Lenses MCP Server

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific resources like topics, connectors, or environments, but there is some overlap between tools like get_topic, get_topic_metadata, and get_topic_partitions, which could cause confusion about which to use for specific topic details. The descriptions help clarify, but the boundaries are not always perfectly clear.
Naming Consistency5/5
Tool names follow a consistent snake_case pattern with clear verb_noun structures throughout, such as create_topic, list_consumer_groups, and update_dataset_topic_description. There are no deviations in naming conventions, making the set predictable and easy to navigate.
Tool Count2/5
With 42 tools, the count is excessive for typical MCP server scope, leading to potential cognitive overload and inefficiency. While the domain is broad (Kafka and Lenses management), many tools could be consolidated or omitted without losing functionality, making the set feel heavy and unwieldy.
Completeness5/5
The tool set provides comprehensive coverage for managing Lenses environments, Kafka topics, connectors, SQL processors, and consumer groups, including full CRUD operations, health checks, and advanced features like message resending and configuration validation. No significant gaps are apparent for the stated domain.
Average 3.1/5 across 42 of 42 tools scored. Lowest: 1/5.
See the Tool Scores section below for per-tool breakdowns.
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}
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a delete operation (implying mutation/destruction) but doesn't clarify critical aspects: whether this is irreversible, what permissions are required, if there are rate limits, what happens to consumer group state after deletion, or what format the 'result' return takes. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with clear sections (purpose, args, returns) in just four sentences. Each sentence serves a distinct purpose: stating the action, listing parameters, and describing the return. There's no redundant information, though the parameter explanations are overly brief given the 0% schema coverage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a destructive operation with 3 parameters (0% schema coverage) but with an output schema present, the description is minimally adequate. The output schema means return values don't need explanation, but the description lacks crucial context for a delete operation: no warnings about irreversibility, no permission requirements, no examples of offset objects. It meets basic requirements but leaves significant gaps for safe usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists the three parameters with brief labels but provides no semantic context: 'environment' (what environments exist?), 'group_id' (format/constraints?), 'offsets' (structure of 'topic-partition objects'?). The description adds minimal value beyond parameter names, failing to explain what these parameters mean or how they should be used.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete offsets') and target ('for a consumer group topic-partition tuples'), making the purpose immediately understandable. It distinguishes from sibling tools like 'delete_consumer_group' (which deletes the entire group) and 'update_consumer_group_offsets' (which updates rather than deletes offsets). However, it doesn't specify the exact resource being deleted (offsets for specific partitions) with maximum precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 the consumer group to exist), when-not-to-use scenarios (e.g., if offsets need preservation), or comparisons to similar tools like 'delete_consumer_group_topic_partition_offset' (which appears to handle single offsets). The agent receives no usage context beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Update' implies mutation, it doesn't specify whether this operation is destructive, requires specific permissions, has rate limits, or what happens to existing offsets not mentioned. The description mentions it returns 'The result of the update operation' but doesn't explain what that result contains or format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence serves a purpose, though the parameter explanations could be more informative. The formatting is clean and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 3 parameters, 0% schema coverage, no annotations, but has an output schema, the description is minimally adequate. The presence of an output schema reduces the need to document return values, but the description lacks important context about the mutation's behavior, parameter details, and differentiation from sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists the three parameters but provides minimal semantic context: 'environment' is just 'The environment name', 'group_id' is 'The ID of the consumer group', and 'offsets' is 'A list of topic-partition offset objects' without explaining what those objects contain or their expected structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update the offset') and target ('for a consumer group topic-partition tuples'), providing specific verb+resource. However, it doesn't explicitly distinguish this tool from its sibling 'update_consumer_group_topic_partition_offset', which appears to be a more targeted version of the same operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'update_consumer_group_topic_partition_offset' or 'delete_consumer_group_offsets'. There's no mention of prerequisites, typical use cases, or when this batch update approach is preferable to single-partition updates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 a connector and returns the created object, but lacks details on permissions required, whether this is a mutating operation, potential side effects (e.g., impact on clusters), error conditions, or rate limits. For a creation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses minimal sentences. It front-loads the purpose and efficiently documents parameters. However, the 'Args' and 'Returns' labels are slightly redundant with the schema and output schema, and some sentences could be more concise (e.g., 'The created connector object' is vague).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, nested objects, no annotations) and the presence of an output schema, the description is partially complete. It covers the basic purpose and parameters but lacks behavioral context, usage guidelines, and detailed parameter semantics. The output schema reduces the need to explain return values, but overall completeness is moderate with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'environment: The environment name'), adding basic semantics beyond the schema's titles. However, it doesn't elaborate on format constraints, valid values, or how 'configuration' should be structured, leaving gaps for a tool with nested objects.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'Creates a new Kafka connector' with a specific verb ('Creates') and resource ('Kafka connector'). It distinguishes from siblings like 'delete_kafka_connector' or 'list_kafka_connectors' by specifying creation. However, it doesn't explicitly differentiate from 'validate_connector_configuration' which might be a prerequisite.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether 'validate_connector_configuration' should be used first), exclusions, or comparisons to sibling tools like 'create_sql_processor' or 'create_topic'. Usage is implied only by the tool name and purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Delete a consumer group' but doesn't disclose critical behavioral traits such as whether this is destructive, irreversible, requires specific permissions, has side effects, or what happens to associated data. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core action. The Args and Returns sections are structured, but the Returns statement ('The result of the delete operation') is vague and could be more informative, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a deletion operation with no annotations and an output schema (implied by 'Has output schema: true'), the description is moderately complete. It covers the basic action and parameters but lacks behavioral context and detailed usage guidelines, which are crucial for safe tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics by naming the parameters ('environment' and 'group_id') and briefly describing them, but it doesn't explain format, constraints, or examples. This partially compensates but leaves significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Delete') and resource ('a consumer group'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'delete_consumer_group_offsets' or 'delete_consumer_group_topic_partition_offset', which also delete aspects of consumer groups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'delete_consumer_group_offsets' and 'delete_consumer_group_topic_partition_offset', the description lacks context on whether this deletes the entire group or specific parts, leaving the agent uncertain about tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'Deletes' implies a destructive mutation, it doesn't disclose critical behavioral traits: whether deletion is permanent/reversible, what permissions are required, if it affects