SageMaker AI MCP Server

Server Quality Checklist

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Latest release: v0.0.1
Disambiguation5/5
Each tool targets a specific resource-action pair, and even closely related resources like pipelines and pipeline executions are clearly distinguished by their names and descriptions. There is no meaningful overlap that would cause selection ambiguity.
Naming Consistency5/5
All tools follow a consistent <verb>_<resource>_sagemaker pattern, using snake_case throughout. Verb choice (list, describe, create, delete, start, stop) is uniform, and the resource portion is descriptive and predictable.
Tool Count1/5
With 57 tools, the server is far beyond the typical well-scoped range and exceeds even the 'too many' threshold. The sheer number is overwhelming and suggests an extreme mismatch for an MCP server, even considering the breadth of SageMaker.
Completeness2/5
The tool set covers many resources but lacks fundamental lifecycle operations such as create or update for core entities like training jobs, models, endpoints, and pipelines. Several listed resources have no describe or delete counterparts, leaving significant gaps that hinder agent workflows.
Average 3.3/5 across 57 of 57 tools scored. Lowest: 1.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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?
No annotations are present, and the description gives no behavioral details such as permissions, error handling, read-only guarantees, or potential side effects. The word 'describe' implies a read operation, but nothing is disclosed beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (one sentence) but under-specified. It does not earn its place because it simply restates the tool name without adding useful information. Concise is not the same as minimal to the point of uselessness.
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 the simplicity (one required parameter) and the presence of an output schema, the description need not explain return values. However, it lacks any contextual framing about what a SageMaker Pipeline Execution is, what information is returned, or when to use this tool. The bare description is inadequate for an agent to confidently select and invoke the tool.
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 schema covers the single parameter fully (100% coverage), so the baseline is 3. The description adds no parameter semantics beyond what the schema already states, but the schema adequately documents the pipeline_execution_arn parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Describe a SageMaker Pipeline Execution' is a tautology that merely restates the tool name. It does not provide any specifics about what the 'describe' operation returns or how it differs from sibling tools like describe_pipeline_sagemaker or describe_training_job_sagemaker.
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?
There is no guidance on when to use this tool versus the many sibling describe_* tools. No context, prerequisites, or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. The phrase 'Describe' implies a read-only operation, but it does not disclose any specific behaviors, required permissions, return format, or limitations. This is a tautological restatement of the tool name and adds no value beyond what the name already implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise in length, but it is under-specified and merely restates the purpose implied by the tool name. It does not earn its place by providing any useful information beyond the title, making it closer to a placeholder than a well-structured description.
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 the tool has an output schema and four required parameters, the description is too minimal to be contextually complete. It does not explain expected behavior, how the tool fits into the broader workflow, or any special considerations. The output schema covers return values, but the lack of usage context and behavioral details leaves significant 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?
The input schema provides 100% description coverage for all four required parameters, including detailed explanations of each field (e.g., domain_id, user_profile_name, app_type, app_name). The tool description itself adds no additional parameter information, so it receives the baseline score of 3 as specified for high 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 'Describe' and the resource 'SageMaker App', which is specific enough to identify the tool's basic function. However, it does not add any scope or distinguishing details that differentiate it from sibling describe tools for other SageMaker resources (e.g., describe_domain, describe_endpoint), so it falls short of 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, what conditions apply, or how it compares to alternatives like list_apps_sagemaker or create_app_sagemaker. It is a bare statement with no 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?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It only says 'Describe', which implies a read-only operation, but it does not state whether permissions are needed, whether the definition is the original template or processed version, or any limitations such as size or availability. This is a significant gap for a tool with zero annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that essentially restates the tool name without adding new information. While it is brief, it is under-specified rather than concise; it does not earn its place by providing any value beyond the name. There is no structure or additional context.
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 the tool's simplicity (one parameter) and presence of an output schema, the description might be minimally acceptable. However, it lacks any contextual information about when to use this over sibling tools, such as describe_pipeline_execution_sagemaker or describe_pipeline_sagemaker. The absence of usage guidelines and behavioral details makes it incomplete for an agent to confidently select this tool.
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 input schema has one parameter (pipeline_execution_arn) with 100% description coverage, so the schema already fully documents the parameter. The description adds no extra meaning, such as format constraints or prerequisites for the ARN. Baseline of 3 is appropriate because schema coverage is high.
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 'Describe Pipeline Definition for a SageMaker Pipeline Execution' clearly states the action (describe) and the specific resource (pipeline definition for an execution). It distinguishes from siblings like describe_pipeline_execution_sagemaker by focusing on the definition rather than the execution status. However, it does not explicitly differentiate from describe_pipeline_sagemaker, which could be ambiguous without deeper inference.
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?
There is no guidance on when to use this tool versus alternatives. For example, it does not mention that this tool returns the underlying template/definition, while describe_pipeline_execution_sagemaker returns runtime details. The description provides no exclusions or alternative references, so the agent is left without decision support.
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 merely states the action without revealing side effects, long-running nature, costs, or any post-create behavior. The agent cannot anticipate what happens after creation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single terse sentence with no wasted words, but it's under-specified for a create operation. It front-loads the core action but lacks necessary supporting context, making it concise yet incomplete.
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?
For a create operation with nested objects, an output schema, and many sibling tools, the description is far too minimal. It doesn't explain the nature of the resource, possible app types (though schema covers them), or operational implications. The rich schema cannot compensate for the lack of contextual guidance.
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 input schema has 100% description coverage, so the baseline is 3. The description itself adds no parameter meaning beyond the schema, which already fully documents each field. No additional clarification is provided.
