effects or safety warnings.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description does not add parameter-specific information, but this is appropriate given the lack of parameters. A baseline score of 4 is applied as it meets expectations for a parameterless tool.

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

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

The description clearly states the specific action ('Reset config.json to defaults from config.default.json') and resource ('config.json'), distinguishing it from sibling tools like 'update_config' or 'reload_config'. It explicitly mentions 'manual reset - overwrites current config', which clarifies the operation's nature.

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

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

The description implies usage context by specifying 'manual reset' and that it 'overwrites current config', suggesting it should be used when reverting to defaults is needed. However, it does not explicitly state when to use this tool versus alternatives like 'update_config' or 'reload_config', nor does it provide exclusions or prerequisites.

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 hints at 'comprehensive options and conflict resolution' but doesn't disclose critical behavioral traits: whether this is a destructive operation (likely yes, as it overwrites indices), permission requirements, rate limits, error handling, or what 'conflict resolution' entails. For a mutation tool with zero annotation coverage, this is a significant gap.

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

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

The description is a single, efficient sentence that front-loads the core action. However, 'comprehensive options and conflict resolution' is vague and doesn't earn its place clearly—it could be more specific or omitted for brevity. Overall, it's concise but with minor 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 high schema coverage (100%) and an output schema (implied by context signals), the description doesn't need to detail parameters or return values. However, for a complex, likely destructive tool with no annotations, it should better address behavioral aspects like safety, prerequisites, and error handling. It's minimally adequate but leaves gaps in critical 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 8 parameters thoroughly. The description adds minimal value beyond implying 'comprehensive options' (which the schema details) and 'conflict resolution' (unclear how it relates to parameters like 'rename_pattern' or 'ignore_unavailable'). 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 action ('restore indices from an Elasticsearch snapshot') and resource ('indices', 'snapshot'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'create_snapshot' or 'list_snapshots' beyond the obvious verb difference, missing an opportunity to clarify its unique role in the snapshot management workflow.

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 mentions 'comprehensive options and conflict resolution' but doesn't specify scenarios, prerequisites (e.g., snapshot must exist), or exclusions (e.g., cannot restore while indexing). With siblings like 'create_snapshot' and 'list_snapshots', clear usage context is lacking.

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

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

No annotations are provided, so the description carries full burden. It mentions 'advanced filtering, pagination, and time-based sorting capabilities' but doesn't disclose critical behavioral traits like whether this is a read-only operation, potential performance impacts, rate limits, authentication requirements, or what happens when no results are found. The description is insufficient for a mutation-sensitive 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 that front-loads the core purpose. It mentions three key capabilities concisely without unnecessary elaboration. However, it could be slightly more structured by separating purpose from capabilities.

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 8 parameters, no annotations, but has an output schema, the description is minimally adequate. The output schema existence means the description doesn't need to explain return values, but for a search tool with many parameters and no safety annotations, the description should provide more behavioral context about how searches work and their limitations.

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 8 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters (e.g., date_from/date_to vs time_period) or provide usage examples. 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 tool searches documents in Elasticsearch with specific capabilities (advanced filtering, pagination, time-based sorting). It uses a specific verb ('search') and resource ('documents in Elasticsearch index'), but doesn't explicitly differentiate from sibling tools like 'get_document' or 'list_indices' which might serve different purposes.

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

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

No guidance is provided on when to use this tool versus alternatives. The description mentions capabilities but doesn't specify scenarios where this tool is preferred over other search-related tools or when it should not be used. There's no mention of prerequisites or constraints.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions what information is returned but doesn't describe important traits like whether this is a read-only operation (implied but not stated), whether it requires authentication, potential rate limits, or what 'comprehensive system information' includes. 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 front-loads the core purpose. Every word contributes meaning without redundancy. It's appropriately sized for a simple status-checking tool with one optional parameter.

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), 100% schema coverage, and the presence of an output schema (which means the description doesn't need to explain return values), the description is reasonably complete. It clearly states what the tool does and what information it provides. The main gap is the lack of behavioral context, but the output schema helps compensate for this.

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

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

The input schema has 100% description coverage, with the single parameter 'check_updates' clearly documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema. According to the 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 tool's purpose with specific verbs ('check', 'get') and resources ('server status', 'version', 'available updates', 'system information'). It distinguishes from obvious siblings like 'elasticsearch_status' by focusing on the server itself rather than a specific component. However, it doesn't explicitly differentiate from all potential status-related tools in the list.

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

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

The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, timing considerations, or comparison to similar tools like 'elasticsearch_status' or 'get_config'. The agent must infer usage context solely from the tool name and 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 and discloses key behavioral traits: it performs an upgrade (implying mutation), includes automatic configuration backup and restoration (safety feature), and specifies installation method ('via uvx'). However, it doesn't mention potential side effects, permissions needed, or 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, efficient sentence that front-loads the core action ('Upgrade this MCP server') and includes only essential qualifying details. Every word earns its place with no 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 the tool's complexity (a server upgrade operation), no annotations, and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the what, how ('via uvx'), and safety features ('automatic configuration backup and restoration'), though it could benefit from more behavioral context like prerequisites or risks.

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

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

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter details (none exist), which is appropriate, earning a baseline score above 3 due to the lack of 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 ('upgrade') and target resource ('this MCP server'), with specific implementation details ('when installed via uvx'). However, it doesn't explicitly distinguish this tool from potential sibling upgrade tools (none are listed in siblings, but the distinction isn't made).

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

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

The description implies usage context ('when installed via uvx') but doesn't provide explicit guidance on when to use this tool versus alternatives, prerequisites, or exclusions. No sibling tools appear to be direct alternatives, so the implied context is adequate but not comprehensive.