related resources, or any rate limits. The description only states the basic action without safety or 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with a clear purpose statement followed by Args and Returns sections. However, the Args section merely repeats parameter names without adding semantic value, and the structure could be more front-loaded with critical behavioral information instead of basic parameter listing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, 3 undocumented parameters, and an output schema that presumably documents the return format, the description is incomplete. It lacks essential context: prerequisites, irreversible consequences, error conditions, and differentiation from sibling deletion tools. The output schema reduces need to explain returns, but other gaps remain significant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides only parameter names and types without meaning. The description adds minimal value by listing parameters in the Args section but doesn't explain what environments, clusters, or connectors are, their formats, or how to identify them. This partially compensates but leaves semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Deletes') and resource ('a Kafka connector'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like delete_sql_processor or delete_consumer_group, which would require mentioning it's specifically for Kafka connectors rather than other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 to identify the connector first via list_kafka_connectors), when deletion is appropriate, or what happens after deletion. With multiple deletion tools in the sibling list, this lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 is destructive ('Removes'), which is clear, but lacks critical details: whether deletion is irreversible, if it requires specific permissions, what happens to associated resources, or any rate limits. The description adds minimal value beyond the obvious destructive nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first. The Args and Returns sections are structured clearly, though they could be more integrated. Every sentence earns its place, but minor improvements in flow (e.g., merging sections) could enhance readability without adding waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation with 2 parameters), no annotations, and an output schema (which covers return values), the description is minimally adequate. It covers the basic action and parameters but lacks context on behavioral risks, usage prerequisites, and error handling. The output schema reduces the burden, but more guidance is needed for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds basic semantics by naming the parameters ('environment' and 'sql_processor_id') and implying their roles, but doesn't explain format (e.g., what constitutes a valid environment name or ID), sources (e.g., from 'list_sql_processors'), or constraints. It compensates partially but not fully for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Removes') and resource ('an existing SQL processor'), making it immediately understandable. It distinguishes from siblings like 'create_sql_processor' by focusing on deletion rather than creation. However, it doesn't explicitly differentiate from other deletion tools like 'delete_kafka_connector' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the SQL processor must be stopped first), nor does it reference sibling tools like 'list_sql_processors' for selection or 'get_sql_processor' for verification. Usage is implied through the action but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves metrics (implying read-only), but doesn't disclose behavioral traits such as authentication needs, rate limits, error conditions, or whether it's safe for frequent use. The mention of 'ranged metrics' hints at date-based filtering, but this isn't elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose, followed by structured sections for Args and Returns. However, the Args section repeats parameter names without adding much value beyond what's implied, and the Returns section could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no annotations, but with an output schema), the description is moderately complete. It covers the purpose and parameters, and the output schema handles return values, but it lacks usage guidelines and detailed behavioral context, which are important for a tool in a server with many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics: it names the parameters ('environment' and 'entity_name') and loosely describes them ('The environment name' and 'The dataset's entity name'), but doesn't explain formats, constraints, or examples. This partially compensates but leaves gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get ranged metrics for a dataset's messages.' It specifies the verb ('Get') and resource ('dataset's messages'), and the 'ranged metrics' adds specificity. However, it doesn't explicitly differentiate from sibling tools like 'get_dataset' or 'list_datasets', which might retrieve different aspects of datasets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'get_dataset' or 'list_datasets', nor does it specify prerequisites or exclusions. 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves information, implying a read-only operation, but does not disclose behavioral traits like authentication needs, rate limits, error conditions, or whether it requires specific permissions. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the main purpose, followed by structured sections for Args and Returns. Each sentence adds value, with no wasted words, though it could be slightly more detailed without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 has an output schema), the description is somewhat complete. It covers the purpose and parameters briefly, and the output schema likely handles return values, but it lacks behavioral context and usage guidelines, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description lists parameters in the Args section with brief names but adds minimal semantics beyond the schema's titles. It partially compensates by indicating what the parameters represent, but does not explain format, constraints, or examples, leaving gaps in understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'Retrieve information about a specific topic,' which is a specific verb (retrieve) and resource (topic). It distinguishes from siblings like get_topic_metadata or get_topic_partitions by focusing on comprehensive topic details, though the distinction could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like get_topic_metadata or get_topic_partitions. The description lacks context on prerequisites, such as needing an existing topic, and does not mention any exclusions or specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what 'broker configurations' entail. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences: purpose statement, parameter list, and return value. It's front-loaded with the core purpose. However, the Args and Returns sections use basic formatting without additional explanatory text, keeping it concise but slightly under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and an output schema present, the description provides a basic purpose and parameter names but lacks details on parameter semantics, behavioral context, and differentiation from siblings. The output schema reduces the need to explain return values, but overall completeness is minimal for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by naming the parameters ('environment', 'topic_name') in the Args section, but doesn't explain what these mean (e.g., format of environment name, scope of topic_name). This partially compensates but falls short of fully clarifying parameter purposes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('broker configurations for a topic'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from similar siblings like 'get_topic' or 'get_topic_metadata', which could also retrieve topic-related information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'get_topic', 'get_topic_metadata', and 'get_topic_partitions', the description lacks any indication of when this specific broker configuration retrieval is appropriate, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions retrieving details from a 'v2 endpoint', which hints at API versioning, but lacks critical behavioral info such as whether it's read-only, requires specific permissions, has rate limits, or how it handles errors. This is inadequate for a tool with potential complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and front-loaded key information. It's concise with no redundant sentences, though the parameter explanations could be more informative without adding bulk.