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 uses a clear verb+resource structure ('Create a SageMaker App') that accurately identifies the operation. It distinguishes from sibling tools like describe_app_sagemaker and delete_app_sagemaker, though it doesn't elaborate on the app types or scope.
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 domain_id or user_profile_name, nor does it indicate when this tool is preferred over other create tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 merely states 'Create a Managed MLflow Tracking Server,' without mentioning side effects, permissions, provisioning time, or any implications for the underlying SageMaker resources. For a create operation, this is a significant transparency 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 a single sentence that is front-loaded with the action and resource. It is concise and to the point; however, it is so brief that it borders on under-specification, omitting anything beyond the core action. Still, it is appropriately sized for a simple create tool and does not waste words.
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?
Despite having a complete schema and output schema, the description offers no context about when to create a managed MLflow server, what infrastructure is affected, or any caveats. A create tool typically warrants usage context (e.g., 'Use this to set up a server before using start/stop/describe commands'), but this description is minimal and does not fill that gap.
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 input schema describes all three parameters (artifact_store_uri, tracking_server_name, tracking_server_size) with 100% coverage. The description adds no parameter-specific meaning, but the baseline for high schema coverage is 3, so this score reflects that the schema carries the load adequately.
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 action ('Create') and the specific resource ('Managed MLflow Tracking Server in SageMaker'). It unambiguously distinguishes this tool from its siblings, which include list, describe, start, stop, and delete MLflow tracking servers, as well as a presigned URL creator for a different resource.
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 the other MLflow tracking server tools. There is no mention of prerequisites, use cases, or alternatives. While the name implies creation, the description itself offers no explicit or implicit usage context beyond the verb 'create.'
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. The description only says 'Describe', which implies a read operation, but it does not explicitly state that the operation is non-destructive, does not clarify whether it requires specific permissions, or mention any error conditions. This is a minimal disclosure.
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 a single, front-loaded sentence with no wasted words. For a simple describe tool with one parameter, this length is appropriate. However, it is somewhat sparse, providing only the minimum information.
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?
This is a simple tool with one required parameter and an output schema present, so the description need not explain return values. However, with no annotations and no usage context, the description is only minimally viable. It lacks any clarification on when to use this tool relative to sibling describe tools or any additional behavioral context, making it adequate but not comprehensive.
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 100%, meaning the only parameter (app_image_config_name) already has a clear description in the schema. The tool description adds no additional meaning beyond what the schema provides, so the baseline score of 3 applies.
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 'Describe a SageMaker App Image Config' clearly states the verb (Describe) and the resource (SageMaker App Image Config). It is specific enough to indicate the tool's function, though it does not differentiate from sibling describe tools beyond the resource name, which is already evident from the tool 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?
The description provides no guidance on when to use this tool versus alternatives, such as list_apps or describe_app. There is no mention of prerequisites, context, or exclusions. The agent is left to infer usage solely from the tool name and schema.
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 carry the full burden of behavioral disclosure. It only says 'Describe a SageMaker Domain,' implying a read-only operation but not explicitly stating safety, permissions, or error behavior. The word 'describe' hints at non-mutating behavior but gives no further detail.
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 a single short sentence with no filler, but it conveys minimal information beyond the tool name. It is efficient but not particularly valuable, hence a 4 rather than 5.
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 simple describe action with one parameter and an output schema, the description is functionally minimal. It lacks usage context, alternatives, or behavioral notes, making it incomplete for a tool with many siblings but acceptable for a straightforward API call.
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 input schema has 100% coverage, including a description for domain_id. The tool description itself adds no parameter-level meaning beyond what the schema already documents, so the baseline of 3 applies.
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 'Describe a SageMaker Domain' uses a specific verb ('describe') and resource ('Domain'), distinguishing it from siblings about endpoints, pipelines, and models. However, it is essentially a paraphrase of the tool name and lacks elaboration on what describing entails, so it is clear but not particularly rich.
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 list_domains or describe_endpoint_sagemaker. There are no stated exclusions, prerequisites, or context about selecting this over siblings, leaving the agent without 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 for behavioral disclosure. 'Describe' implies a read-only operation, but the description does not explicitly state non-mutation, permissions, or what happens with invalid inputs. It adds no behavioral context beyond the verb.
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 a single, front-loaded sentence with no filler words. It is efficient and easy to parse, though it could be slightly more informative without becoming verbose.
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 simple describe operation with one parameter and an output schema, the description is minimally viable. However, it lacks any context about what an endpoint configuration is or how this differs from other describe tools, and the output schema is not referenced. It is adequate but leaves room for improvement.
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 input schema has 100% description coverage for the single parameter 'endpoint_config_name', with a clear description. The tool description adds no parameter information beyond the schema, so the baseline score of 3 applies.
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 ('Describe') and the resource ('a SageMaker Endpoint Configuration'), using a specific verb and resource. However, it does not distinguish this from sibling describe tools like describe_endpoint_sagemaker, so it stops short of full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool vs alternatives, no exclusions, and no mention of prerequisites. The one-sentence description leaves the agent to infer usage from the 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 only states that the tool describes a job, offering no details about error handling, return structure, or any side effects. The separate output schema exists but the description itself adds no 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 a single sentence with no wasted words. It is efficient but offers little value beyond what the tool name already implies, edging it slightly below a perfect score.
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?
The one-parameter input and presence of an output schema cover the essential mechanics, so the description is minimally adequate. However, the absence of annotations and any usage context leaves gaps in fully understanding the tool's behavior and place among 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 coverage is 100% with a clear description for the single parameter 'job_name'. The tool description adds no extra meaning beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (describe) and the specific resource (a SageMaker Inference Recommender Job), distinguishing it from sibling describe tools for other resource types. It is unambiguous, though it lacks detail about what information is returned.