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

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

With no annotations provided, the description carries full burden but lacks critical behavioral details. It mentions 'force recreate' as an option but doesn't disclose potential destructive effects, permission requirements, side effects like data loss, or runtime characteristics. This is inadequate for a setup tool that likely involves system changes.

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 mentions key options without unnecessary words. Every element serves a purpose, making it optimally concise for the information conveyed.

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 an output schema (which handles return values) and 100% schema coverage for parameters, the description is moderately complete. However, as a setup tool with no annotations, it should ideally include more behavioral context about system impact and dependencies to be fully helpful for 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%, so the schema already documents both parameters fully. The description adds minimal value by naming 'Kibana' and 'force recreate' but doesn't provide additional context beyond what's in the schema descriptions. 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 ('Auto-setup') and resource ('Elasticsearch using Docker'), and mentions optional components ('Kibana') and behaviors ('force recreate'). However, it doesn't explicitly differentiate from sibling tools like 'elasticsearch_status' or 'server_status' that might check rather than setup, leaving some ambiguity.

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 initial setup or reconfiguration with optional features, but provides no explicit guidance on when to use this tool versus alternatives like 'server_upgrade' or 'reset_config', nor any prerequisites or exclusions. This leaves the agent guessing about appropriate contexts.

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 an update operation (implying mutation) but doesn't mention permissions required, whether changes are reversible, side effects, or how it interacts with tools like 'reload_config'. For a configuration mutation tool, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that immediately conveys the core functionality. It's front-loaded with the main purpose and mentions both operation modes without unnecessary elaboration. Every word earns its place.

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

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

Given this is a mutation tool with no annotations but with 100% schema coverage and an output schema (implied by 'Has output schema: true'), the description is minimally adequate. However, for a configuration update operation that could have significant system impact, more behavioral context would be helpful despite the structured data coverage.

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 thoroughly. The description adds minimal value by hinting at the two usage modes (section-specific vs full replacement), which aligns with the schema's structure but doesn't provide additional semantic context beyond what's in the parameter descriptions.

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 ('configuration'), and specifies two modes: 'section-specific changes' and 'full configuration replacement'. This distinguishes it from sibling tools like 'get_config' or 'reset_config', though it doesn't explicitly name those 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 implies usage context by mentioning two modes (section-specific vs full replacement), but doesn't provide explicit guidance on when to choose one over the other or mention related tools like 'reset_config' or 'reload_config'. The agent must infer usage from the parameter descriptions.

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 'Update' implying a mutation, but doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or what the output contains. The description adds minimal 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, efficient sentence that front-loads the core action and resource. There is zero waste or redundancy, making it appropriately concise 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 the mutation nature, 9 parameters, and no annotations, the description is incomplete—it lacks behavioral context and usage guidance. However, the presence of an output schema reduces the need to explain return values, and the schema covers parameters well, making it minimally adequate but with clear gaps.

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 9 parameters. The description adds no additional meaning about parameters beyond implying metadata fields can be updated, which is already clear from 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 action ('Update') and resource ('existing metadata documentation for an Elasticsearch index'), making the purpose evident. It distinguishes from siblings like 'create_index_metadata' by specifying 'existing' metadata, but doesn't explicitly contrast with other update tools like 'update_config'.

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 index), exclusions, or compare with siblings like 'create_index_metadata' for new metadata or 'update_config' for different settings.

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 'comprehensive error reporting', which hints at output behavior, but doesn't specify what happens if validation fails (e.g., returns errors vs. throws exceptions), whether it's read-only or has side effects, or any performance considerations. This leaves significant gaps for a validation 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 front-loads the core purpose ('Validate configuration object structure, types, and values') and adds value with 'comprehensive error reporting'. There is no wasted text, making it highly concise and well-structured for quick understanding.

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 (validation with error reporting), 100% schema coverage, and the presence of an output schema, the description is reasonably complete. It covers what the tool does and hints at output behavior. However, it could improve by addressing usage context or behavioral details, especially since no annotations are provided to fill those gaps.

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 'config' well-documented in the schema as 'Configuration object to validate. If not provided, validates current config'. The description adds no additional parameter semantics beyond this, such as examples of valid config structures or validation rules. Baseline 3 is appropriate since 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 tool's purpose: 'Validate configuration object structure, types, and values with comprehensive error reporting.' It specifies the verb (validate), resource (configuration object), and scope (structure, types, values, error reporting). However, it doesn't explicitly differentiate from sibling tools like 'get_config' or 'update_config', 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, such as needing a config object to validate, or compare it to related tools like 'reload_config' or 'reset_config'. Without such context, users might struggle to choose the right tool for validation tasks.

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 validates and provides guidance, but doesn't specify whether it's read-only, what permissions are required, how validation errors are reported, or if it modifies the document. This leaves significant gaps for a validation 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 front-loads the core purpose without unnecessary words. It directly communicates the tool's function in a compact form.

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 an output schema and high schema coverage, the description is minimally adequate. However, as a validation tool with no annotations, it lacks details on behavioral aspects like error handling or security requirements, leaving room for improvement in 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 schema description coverage is 100%, with the parameter 'document' fully described in the schema. The description adds minimal value beyond this, mentioning 'document structure' and 'knowledge base schema' but not elaborating on format expectations or validation criteria beyond what the schema implies.

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: 'Validate document structure against knowledge base schema and provide formatting guidance.' It specifies the verb (validate) and resource (document structure), though it doesn't explicitly differentiate from sibling tools like 'validate_config' or 'get_document' beyond the schema focus.

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, such as needing an existing knowledge base schema, or compare it to siblings like 'validate_config' or 'create_document_template' for related tasks.

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