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and no annotations, but with an output schema present (implied by 'Returns'), the description is moderately complete. It covers purpose and return values but lacks behavioral context and detailed parameter semantics, making it adequate but with notable gaps for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists the two parameters ('environment' and 'topic_name') in the Args section, but adds minimal semantic context beyond their names (e.g., no explanation of what an 'environment' entails or format examples). This provides basic mapping but falls short of fully clarifying parameter meanings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieve') and resource ('detailed partition information'), specifying it includes messages and bytes and uses a v2 endpoint. It distinguishes itself from siblings like 'get_topic_metadata' or 'get_topic' by focusing on partition-level details, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_topic_metadata' or 'list_topic_metadata'. The description mentions it's for partition details, but doesn't specify scenarios or prerequisites, leaving usage unclear relative to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 context. It mentions the return type ('list of consumer group objects') but doesn't describe pagination, rate limits, authentication requirements, error conditions, or what happens if the topic doesn't exist. For a read operation with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Every sentence adds value, though the purpose statement could be slightly more specific about what 'retrieve' entails in this context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 value documentation) and only 2 parameters, the description is reasonably complete for a simple lookup tool. However, with no annotations and minimal behavioral context, it leaves gaps about operational constraints and error handling that could affect agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's Args section documents both parameters with basic semantics ('environment name' and 'topic name'). However, it doesn't provide format details, valid values, or examples. Since there are only 2 parameters and the description covers them, baseline 3 is appropriate, though more detail would improve utility.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'retrieve' and resource 'list of consumer groups by a specific topic', making the purpose understandable. It distinguishes from the sibling 'list_consumer_groups' by specifying topic-based filtering, but doesn't explicitly contrast with other consumer group tools like 'delete_consumer_group'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. While the description implies it's for listing consumer groups filtered by topic, it doesn't mention when to use this instead of 'list_consumer_groups' (which likely lists all groups) or other consumer group operations like 'delete_consumer_group'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Retrieves' data, implying a read-only operation, but doesn't cover critical aspects like authentication needs, rate limits, error handling, or pagination behavior. For a list operation with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first ('Retrieves all SQL processor details'), followed by structured Args and Returns sections. There's no wasted text, making it efficient, though the Args section could be more integrated into the flow for optimal structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a simple list operation with one parameter) and the presence of an output schema (which handles return values), the description is moderately complete. It covers the basic purpose and parameter, but lacks usage guidelines, behavioral details, and richer parameter context, making it adequate but with clear gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the parameter 'environment' has no description in the schema. The tool description adds minimal semantics by noting 'environment: The environment name' in the Args section, which clarifies the parameter's purpose but lacks details like format, examples, or valid values. With one parameter, this provides basic compensation but remains inadequate for full understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Retrieves') and resource ('all SQL processor details'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_sql_processor' (which likely retrieves a single processor), 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.
Usage Guidelines2/5
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 'get_sql_processor' (for single processor details) or 'list_sql_processors' (if it exists elsewhere), nor does it specify prerequisites or contexts for use. This leaves the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it's a list operation, implying read-only behavior, but does not disclose any behavioral traits such as permissions required, rate limits, pagination, or whether it's safe to use. The description adds minimal context beyond the basic action, missing key details for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the main purpose first, followed by structured sections for Args and Returns. It avoids unnecessary fluff, but the 'Args' and 'Returns' labels are slightly redundant since the schema covers this; however, the text is clear and efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter, no annotations, and an output schema exists (which handles return values), the description is minimally complete. It explains the parameter and return content, but lacks behavioral context (e.g., safety, performance) and usage guidelines. For a simple list tool, it's adequate but has clear gaps in transparency and guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that explains the 'environment' parameter as 'The environment name', adding meaning beyond the input schema which has 0% description coverage. With only 1 parameter, this compensates well, though it could provide more context (e.g., what environments are valid). Baseline is 4 due to low parameter count and adequate explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'List all topic metadata' which provides a clear verb ('List') and resource ('topic metadata'), distinguishing it from siblings like 'get_topic_metadata' or 'list_topics'. However, it lacks specificity about what 'topic metadata' includes beyond the returns section mentioning 'schemas and descriptions', making it somewhat vague rather than highly specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. For example, it does not differentiate from 'get_topic_metadata' (which might fetch metadata for a specific topic) or 'list_topics' (which might list topic names only). There is no mention of prerequisites, context, or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('resend') but doesn't explain what 'resend' means operationally: Does it duplicate the message? Replay it to consumers? Does it affect message ordering or delivery guarantees? Are there side effects on the original message? No information about permissions, rate limits, idempotency, or error conditions is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured: a clear purpose statement followed by 'Args:' and 'Returns:' sections. Every sentence earns its place, though the parameter listings are minimal. It's front-loaded with the core functionality. Some minor verbosity exists in repeating parameter names that are already in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 required parameters, no annotations, but with an output schema), the description is partially complete. The output schema existence means return values don't need explanation, but the description lacks crucial behavioral context for a mutation tool ('resend' implies write operation). It covers the basic what but not the how, when, or why, leaving significant gaps for the agent to navigate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides only parameter names and types without descriptions. The description lists the four parameters but doesn't add meaningful semantics beyond their names. It doesn't explain what 'environment' refers to (e.g., dev/prod), valid ranges for 'partition' and 'offset', or format expectations for 'topic_name'. The baseline would be lower, but the description at least enumerates the parameters, providing minimal context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Resend a Kafka message' - a specific verb ('resend') and resource ('Kafka message'). It distinguishes itself from siblings like 'update_consumer_group_offsets' or 'delete_consumer_group_topic_partition_offset' by focusing on message resending rather than offset management or deletion. However, it doesn't explicitly differentiate from all siblings in the description text itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 message at the specified offset), when-not-to-use scenarios, or related tools like 'update_consumer_group_offsets' that might handle similar Kafka operations. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Update the offset') but fails to mention critical details like required permissions, whether the operation is idempotent, potential side effects (e.g., impact on consumer group state), or error handling. This leaves significant gaps for an AI agent to understand the tool's behavior beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with a clear purpose statement followed by 'Args' and 'Returns' sections, making it easy to parse. It avoids unnecessary verbosity, though the parameter explanations are minimal. Every sentence serves a purpose, but the lack of deeper context slightly reduces efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a 5-parameter mutation tool with no annotations, the description is moderately complete: it covers the basic operation and parameters. However, it lacks details on behavioral traits, usage context, and output specifics, despite having an output schema. For a tool that modifies consumer group offsets, more guidance on implications and alternatives would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It lists all five parameters with brief labels (e.g., 'environment: The environment name'), adding minimal semantic context beyond the schema's titles. However, it does not clarify parameter relationships, valid ranges (e.g., for 'offset'), or examples, providing only basic definitions that partially address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('offset for a topic-partition for a given group'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'update_consumer_group_offsets' or 'delete_consumer_group_topic_partition_offset', which handle similar resources but with different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'update_consumer_group_offsets' (which might update multiple offsets) or 'delete_consumer_group_topic_partition_offset' (which removes an offset). It lacks context on prerequisites, error conditions, or typical use cases, offering only basic parameter information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it's an update operation but doesn't mention permission requirements, whether changes are reversible, rate limits, or what happens to existing descriptions. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence serves a purpose, though the 'Returns' section could be more informative beyond 'Success message'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter mutation tool with no annotations, the description provides basic purpose and parameter identification. However, with an output schema present, the description doesn't need to detail return values. The main gap is lack of behavioral context for a write operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all three parameters with brief explanations, but doesn't provide format details, constraints, or examples. The description adds basic meaning but doesn't fully compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update topic description') and specifies it's in metadata, which distinguishes it from other update operations. However, it doesn't explicitly differentiate from sibling tools like 'update_topic_metadata' or 'update_dataset_topic_tags', which could be related operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'update_topic_metadata' or 'update_dataset_topic_tags'. It lacks context about prerequisites, typical scenarios, or exclusions for this specific metadata update operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It mentions 'Update' implying mutation but doesn't specify permissions needed, whether changes are reversible, rate limits, or error handling. The return value is briefly noted as a 'Success message' but without format or failure details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses minimal sentences. However, the first sentence could be more front-loaded with key details, and some redundancy exists (e.g., 'topic_name: Name of the topic').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and no annotations, the description provides basic purpose and parameter names but lacks depth. An output schema exists, so return values needn't be detailed, but behavioral and usage context is incomplete for a mutation tool with multiple siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters ('environment', 'topic_name', 'tags') and adds that tags are 'List of tag names', providing basic semantics. However, it doesn't explain parameter formats, constraints, or examples, leaving gaps despite the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update topic tags') and target resource ('in metadata'), specifying it modifies metadata tags for a dataset topic. However, it doesn't explicitly differentiate from sibling tools like 'update_dataset_topic_description' or 'update_topic_metadata', which also update metadata aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'update_dataset_topic_description' or 'update_topic_metadata', nor any prerequisites or exclusions. The description only states what the tool does without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 configuration and returns results with errors, which implies a read-only, non-destructive operation. However, it lacks critical details: whether validation requires specific permissions, if it's idempotent, rate limits, network impact, or what happens on invalid input (e.g., partial validation). For a validation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses minimal sentences. The first sentence states the purpose directly, and subsequent lines efficiently list parameters and returns. There's no redundant information, though it could be more front-loaded with usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, nested object, validation logic) and no annotations, the description is incomplete. It covers purpose, parameters, and returns, but lacks behavioral details (e.g., side effects, error handling) and usage guidelines. The presence of an output schema reduces the need to explain return values, but overall, it's adequate only for basic understanding with clear gaps for agent reliability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description lists all four parameters with brief labels ('environment', 'name', etc.), adding basic semantics beyond the schema's titles. However, it doesn't explain what each parameter means (e.g., 'environment' vs. 'cluster'), expected formats, or constraints, leaving the agent to infer from context. This partially compensates but falls short of fully clarifying parameter roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Validates a Kafka connector configuration.' It specifies the verb ('validates') and resource ('Kafka connector configuration'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'create_kafka_connector' or 'update_topic_config', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., use before deployment), exclusions, or comparisons to siblings like 'create_kafka_connector' or 'set_action_on_kafka_connector'. The only implied usage is from the purpose statement, which is insufficient for clear agent decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but doesn't mention permissions required, whether the topic creation is idempotent, potential side effects, or error conditions. The description lacks critical behavioral context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear opening statement followed by organized Args and Returns sections. Every sentence serves a purpose, though the 'Returns' line is somewhat vague and could be more specific about what 'Creation result' entails.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 5-parameter mutation tool with no annotations, the description provides basic parameter information but lacks crucial behavioral context. The existence of an output schema helps, but the description doesn't adequately address permissions, side effects, or error handling that would be essential for safe tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by listing all 5 parameters with brief explanations. It clarifies that 'partitions' and 'replication' have defaults, and 'configs' are optional topic configurations, adding meaningful context beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Creates a new Kafka topic') and resource ('Kafka topic'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'create_topic_with_schema', which handles similar functionality with additional schema capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'create_topic_with_schema' or 'update_topic_config'. It mentions optional configuration but doesn't specify scenarios where this tool is preferred or prerequisites for successful invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the API ('Lenses WebSocket API') but lacks critical behavioral details: whether this is read-only or can mutate data, authentication requirements, rate limits, or error handling. The description is minimal and doesn't compensate for the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with three clear sections: purpose, parameters, and returns. Each sentence adds value without redundancy, and it's front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (executing SQL via an API) and no annotations, the description is incomplete—it lacks behavioral context and usage guidelines. However, the presence of an output schema (returns 'MessageRecord objects') mitigates some gaps by documenting return values, keeping it from being severely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's 'Args' section adds meaning by explaining 'environment' as 'The environment name' and 'sql' as 'The SQL statement/query to execute.' This clarifies semantics beyond the bare schema, though it doesn't detail format or constraints (e.g., SQL dialect, environment options).