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 usage guidance is provided. The description does not mention when to use this tool versus the sibling list tool, nor does it provide any context on how to obtain the job name. It is purely a restatement of the action.
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, but it only states the basic action. It does not mention that this is a read-only operation, what information it returns, or how it handles non-existent pipelines. This leaves the agent guessing about side effects and edge cases.
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 a single, concise sentence without any redundant wording. It is well-structured and front-loaded, stating the purpose immediately. It earns its place by being clear, though it could arguably include more useful context without sacrificing 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 simplicity of the tool (one parameter, no annotations) and the presence of an output schema, the description is minimally adequate. It does not explain the tool's relationship to sibling tools or provide additional context about the pipeline resource being described. For a simple describe operation, this is sufficient but not comprehensive.
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 single parameter 'pipeline_name' is fully described in the input schema ('The name of the SageMaker Pipeline to describe'), so schema coverage is 100%. The description itself adds no additional semantic detail beyond the schema, which gives a baseline of 3 according to the rubric.
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 states a clear verb+resource: 'Describe a SageMaker Pipeline'. It identifies the tool's primary function. However, it does not distinguish itself from sibling tools like 'describe_pipeline_execution_sagemaker' or 'describe_pipeline_definition_for_execution_sagemaker', which also involve describing pipeline-related entities.
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 lacks any mention of prerequisites, exclusions, or situations where a different structure (e.g., describe_pipeline_execution_sagemaker) would be more 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Start a SageMaker Pipeline Execution,' implying a mutating action but providing no details about asynchronicity, return values, potential errors, or whether it requires an existing pipeline. This is a significant gap for a tool that likely triggers a long-running workflow.
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 a single sentence, concise and front-loaded, with no filler words. However, it is arguably under-specified for the tool's complexity, which limits its usefulness. Still, it is efficiently written and easy to parse.
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?
Although an output schema exists (so return format need not be described), the description lacks essential context for a state-changing operation. It does not mention whether the call is asynchronous, whether it requires a pipeline to be in a certain state, or what side effects occur. This is incomplete for an agent that needs to correctly assess the impact of 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 100%: both 'pipeline_name' and 'parameters' have descriptions explaining their values. The tool description adds nothing beyond what the schema already provides, so it does not compensate or extend parameter understanding. A baseline score of 3 is appropriate given 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 'Start a SageMaker Pipeline Execution' clearly states the action (start) and the resource (SageMaker Pipeline Execution). It distinguishes from sibling tools like stop_pipeline_execution and describe_pipeline_execution by indicating initiation rather than modification or inspection, though it does not explicitly call out this differentiation.
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?
There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., pipeline must exist), when a start is appropriate, or that stopping/describing executions are separate operations. The description is purely a statement of the action with no contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description merely restates the tool's name ('Delete a SageMaker Model Card') and adds no behavioral context beyond what the name implies. With no annotations, the description fails to disclose irreversibility, permission requirements, or side effects of deletion.
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 a single, concise sentence that is easily parsed. It is not bloated, though it could incorporate a brief note about deletion consequences without becoming overly long.
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 simple one-parameter delete tool, the description is minimally adequate but lacks important context such as whether deletion is permanent or requires special permissions. The presence of an output schema reduces the need to describe return values, but the absence of any safety warnings leaves a gap.
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 input schema has 100% coverage: the single parameter 'model_card_name' is described with its type and purpose. The description adds no extra parameter details, but the schema already provides sufficient semantics for the only parameter.
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 action ('Delete') and the resource ('SageMaker Model Card'), leaving no ambiguity about what the tool does. It distinguishes itself from sibling tools like delete_model_sagemaker by specifically targeting Model Cards.
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 list_model_cards or describe_model_card. It does not mention any prerequisites, caveats, or situations where deletion 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action without noting side effects, permissions, or that the operation is safe/read-only. There is no mention of expiration behavior or the return format beyond what the schema implies.
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 a single concise sentence with no redundant wording, earning its place. However, it is almost terse; while there is no waste, a bit more context would improve usefulness without harming conciseness.
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?
Despite having an output schema, the description lacks essential context: when to use this tool, what prerequisites exist, and any behavioral nuances. This is particularly problematic given the absence of annotations. The agent must infer usage solely from the name and schema, which is insufficient for complex decision-making.
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 100%, so the input schema already fully documents all three parameters. The description adds no extra meaning beyond what the parameter descriptions provide, making the baseline of 3 appropriate.
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 uses the specific verb 'Create' and the target resource 'presigned URL for a SageMaker Domain', making the tool's purpose unambiguous. It clearly distinguishes from sibling tools that create presigned URLs for other resources (e.g., MLflow tracking server or notebook instance).
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 does not mention prerequisites, such as the need for an existing domain or user profile, nor does it explain scenarios where this presigned URL would be needed.
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, the description must disclose behavioral traits. It only states the obvious deletion operation, which is already clear from the tool name. It does not mention whether the config must be unused, whether deletion is irreversible, or what the output schema represents. This is a minimal restatement rather than genuine behavioral disclosure.
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 a single, clear sentence with no fluff. It is concise and front-loaded. However, it provides no more information than the tool name itself, making it slightly under-specified. It earns a 4 for conciseness but lacks additional substantive content.
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?
Despite low complexity, the description insufficiently covers usage context and behavioral transparency. It simply states the action, leaving the user uninformed about when to use the tool, what to expect, and any consequences. For a destructive operation, this is 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?
The input schema documents the single parameter (app_image_config_name) with full coverage, so the description does not need to explain it. The description adds no additional semantic information about the parameter, so it relies entirely on the schema. Baseline 3 is appropriate given the high schema coverage.
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 uses a specific verb ('Delete') and identifies the resource ('SageMaker App Image Config'), clearly distinguishing it from sibling tools like describe_app_image_config_sagemaker or delete_app_sagemaker. It precisely states the action and resource, leaving no ambiguity about what the tool does.
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 instead of alternatives. There is no mention of prerequisites, side effects, or situations where deletion is appropriate. For a user deciding between delete and describe, this description offers no support.
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 present, so the description must carry the burden of behavioral disclosure. It states the action is 'Delete', which implies destructiveness, but it does not disclose irreversibility, potential failure conditions (e.g., if the app is running), or consequences for associated data. This is minimal transparency for a destructive operation.
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 an extremely concise single sentence with zero filler words. It is front-loaded and efficiently communicates the core action. While it is terse, it earns a 4 for appropriate size and clarity without unnecessary elaboration.
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?
For a delete operation with 4 required parameters and an output schema, the description is under-specified. It does not mention whether the operation is reversible, whether it can fail under certain conditions (e.g., app still running), or any validation steps. The tool complexity is low, but the risk of destructive action warrants more behavioral context than a single phrase.
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 input schema covers 100% of parameters with descriptive titles and descriptions (e.g., 'The ID of the domain in which the app resides'). The description adds no parameter-specific information beyond the schema, so the baseline 3 applies per the rubric.
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 'Delete a SageMaker App' uses a specific verb ('Delete') and resource ('SageMaker App'), exactly matching the tool name. It clearly distinguishes this from sibling tools like 'describe_app_sagemaker' and 'create_app_sagemaker' and other delete tools for different 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?
No guidance is provided about when to use this tool versus alternatives. There is no mention of prerequisites (e.g., app must exist or be inactive), circumstances for deletion, or exclusions. The description merely restates the action without contextual 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 the full burden of behavioral disclosure, but it only says 'Delete a SageMaker Pipeline' without revealing consequences like permanence, cascading deletions, or permission requirements. It adds no context beyond what the tool name already implies.
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 extremely concise at four words, and every word is meaningful. It is front-loaded with the verb 'Delete' and clearly identifies the resource. However, it lacks any structural elements like warnings or usage notes, which keeps it from a perfect score.
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?
Even though the tool is simple and the schema covers the only parameter, the description omits crucial context for a destructive operation. No mention of irreversibility, what happens to associated resources, or any caveats. The presence of an output schema reduces the need to describe return values, but the overall description is too sparse to be fully useful.
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 input schema has 100% coverage, with the parameter 'pipeline_name' clearly described as 'The name of the SageMaker Pipeline to delete.' The description adds no additional parameter semantics beyond the schema, which already fully documents the required parameter.
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 'Delete a SageMaker Pipeline' uses a specific verb (delete) and resource (SageMaker Pipeline), clearly distinguishing it from sibling tools like describe_pipeline_sagemaker, list_pipelines_sagemaker, and start_pipeline_execution_sagemaker. It unambiguously states the tool's function.
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, no prerequisites (e.g., pipeline must exist), and no mention of whether deletion is reversible. It simply restates the action without any 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, the description carries the full burden of behavioral disclosure. It only states 'Describe' which implies a read operation, but does not specify what is returned, whether it errors if the card doesn't exist, or any permissions needed. This is a minimal level of transparency.
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 extremely concise, using a single front-loaded sentence that conveys the purpose without any wasted words. It is appropriately sized for a simple describe 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?
For a simple one-parameter describe tool with an output schema and full schema coverage, the description is adequate but lacks context such as usage guidance or behavioral details. It doesn't explain what the returned data contains, but the output schema covers that, so a score of 3 is reasonable.
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 100% and the parameter 'model_card_name' has a clear description in the schema. The tool description itself adds no additional meaning beyond the schema, so the baseline of 3 is appropriate.
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 'Describe a SageMaker Model Card' uses a specific verb and resource, clearly indicating it returns details about a model card. It differentiates from sibling tools like describe_pipeline_sagemaker or describe_model_sagemaker by naming the unique resource 'Model Card'.
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 list_model_cards_sagemaker. There is no mention of prerequisites, when to use, or when not to use.
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 only says 'Describe' without explicitly stating that the operation is read-only, requires any specific permissions, or returns a representation of the model. The description adds no context beyond what the name alone implies.
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 a single, concise sentence with no redundant phrasing. It is appropriately sized for a tool with one parameter and an output schema, with every word earning its place.
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 simplicity of the tool (one parameter, output schema present), the description provides a minimally viable purpose. However, it lacks usage guidance and any behavioral notes, creating noticeable gaps. It is adequate but not comprehensive for a reader who needs to decide when and how to invoke this tool.
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 schema fully documents the only parameter (model_name) with a clear description, achieving 100% coverage. The tool description adds no additional parameter semantics, so the baseline of 3 applies. There is no need for the description to re-explain what the schema already covers.
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 uses a clear verb+resource pattern ('Describe a SageMaker Model') and names the resource type, distinguishing it from sibling tools like describe_pipeline_sagemaker and describe_endpoint_sagemaker. However, it does not elaborate on what specific aspects of the model are described (e.g., configuration, status), leaving some ambiguity about the exact scope.
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?
There is no guidance on when to use this tool versus alternatives such as list_models_sagemaker or other describe_* tools. The description simply states what it does without indicating prerequisites, exclusions, or preferred contexts.
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, the description carries the full burden of disclosing behavioral nuances. It only states the action 'Start' without explaining side effects, whether the operation is idempotent, whether permissions are required, or what the response might contain. This is a significant gap for a state-changing operation.
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 a single, direct sentence that avoids waste and front-loads the key action. However, it is too brief to be considered excellent; it lacks any supplementary context that would make it more useful without bloating.
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?