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Executes SQL statements/queries using Lenses WebSocket API.' It specifies the verb ('executes') and resource ('SQL statements/queries'), though it doesn't explicitly differentiate from siblings like 'create_sql_processor' or 'get_sql_processor' which might involve SQL but serve different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'create_sql_processor' or 'get_dataset', there's no indication of whether this is for ad-hoc queries, batch processing, or other contexts, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 retrieves dataset details, but doesn't disclose traits like whether it's read-only, requires specific permissions, has rate limits, or what happens on errors. For a retrieval 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by separate 'Args' and 'Returns' sections. Every sentence adds value, and it's front-loaded with the main functionality. It could be slightly more concise by integrating the sections more fluidly, but it's efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains the purpose, parameters, and return values. Since an output schema exists, it doesn't need to detail return values extensively, but it could improve by adding more behavioral context or usage guidelines.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that lists and briefly describes the three parameters (environment, connection, dataset), adding meaning beyond the input schema, which has 0% description coverage. However, it doesn't provide examples (e.g., for 'connection'), constraints, or format details, so it only partially compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a single dataset by connection/name.' It specifies the verb ('Get') and resource ('dataset'), and distinguishes it from siblings like 'list_datasets' by focusing on a single dataset retrieval. However, it doesn't explicitly contrast with other get_* tools (e.g., 'get_topic'), so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_datasets' for browsing or 'get_dataset_message_metrics' for metrics, nor does it specify prerequisites or exclusions. The usage is implied by the purpose but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the tool returns logs as a string, but omits critical details like whether logs are streamed or truncated, time ranges, error handling for non-existent pods, or authentication needs. This is a significant gap for a tool with potential operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for purpose, args, and returns. It uses minimal sentences without redundancy. However, the 'Args' and 'Returns' sections could be integrated more seamlessly, and some details are sparse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, but an output schema exists (implied by 'Returns'), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines, which are important for a tool interacting with Kubernetes resources.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'Pod's name'), adding meaning beyond the schema's titles. However, it does not specify formats or constraints (e.g., valid environment names), leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns the logs produced by a running Kubernetes Pod.' It specifies the verb ('returns') and resource ('logs'), but does not differentiate from sibling tools, as none appear to be log-related. The title is null, so the description carries the full burden.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention prerequisites, such as requiring the pod to be running, or suggest other tools for similar tasks. It lacks context for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it states this is a retrieval operation (implying read-only), it doesn't specify authentication requirements, rate limits, error conditions, or what happens if the ID doesn't exist. The description adds minimal behavioral context beyond the basic operation type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses minimal sentences. Each section earns its place by providing essential information without redundancy. The formatting with bullet-like sections enhances readability while maintaining brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (as indicated by context signals), the description doesn't need to explain return values in detail. The description covers the basic operation, parameters, and return scope adequately for a retrieval tool. However, the lack of behavioral context and usage guidelines leaves some gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by explaining that 'environment' is 'The environment name' and 'sql_processor_id' is 'SQL processor unique identifier', which helps understand what these parameters represent. However, it doesn't provide format examples, constraints, or relationships between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'Retrieves a single SQL processor by ID', which is a specific verb (retrieves) and resource (SQL processor). It distinguishes this tool from siblings like 'list_sql_processors' by specifying it fetches a single item by ID rather than listing multiple items. However, it doesn't explicitly contrast with other get_* tools like 'get_environment' or 'get_topic'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to use 'get_sql_processor' versus 'list_sql_processors', nor does it provide any context about prerequisites, dependencies, or typical use cases. The agent must infer usage from the purpose statement alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation, implying read-only behavior, but doesn't clarify permissions needed, error conditions, rate limits, or what happens if the topic doesn't exist. The mention of returns is minimal and doesn't detail format or structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Each part adds value without redundancy, though the Returns section could be more detailed if not for the output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 required parameters), no annotations, but an output schema present, the description is reasonably complete. It covers the purpose and parameters, and the output schema likely handles return value details, reducing the need for extensive description. However, more behavioral context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's Args section documents both parameters ('environment' and 'topic_name') with brief explanations. This adds meaning beyond the bare schema, though it doesn't specify format constraints (e.g., valid environment names) or examples. With two parameters covered, it meets the baseline for partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'Get metadata for a specific topic', specifying both the verb ('Get') and resource ('metadata for a specific topic'). It distinguishes from siblings like 'list_topic_metadata' (which likely lists multiple topics) by focusing on a single topic, but doesn't explicitly contrast with 'get_topic' or 'get_topic_partitions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention when to choose this over 'get_topic', 'list_topic_metadata', or other metadata-related siblings, nor does it specify prerequisites or contextual constraints for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only mentions retrieval of 'detailed information' without specifying what that entails (e.g., format, pagination, permissions required, or rate limits). It lacks critical behavioral details like whether this is a safe read operation or has side effects, making it insufficient for informed use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses minimal sentences. It's front-loaded with the main purpose, though 'detailed information' is vague and could be more precise. Overall, it's efficient with little waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage and an output schema present, the description adds some param semantics but lacks behavioral context (e.g., safety, permissions). The output schema handles return values, so the description doesn't need to explain those. However, for a tool with no annotations, more behavioral disclosure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining the 'environment' parameter in the Args section, adding meaning beyond the bare schema. However, it doesn't detail possible values or constraints for 'environment', leaving some ambiguity. With only 1 parameter, this is adequate but not comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and resource 'information about all topics', making the purpose unambiguous. It distinguishes from siblings like 'get_topic' (singular) and 'list_topic_metadata' (metadata-specific), though not explicitly named. However, it lacks the specificity of 'detailed information' being clarified, keeping it from 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_topic' for a single topic or 'list_topic_metadata' for metadata-focused listing. The description only states what it does, not when it's appropriate, leaving the agent to infer usage from context without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the tool performs a restart operation but doesn't disclose critical details like whether this requires admin permissions, if it's destructive to data, potential side effects (e.g., temporary downtime), or rate limits. The description is functional but 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and efficiently front-loaded: the first sentence clearly states the purpose, followed by organized Args and Returns sections. Every sentence earns its place with no redundant information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with 4 parameters) and lack of annotations, the description is minimally adequate but incomplete. It covers the basic purpose and parameters, and the presence of an output schema means return values don't need explanation. However, for a mutation tool, it should ideally include more behavioral context (e.g., safety warnings, error conditions) to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but only partially does. It lists all 4 parameters in the Args section, providing basic semantic meaning (e.g., 'environment: The environment name'), but doesn't elaborate on format constraints, valid values, or relationships between parameters (e.g., task_id must belong to the specified connector). This adds some value over the bare schema but leaves gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('restarts') and target ('a specific task of a Kafka connector'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'set_action_on_kafka_connector' which might also affect connector tasks, leaving room for ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., the connector must exist, the task must be in a failed state), nor does it compare to similar tools like 'set_action_on_kafka_connector' that might handle broader connector actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool performs control operations but lacks critical behavioral details: required permissions, whether actions are reversible, potential side effects (e.g., data loss on stop), rate limits, or error conditions. The description adds minimal value beyond the basic action list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It front-loads the purpose in the first sentence, followed by organized sections for 'Args' and 'Returns'. Every sentence earns its place, though the 'Returns' section is somewhat vague ('The result of the control operation').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (control operations on Kafka connectors), no annotations, and an output schema (which should document return values), the description is moderately complete. It covers parameters well but lacks behavioral context and usage guidelines. The output schema reduces the need to explain returns, but the description could better address mutation risks and sibling tool distinctions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It documents all 4 parameters with clear names and provides the 'action' parameter's options ('start', 'stop', 'restart', 'pause', 'resume'), adding significant semantic value. However, it doesn't explain the relationships between parameters (e.g., hierarchy: environment → cluster → connector) or format expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Controls a Kafka connector (start, stop, restart, pause, resume).' It specifies the verb ('Controls') and resource ('Kafka connector') with specific action examples. However, it doesn't explicitly differentiate from sibling tools like 'restart_kafka_connector_task' or 'validate_connector_configuration', 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.
Usage Guidelines2/5
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., connector must exist), exclusions, or comparisons to siblings like 'restart_kafka_connector_task' (which might handle task-level restarts). Usage is implied through the action list 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states it's an update operation, implying mutation, but doesn't disclose critical traits like required permissions, whether changes are reversible, rate limits, or error conditions. The 'Returns' section mentions a success message but lacks detail on format or potential failures.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose, followed by structured sections for Args and Returns. Each sentence serves a clear function, with no redundant information. However, the Args section could be more integrated into the main description for better flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 required parameters, mutation operation) and lack of annotations, the description is moderately complete. It covers parameters and return value basics, and an output schema exists, so detailed return explanations aren't needed. However, it misses behavioral context like side effects or error handling, which is important for a configuration update tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates well by explaining all three parameters: 'environment' as the environment name, 'topic_name' as the topic name, and 'configs' as a list of key-value pairs with an example. This adds meaningful context beyond the bare schema, though it could specify allowed config keys or value formats more explicitly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'topic configuration', making the purpose specific and understandable. It distinguishes from siblings like 'create_topic' or 'get_topic' by focusing on configuration updates rather than creation or retrieval. However, it doesn't explicitly differentiate from 'update_topic_metadata', which might handle different aspects of topic updates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites like needing an existing topic or environment, nor does it compare with siblings such as 'update_topic_metadata' or 'get_topic_broker_configs' for related operations. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns 'health status information including agent connection and any issues,' which gives some insight into output behavior. However, it lacks critical details such as whether this is a read-only operation (implied but not stated), potential side effects, error handling, authentication requirements, or rate limits. For a health-check tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, using a brief purpose statement followed by 'Args:' and 'Returns:' sections. Every sentence adds value: the first states the tool's function, and the subsequent lines explain the parameter and return value. There's no redundant information, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no nested objects) and the presence of an output schema (which handles return value details), the description is reasonably complete. It covers the purpose, parameter meaning, and general return content. However, it could improve by addressing behavioral aspects like safety or usage context, 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.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'name' by specifying it as 'The name of the environment to check.' This clarifies the parameter's role beyond the schema's basic type information. With 0% schema description coverage and only one parameter, the description effectively compensates by providing clear semantics, though it doesn't detail format constraints (e.g., case sensitivity).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Checks the health status of a Lenses environment.' It specifies the verb ('checks') and resource ('health status of a Lenses environment'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_environment' or 'list_environments', which likely provide different types of environment information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'get_environment' (which might retrieve configuration details) or 'list_environments' (which might list environments without health checks). There's no context about prerequisites, timing, or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool deletes an offset, implying a destructive mutation, but doesn't mention permissions required, whether the deletion is reversible, rate limits, or error conditions. This leaves significant gaps in understanding the tool's behavior and risks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence earns its place without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a destructive operation with no annotations, the description is minimally adequate but incomplete. It covers the basic purpose and parameters but lacks behavioral context, usage guidelines, and error handling. The presence of an output schema reduces the need to explain return values, but more detail on the operation's impact is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists all four parameters with brief explanations (e.g., 'environment: The environment name'), adding meaning beyond the input schema, which has 0% description coverage. However, it doesn't provide details on parameter formats, constraints, or examples, leaving some semantic gaps despite covering all parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete the offset') and the target resource ('for a topic-partition for a given group'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_consumer_group' or 'delete_consumer_group_offsets', which handle broader deletions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as 'delete_consumer_group_offsets' (which might delete all offsets for a group) or 'update_consumer_group_topic_partition_offset' (which modifies offsets). The description lacks context on prerequisites, exclusions, or typical scenarios for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'retrieves' a list, implying a read-only operation, but doesn't specify permissions needed, rate limits, pagination behavior, or what happens if the environment doesn't exist. For a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by separate Args and Returns sections. Every sentence earns its place: the first states what the tool does, the second documents the parameter, and the third describes the return value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 value documentation) and only one parameter, the description is