The tool is a lifecycle operation with no annotations, no behavioral detail, and no usage guidelines. While it has an output schema, that does not compensate for the missing context about when and how to use the tool relative to other MLflow server operations. The description is inadequate for a state-changing action.
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 coverage is 100% with the parameter 'tracking_server_name' properly described in the schema. The tool description adds no additional parameter semantics, but the baseline of 3 is appropriate since the schema handles the explanation.
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 uses a specific verb ('Start') and defines the exact resource ('Managed MLflow Tracking Server') and context ('in SageMaker'). This clearly distinguishes the tool from sibling operations like create_mlflow_tracking_server_sagemaker (which creates, not starts) and stop_mlflow_tracking_server_sagemaker (which stops).
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 does not mention prerequisites (e.g., server must exist before starting), nor does it reference the related lifecycle tools (create, describe, stop, delete). The agent is left to infer usage from the 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, and the description does not disclose side effects such as cancellation of running steps, idempotency, or potential errors in stopping a pipeline execution. For a mutation tool, this lacks 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 a single, short sentence that is front-loaded and easy to read. It earns its place as a readable summary, though it essentially restates the tool name.
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?
The tool has a simple interface (one required param and output schema), but with no annotations, the description lacks critical behavioral context about the stopping operation, such as idempotency, failure conditions, or permissions.
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 schema fully documents the only parameter (pipeline_execution_arn) with a clear description, so the tool description adds no additional semantic information. Baseline of 3 is appropriate due to 100% schema coverage.
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 uses the specific verb 'Stop' and names the resource 'SageMaker Pipeline Execution', clearly identifying the tool's action and distinguishing it from sibling tools like stop_training_job_sagemaker. It directly states what the tool does.
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 vs alternatives, prerequisites, or exclusions. The description only states what it does, leaving the agent to infer usage from the name.
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 for behavioral disclosure. It only states that it stops a job, without mentioning side effects, reversibility, permissions, or behavior for already-stopped jobs. This is a limiting factor for a mutation 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?
A single, complete sentence that is front-loaded with the action and resource. Every word is useful, with no redundancy or unnecessary detail.
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 low complexity (one parameter and an output schema), the description is minimally adequate. However, it omits any context about the operation's effects, such as whether the job is terminated immediately or if the request can be retried. No annotations exist to cover these aspects.
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 coverage is 100%, with the parameter 'training_job_name' clearly described in the schema. The description adds no additional meaning beyond the schema, but since the schema fully documents the single parameter, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Stop' and the resource 'SageMaker Training Job', which is specific and unambiguous. While it doesn't explicitly differentiate from sibling stop tools, the resource type is distinct and the intent is clear.
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 does not mention prerequisites, scenarios, or exclusions, leaving the agent to infer usage solely from the tool name. Sibling tools like stop_processing_job_sagemaker would require similar inference.
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, and the description does not disclose any behavioral traits such as whether this is a read-only operation, required permissions, or lifecycle of the URL. It simply restates the 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 a single, clear sentence with no unnecessary words. However, it only covers the basic purpose and lacks any additional contextual information, so it gets a 4.
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 simple tool with full schema coverage and an output schema, the description covers the basic purpose but omits usage context and behavioral details. For a tool with no annotations, this leaves gaps in completeness, so a 3 is appropriate.
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 input schema already describes both parameters (expiration_seconds and tracking_server_name) with 100% coverage, so the description adds no additional parameter semantics beyond what the schema provides. Baseline 3 is appropriate.
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 action (Create) and the specific resource (presigned URL for a Managed MLflow Tracking Server in SageMaker), distinguishing it from sibling presigned URL tools for domains and notebook instances.
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, prerequisites, or use cases. It only states the operation without any contextual 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 responsibility for disclosing behavioral traits. It only states the action 'delete' but does not mention irreversibility, potential cascading effects on associated resources, or any required domain state. This is a significant gap for a destructive 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 a single, concise sentence that directly states the action and resource. Every word is necessary, and it is front-loaded with the key information.
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 the tool's destructive nature and lack of annotations, the description is incomplete: it fails to convey side effects, preconditions, or operational impact. Although an output schema exists and parameter coverage is complete, the description does not provide adequate context for an agent to safely invoke deletion.
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 input schema already provides a description for the only parameter, domain_id, with 100% coverage. The tool description adds no additional parameter semantics beyond what the schema offers, so the baseline score of 3 applies.
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 'Delete a SageMaker Domain' uses a specific verb and resource, clearly distinguishing this tool from sibling delete tools like delete_model_sagemaker or delete_endpoint_sagemaker. It fully states the tool's function without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, nor any prerequisites or exclusions (e.g., whether the domain must have no associated apps or users). Users must infer usage solely from the name and 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 the full burden of disclosing behavioral traits. It only states the purpose and does not explicitly mention that the operation is read-only, what information it returns, potential errors (e.g., tracking server not found), or required permissions. While 'describe' implies non-mutating behavior, the description fails to make behavioral details explicit.
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 a single, front-loaded sentence with no redundant words. It directly states the tool's action and target resource, achieving maximum efficiency.
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?
The tool is simple with one parameter and an output schema, but the description is too sparse to be contextually complete. It lacks information about when to use this tool compared to listing servers or other operations, and does not mention any caveats or limitations. The absence of usage guidance and behavioral transparency leaves gaps that are not covered by schema/annotations alone.
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 100% (tracking_server_name is described in the schema). Per the rubric, the baseline is 3. The description adds no additional parameter semantics beyond what the schema already provides, but it is not required to compensate given full schema coverage.