reasonably complete. It covers the basic purpose and parameter, though it could better address behavioral aspects given the lack of annotations. For a simple list operation, this provides adequate context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It documents the single parameter 'environment' in the Args section, adding meaning beyond the bare schema. However, it doesn't explain what constitutes a valid environment name, provide examples, or describe format constraints, leaving some semantic gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieve') and resource ('list of all Kafka consumer groups'), making the purpose explicit. It distinguishes from sibling 'list_consumer_groups_by_topic' by specifying 'all' groups rather than filtered by topic. However, it doesn't explicitly contrast with other list operations like 'list_topics' or 'list_datasets'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools like 'list_consumer_groups_by_topic' for topic-filtered lists or 'get_environment' for environment details. It also lacks prerequisites or context about when this operation is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 returns information, implying a read-only operation, but doesn't clarify permissions, rate limits, error handling, or data freshness. For a tool with zero annotation coverage, this leaves significant behavioral gaps, though it correctly indicates a non-destructive action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded, starting with the core purpose, followed by clear Args and Returns sections. Every sentence earns its place without redundancy, making it efficient and easy to parse for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (1 parameter, no annotations, but has an output schema), the description is reasonably complete. It explains the purpose, parameter, and return value. The output schema handles return details, so the description doesn't need to elaborate further, though it could benefit from more behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'environment' by specifying it as 'The environment name' in the Args section, which clarifies its role beyond the schema's basic type. With schema description coverage at 0%, this compensates well, though it doesn't detail format or constraints like valid environment names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns deployment information including available Kubernetes clusters and Connect clusters.' It specifies the verb ('Returns') and the resource ('deployment information'), making the function explicit. However, it doesn't differentiate from siblings like 'get_environment' or 'list_environments', which might also retrieve environment-related data, so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 an 'environment' parameter but doesn't explain prerequisites, such as whether the environment must exist or be accessible. Without explicit when/when-not instructions or named alternatives, usage context is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool retrieves a list and returns a dictionary with details, but lacks critical behavioral information: whether it's read-only (implied but not stated), pagination behavior, error handling, rate limits, or authentication requirements. For a tool with no annotations, this leaves significant gaps in understanding its operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose in the first sentence. The 'Args' and 'Returns' sections are clearly labeled, making it easy to parse. Every sentence adds value without redundancy, and the length is appropriate for a tool with three parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, 1 required), no annotations, and the presence of an output schema, the description is reasonably complete. It covers the purpose, parameters, and return value, and the output schema handles return details. However, it lacks behavioral context (e.g., safety, performance) which would be beneficial since annotations are absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial value beyond the input schema, which has 0% description coverage. It explains that 'environment' is required and names the environment, 'cluster' filters by cluster names, and 'class_name' filters by connector class names. This clarifies the purpose of each parameter, compensating well for the schema's lack of descriptions. However, it doesn't detail format (e.g., string patterns) or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('list of all Kafka connectors'), making the purpose understandable. It distinguishes from siblings like 'get_kafka_connector_target_definition' or 'list_topics' by focusing on connectors specifically. However, it doesn't explicitly differentiate from 'list_sql_processors' or 'list_consumer_groups' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an environment), compare to other list tools (e.g., 'list_topics' for topics), or specify use cases like monitoring or filtering. The description only states what it does, not when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It mentions the tool modifies an existing topic (implying mutation) but doesn't disclose permissions needed, whether changes are reversible, potential impacts on existing data, or rate limits. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Each part earns its place, though the 'Returns' section could be slightly more informative given the output schema exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's mutation nature, no annotations, and 3 parameters, the description is moderately complete. It covers parameters and return value, but lacks behavioral context (e.g., safety, side effects). The output schema reduces need for return details, but overall gaps remain for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining all three parameters in the 'Args' section, clarifying their purposes (e.g., 'New total number of partitions' for 'partitions'). This adds meaningful semantics beyond the bare schema, though it doesn't detail formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Add partitions') and target resource ('to an existing topic'), distinguishing it from sibling tools like 'create_topic' or 'update_topic_config'. It explicitly mentions the verb and resource with no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'update_topic_config' or 'create_topic', nor does it mention prerequisites (e.g., topic must exist) or exclusions. It only states the basic purpose without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 it states this is a creation operation (implying mutation), it doesn't address permissions needed, whether the operation is idempotent, what happens on conflicts, rate limits, or error conditions. The deployment parameter guidance adds some context but doesn't cover the full behavioral profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for Args and Returns. Each sentence earns its place by providing necessary information. While not minimal, the structure helps readability. The deployment parameter explanation is appropriately detailed given its complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 including nested objects) and the presence of an output schema (which handles return values), the description provides good coverage. It explains all parameters thoroughly and states what the tool returns. The main gaps are in behavioral aspects and usage context, but parameter documentation is comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining all 7 parameters in plain language. It clarifies optional vs required parameters, provides deployment configuration details including the 'in process' mode fallback, and explains auto-generation behavior for sql_processor_id. This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'creates' and the resource 'new SQL processor', specifying exactly what the tool does. It distinguishes from sibling tools like 'get_sql_processor', 'list_sql_processors', and 'delete_sql_processor' by focusing on creation rather than retrieval or deletion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 creation is appropriate, or how it relates to sibling tools like 'execute_sql' or 'get_deployment_targets'. The deployment parameter hint about 'in process' mode is technical guidance but not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 fetches data (implying read-only) and returns YAML, but doesn't mention error conditions (e.g., if the connector doesn't exist), authentication needs, rate limits, or whether the data is cached. This leaves gaps for a tool that likely interacts with a live system.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a structured Args/Returns section. Every sentence earns its place by defining the action, parameters, and output without redundancy. It's efficiently sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 covers return values) and no annotations, the description is moderately complete. It defines the purpose and parameters but lacks behavioral details like error handling or system interactions. For a read operation with three required parameters, this is adequate but leaves room for improvement in guiding usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists all three parameters with brief explanations, adding meaning beyond the schema (which has 0% description coverage). It clarifies that 'environment' is a name, 'connect_cluster_name' identifies the cluster, and 'connector_name' specifies the connector. However, it doesn't explain format constraints or provide examples, preventing a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Fetches') and resource ('current target definition for a Kafka connector'), distinguishing it from siblings like 'list_kafka_connectors' (which lists connectors) or 'validate_connector_configuration' (which validates configs). It precisely identifies what is being retrieved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this should be used after creating a connector with 'create_kafka_connector' or in conjunction with 'list_kafka_connectors'. The description lacks context about prerequisites or typical workflows.