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 'Describe a Managed MLflow Tracking Server in SageMaker' uses a specific verb ('describe') and a clear resource ('Managed MLflow Tracking Server in SageMaker'). It distinguishes itself from sibling tools like list_mlflow_tracking_servers, start/stop/delete_mlflow_tracking_server, and other describe_* tools by clearly targeting the MLflow Tracking Server resource.
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 list_mlflow_tracking_servers or other describe operations. The description does not mention prerequisites, selection criteria, or exclusions. It relies entirely on the tool name and the agent's inference to determine appropriate 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 merely restates the action (listing parameters) without clarifying that it is a read-only operation, describing output behavior, or mentioning permissions. It adds minimal context beyond the tool name.
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 a single, concise sentence that front-loads the action and resource. Every word earns its place, with no filler or redundancy.
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?
For a simple one-parameter list operation with an output schema present, the description provides sufficient context about what the tool does. It is not as rich as tools with usage guidance, but it is complete enough for the tool's simplicity.
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 input schema has 100% coverage with a clear description for the single parameter pipeline_execution_arn. The tool description adds no additional meaning beyond what the schema already provides, so the baseline of 3 is appropriate.
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 uses the specific verb 'List' and names the resource 'Pipeline Parameters for a SageMaker Pipeline Execution', which distinguishes it from sibling tools like list_pipeline_executions or list_pipeline_execution_steps. It clearly states what the tool does, though it lacks an explicit contrast with alternatives.
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 does not mention any prerequisites, contextual triggers, or exclusions. The intended use is implied by the tool's name and description but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 only restates the tool's name without adding details about pagination, filtering, read-only semantics, or any other behavioral traits. This is insufficient for a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. It is front-loaded and appropriately sized for a simple list operation, earning the maximum score for 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?
The tool has no parameters and an output schema, so the description need not explain return values. However, it lacks usage guidance and behavioral transparency, making it only minimally complete for an agent tasked with selecting among many similar sibling tools.
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 zero parameters, so the baseline is 4. The description does not add parameter-specific meaning, which is appropriate since there are no parameters to document. No additional semantics are needed beyond the 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 identifies the action ('List') and resource ('SageMaker Processing Jobs'), stating exactly what the tool does. However, it does not explicitly distinguish this from sibling list tools such as list_training_jobs_sagemaker or list_transform_jobs_sagemaker, so it falls short of 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 like describe_processing_job_sagemaker for a single job or other list_*_jobs tools. There are no mentions of use cases, exclusions, or preferred scenarios.
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. The verb 'List' implies a read-only operation, but no details about pagination, ordering, filtering, rate limits, or what exactly is returned are disclosed. The output schema exists but the description does not reference it or any behavioral caveats.
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 a single, clear sentence with no wasted words. It is front-loaded with the action and resource. Every word earns its place.
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?
The tool is simple with no parameters and an output schema, so the description needn't explain return values. However, it lacks usage guidelines and behavioral details like pagination or filtering, which are important for a list operation. It is minimally viable but not fully complete for an AI agent to make informed selection decisions.
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 tool has 0 parameters, and the input schema is empty. Per guidelines, baseline for 0 params is 4. The description does not need to explain parameters because there are none, and no parameter information is missing.
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 'List' and the resource 'SageMaker Training Jobs', which distinguishes it from sibling tools like list_processing_jobs and describe_training_job. However, it lacks any scoping qualifiers (e.g., 'all', 'filtered by...') that would make it fully unambiguous across variations of listing behavior.
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. There is no mention of alternatives or conditions under which this tool is appropriate. The usage is only implied by the name and description, but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only says 'List SageMaker Transform Jobs' which is essentially the operation name itself. It does not mention pagination, ordering, region scope, output shape, or any other behavioral traits, leaving the agent with no insight beyond the name.
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 a single, compact sentence that immediately conveys the operation. No filler or unnecessary details, making it highly efficient and front-loaded.
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 zero-parameter listing tool, the description is adequate to convey its primary purpose, and the existence of an output schema likely covers return values. However, it lacks guidance on when to use it (e.g., in workflows) and any constraints like available filters or result limits, making it only minimally complete.
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 zero parameters, so the baseline is 4. The description appropriately says nothing about parameters, and there is nothing more to explain about them.
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 ('List') and the resource ('SageMaker Transform Jobs'), distinguishing it from sibling list tools that target other SageMaker resources (e.g., training jobs, processing jobs). It is specific, though it does not elaborate on scope or any special behavior.
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 does not mention that this is for enumerating transform jobs, nor does it direct users to describe_transform_job for details on a specific job. The lack of any contextual hints makes it harder for an agent to decide if this is the right list tool.
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 only states the delete action, without acknowledging potential side effects (e.g., impact on existing endpoints), irreversibility, or required permissions.
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 a single, front-loaded sentence that directly states the operation. No wasted words or redundant information.
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 simple one-parameter delete tool, the description covers the core purpose but lacks context about consequences or when to use it. Given the existence of an output schema, return values need not be described, but the absence of any safety/usage context keeps this at a 3.
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 single parameter `endpoint_config_name` is fully described in the schema, and the description adds no additional semantics beyond the API action. Since schema coverage is 100%, the baseline of 3 is appropriate.
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 action (delete) and the resource (SageMaker Endpoint Configuration), distinguishing it from sibling delete tools like delete_endpoint_sagemaker and delete_model_sagemaker. The verb+resource structure is unambiguous and 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?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or situations where deleting an endpoint configuration might be inappropriate.
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, the description carries the full burden. It only states the delete action and does not disclose whether deletion is irreversible, whether the server must be stopped first, or what permissions are required.
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 a single, front-loaded sentence with no unnecessary content. It is concise and immediately conveys the action and target resource.
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?
The tool has one well-documented parameter and an output schema, so basic invocation is clear. However, the lack of behavioral context around a destructive operation leaves the description minimally 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?
The schema describes tracking_server_name with 100% coverage, so the description adds no extra parameter meaning. The tool description does not go beyond what the schema already provides.
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 uses the specific verb 'Delete' and the exact resource 'Managed MLflow Tracking Server in SageMaker', which clearly distinguishes it from sibling tools like delete_model_sagemaker and stop_mlflow_tracking_server_sagemaker.
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, and there are no preconditions, contexts, or exclusions mentioned. The description only states what the tool does, not when or how to choose 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?
No annotations are provided, so the description carries full burden. It merely restates the action implied by the name without disclosing that deletion is permanent or irreversible, or any permissions or potential side effects. This is insufficient for a destructive 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?
One precise sentence, no filler words, front-loaded with the action. Perfectly sized for the simple tool.
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?
The description is minimal but sufficient for a one-parameter delete operation with full schema coverage and output schema. However, it lacks any contextual details about what happens when the model is deleted or any dependencies, which could be expected for a destructive action.
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 covers 100% of parameters with a clear description for model_name. The tool description adds no additional parameter context, but since schema coverage is high, baseline 3 is appropriate.
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 uses the specific verb 'Delete' and identifies the exact resource 'SageMaker Model', clearly differentiating it from sibling delete tools like delete_endpoint_sagemaker and delete_model_card_sagemaker.
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 on when to use this tool versus alternatives. The description simply states the action without context such as prerequisites, when to delete a model, or when to prefer other tools.
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 only restates the tool name without adding context about return format, required permissions, or side effects. The read-only nature is implied but not explicitly disclosed, and no additional behavioral traits are mentioned.
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 a single, concise sentence that directly states the purpose. It is front-loaded and contains no unnecessary words, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema providing return value details. However, the description itself lacks contextual information such as typical use cases or distinctions from similar describe tools. Given the low complexity, a minimal description is acceptable, but it could be slightly more informative.
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 100% with the parameter endpoint_name clearly described in the input schema. The tool description adds no additional parameter context, but the baseline of 3 is appropriate since the schema already documents the parameter effectively.
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 'Describe a SageMaker Endpoint' uses a specific verb and resource, clearly distinguishing it from sibling tools like list_endpoints_sagemaker (listing) and describe_endpoint_config_sagemaker (describing a different resource). It effectively states what the tool does.
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 describe_endpoint_config_sagemaker. There is no mention of typical scenarios, prerequisites, or exclusions, leaving the agent without contextual 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 the full burden of behavioral disclosure. It states the action 'Stop' but does not explain side effects (e.g., whether the job is terminated immediately, if it's reversible, or if any resources are cleaned up). This is minimal and lacks the transparency expected 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence that is front-loaded with the action and resource. No unnecessary words or fluff. For a simple single-parameter tool, this is appropriately sized and structured.
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?
The tool is simple (one param, full schema coverage, output schema present), so the description is minimally adequate for invocation. However, it lacks any behavioral context or usage guidance, which leaves it incomplete in a broader sense. Given the low complexity, a score of 3 reflects that it is 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?
The schema already provides a clear description for the single parameter ('The name of the SageMaker Inference Recommender Job to stop'), and coverage is 100%. The tool description adds no further meaning beyond what the schema states, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Stop') and the specific resource ('a SageMaker Inference Recommender Job'). This distinguishes it from sibling stop_* tools that target different resources (e.g., stop_training_job_sagemaker). The verb+resource structure leaves no ambiguity about what the tool does.
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 does not mention prerequisites (e.g., job must be in a stoppable state), nor does it contrast with other stop tools. Usage is only implied by the name/description, which does not meet the bar for explicit or even adequate contextual guidance.
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, the description carries the full burden, but it only states the action without disclosing side effects such as whether the server can be restarted, if data is preserved, or any permission requirements. The behavior beyond 'stop' is opaque.
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 a single sentence that is front-loaded with the verb and resource. It contains no unnecessary words and is highly scannable.
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 simple one-parameter tool and existing output schema, the description is minimally viable. However, it lacks lifecycle context (e.g., that the server can be restarted and data is retained), which could be valuable given sibling start/delete tools. Not rich but adequate.
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 input schema already provides a full description for the only parameter (tracking_server_name), so the tool description adds no additional meaning. Baseline of 3 is appropriate as the schema covers 100% of the parameter semantics.
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 uses a specific verb ('Stop') and identifies a distinct resource ('Managed MLflow Tracking Server in SageMaker'). It clearly distinguishes the action from sibling tools like start, describe, and delete by stating the exact 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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., server must be running) or how it differs from delete_mlflow_tracking_server_sagemaker, leaving the agent to infer usage from the 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. However, it only states the action without describing side effects, asynchrony, idempotency, or permission requirements, which is insufficient 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It effectively communicates the core purpose without any wasted text.
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?
The schema covers the parameter well and an output schema exists, but the description lacks usage guidance and behavioral context. Given the many sibling stop tools, some additional detail would improve completeness, though the minimal description may suffice for a simple one-param tool.
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 input schema has one parameter with a clear description, achieving 100% schema coverage. The tool description adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Stop' and resource 'SageMaker Transform Job', clearly indicating the action and target. This distinguishes it from sibling stop tools for other job types such as training or processing jobs.
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 explicit guidance on when to use this tool versus other stop tools, and no alternatives or exclusions are mentioned. Usage is only implied by the resource type, but no context or prerequisites are given.
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 carry the burden of disclosing behavioral traits. It does not mention consequences like irreversibility, prerequisites such as the job being InProgress, or whether the stop is asynchronous, offering only a restatement of the 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 a single, front-loaded sentence with no redundant words. It is concise and appropriately sized for a simple stop operation.