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses that the tool returns a list with details like status, metrics, and metadata, which adds useful behavioral context beyond a basic list operation. However, it lacks information on potential side effects, rate limits, or authentication needs, leaving gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence and efficiently adds return details in the second. Every sentence earns its place without waste, making it appropriately sized and well-structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, no annotations, but with an output schema), the description is reasonably complete. It explains what the tool does and what it returns, and since an output schema exists, it need not detail return values further. However, it could improve by addressing usage context or behavioral traits more fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so the schema fully documents the absence of inputs. The description does not add parameter details, which is appropriate here. A baseline of 4 is applied for zero parameters, as no additional semantic value is needed beyond the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lists') and resource ('all Lenses environments'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_environment' (which might fetch a single environment) or 'list_topics' (which lists a different resource), so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. For example, it does not mention if this should be used for a broad overview instead of 'get_environment' for specific details, or any prerequisites or exclusions, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 it 'Creates' without disclosing behavioral traits like permissions needed, whether it's idempotent, error handling, or rate limits. It mentions a return but doesn't describe what 'Creation result' entails beyond the output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a clear summary sentence followed by structured Args and Returns sections. Every sentence adds value, though the parameter explanations could be more front-loaded in the summary for better initial clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter creation tool with no annotations, the description covers parameters well but lacks behavioral context. The presence of an output schema reduces the need to explain returns, but more guidance on usage and error cases would improve completeness given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by listing all 9 parameters with brief explanations, including defaults for partitions and replication, and clarifying when key_schema is required. It adds meaningful context beyond the bare schema, though some details like configs structure remain vague.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Creates' and the resource 'new Kafka topic', specifying it includes 'optional format and schema configuration'. It distinguishes from sibling 'create_topic' by explicitly mentioning schema capabilities, making the purpose specific and differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for creating topics with schema configuration, but doesn't explicitly state when to use this vs. the simpler 'create_topic' sibling tool. It mentions optional parameters but lacks clear guidance on alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 is for retrieval (read-only) and mentions pagination, but doesn't cover important aspects like rate limits, authentication requirements, error conditions, or what happens with invalid parameters. The 'Returns' section mentions paginated results with source types, but lacks detail on response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for purpose, arguments, and returns. While comprehensive, it's appropriately sized for a tool with 13 parameters. Every sentence earns its place, though the parameter explanations could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 parameters, no annotations) and the presence of an output schema, the description is reasonably complete. It explains the tool's purpose, documents all parameters thoroughly, and mentions the return type. However, it lacks behavioral context like error handling or performance characteristics that would be helpful for a complex retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 13 parameters, the description provides comprehensive parameter documentation in the 'Args' section, explaining each parameter's purpose, defaults, and constraints. This fully compensates for the lack of schema descriptions and adds significant value beyond the basic schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 verb ('Retrieves') and resource ('paginated list of datasets'), and distinguishes it from siblings by specifying it's for datasets (topics and other data sources) rather than topics alone or other resources. This differentiates it from tools like list_topics or list_environments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_dataset (for single dataset details) or list_topics (for topics only), nor does it specify prerequisites or contextual constraints beyond the required environment parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses that the tool creates a new resource (implying a write operation) and returns an object with an 'agent_key' for setup, which adds useful context. However, it does not mention permissions required, rate limits, or potential side effects (e.g., if creation is irreversible or has dependencies).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and front-loaded purpose. Sentences are efficient, but the parameter details are somewhat lengthy; however, given the 0% schema coverage, this detail is justified and not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (creation with 4 parameters) and no annotations, the description is fairly complete: it explains purpose, parameters, and return value. An output schema exists, so return details are not needed. It could improve by adding more behavioral context (e.g., permissions), but covers essentials adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides detailed semantics for all 4 parameters: 'name' with validation rules, 'display_name' with fallback behavior, 'tier' with enum options and default, and 'metadata' as key-value pairs. This adds significant meaning beyond the basic schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Creates a new Lenses environment') and identifies the resource ('environment'). It distinguishes from sibling tools like 'get_environment' or 'list_environments' by specifying creation rather than retrieval, and no other sibling tools create environments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a new environment is needed, but does not explicitly state when to use this tool versus alternatives (e.g., updating an existing environment or checking environment health). It mentions the return includes 'agent_key for setup', hinting at a setup context, but lacks explicit guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves data (implying read-only), but does not disclose behavioral traits like error handling (e.g., if the environment name is invalid), authentication needs, rate limits, or whether it's idempotent. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by structured 'Args' and 'Returns' sections. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 parameter) and the presence of an output schema (which handles return value details), the description is largely complete. It covers purpose, parameter semantics, and return content. However, it lacks behavioral context (e.g., error cases), which is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'name' by specifying it as 'the name of the environment to retrieve', which clarifies its purpose beyond the schema's minimal title 'Name'. With 0% schema description coverage, this compensates well, though it could detail format constraints (e.g., case sensitivity).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('retrieves') and resource ('a single Lenses environment by name'), distinguishing it from sibling tools like 'list_environments' (which returns multiple) and 'check_environment_health' (which focuses on health status). The specificity of 'by name' adds further differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need details for a specific environment, contrasting with 'list_environments' for multiple environments. However, it does not explicitly state when NOT to use it or name alternatives, leaving some contextual gaps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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