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?
For a one-parameter command with an output schema present, the description is minimally adequate for basic invocation. However, missing context about state requirements and side effects prevents a perfect score.
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 input schema has 100% coverage with a clear description for the single parameter 'processing_job_name'. The tool description adds no extra semantic detail beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Stop' and names the resource 'SageMaker Processing Job', making the tool's purpose unambiguous. It distinguishes from sibling stop tools like stop_training_job and stop_transform_job.
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 does not mention checking job status with describe_processing_job or finding job names with list_processing_jobs, leaving usage entirely implicit.
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 disclose behavioral traits. It does not mention whether the operation is idempotent, irreversible, or fails if the endpoint does not exist, leaving key side effects undisclosed.
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 a single, concise sentence that immediately conveys the tool's purpose. It is appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple delete operation with one parameter and an output schema, the description is adequate but leaves gaps around behavioral context (e.g., irreversibility, prerequisites). It is not as complete as it could be for a mutation tool without 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?
The schema fully documents the single parameter (endpoint_name) with a clear description, so the schema provides baseline coverage. The description itself adds no extra meaning beyond what the schema already supplies.
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 action ('Delete') and the resource ('SageMaker Endpoint'), distinguishing it from sibling tools like delete_model_sagemaker and delete_endpoint_config_sagemaker.
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 name and description imply the tool is for deleting a SageMaker endpoint, providing a clear context for when to use it. However, it offers no guidance on prerequisites, alternatives, or exclusions relative to other delete tools.
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 responsibility for disclosing behavioral traits. The description merely restates the action ('Describe') without indicating that this is a read-only operation, what information will be returned, or any potential error conditions. It does not add value beyond the tool name, leaving the safety profile and output expectations unclear.
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 a single, concise sentence with no redundant words or filler. It immediately conveys the essential purpose, earning a perfect score for 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 low complexity (one parameter, output schema present), the description is minimally sufficient. However, the lack of explicit read-only disclosure and any usage guidance means the agent must rely on the schema and name conventions. The description does not compensate for the absent annotations, leaving a moderate gap 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?
The schema provides 100% description coverage for the single parameter, explicitly stating it is 'The name of the SageMaker Transform Job to describe'. The tool description adds no additional semantic meaning beyond this, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (describe) and the resource (SageMaker Transform Job). With multiple sibling tools for describing other SageMaker resources, this description precisely identifies the target resource, distinguishing it from describe_pipeline_sagemaker, describe_endpoint_sagemaker, etc.
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 provides no explicit guidance on when to use this tool versus alternatives. Usage is implied by the name and the general pattern of 'describe' tools, but there is no mention of scenarios, prerequisites, or exclusions. For example, it does not state to use this tool when you need details about a specific transform job as opposed to listing jobs.
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 must disclose behavioral traits on its own. It only states the action 'List', which implies a read-only operation, but does not mention pagination, result size limits, ordering, or any other operational behavior. This is a minimal disclosure that adds little beyond the tool name.
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 exactly four words, 'List all SageMaker Domains', and every word contributes meaning. It is front-loaded with a clear action and resource, and contains no redundant or filler content.
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 no parameters and an output schema exists, the description is minimally adequate. However, it lacks any context about pagination, response format, or how it differs from the many related SageMaker list tools, which means the agent may not have enough information to fully understand the operation's behavior. It is a viable baseline but has clear 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 input schema has zero parameters, so there is nothing for the description to explain. The word 'all' in the description confirms that the operation returns every SageMaker Domain without filtering, which is a useful semantic clarification consistent with the empty schema. This aligns with the baseline for zero-parameter tools.
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 'List all SageMaker Domains' uses a specific verb ('List') and a clear resource ('SageMaker Domains'), and the word 'all' indicates the full scope, distinguishing it from single-domain operations like describe_domain_sagemaker or delete_domain_sagemaker. This is clear and unambiguous.
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 its many siblings (e.g., describe_domain_sagemaker, list_user_profiles_sagemaker, list_spaces_sagemaker). There is no mention of prerequisites, filtering alternatives, or typical use cases, leaving the agent to infer applicability solely from the name.
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. 'List all SageMaker Endpoints' implies a read-only operation but does not disclose pagination behavior, response format, or any side effects. It lacks explicit transparency 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler. It is appropriately front-loaded and easily scannable, containing exactly the necessary information for such a simple tool.
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?
The tool is simple (no parameters) and has an output schema, but the description is very brief. It does not mention pagination or clarify the scope (e.g., regional or account-wide), and given the many sibling tools, some usage context 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?
The tool has zero parameters, and the input schema is empty. Per the rubric, a baseline of 4 applies since there is nothing to describe; the description does not need to add parameter semantics.
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 uses a specific verb ('List') and resource ('SageMaker Endpoints'), clearly distinguishing it from sibling tools like describe_endpoint_sagemaker and list_endpoint_configs_sagemaker. It leaves no ambiguity about what the tool returns.
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 describe_endpoint_sagemaker or list_endpoint_configs_sagemaker. It simply states the action without any situational context 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 present, so the description alone must disclose behavioral traits. It only states the tool lists model cards, without mentioning pagination, response scope (e.g., region or account), or that it is a read-only operation. This is minimal coverage for an unannotated tool.
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 a single concise sentence, front-loaded with the action and resource. Every word adds value, and there is no redundancy or filler.
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?
The tool is simple with no parameters and an output schema present, so the description need not explain return values. However, it omits behavioral context like pagination or scope, which is useful for a list operation. Given the simplicity, the description is minimally sufficient but not fully complete.
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 is empty (0 parameters), so the baseline for parameter semantics is 4. The description adds no parameter details, but none are needed since the tool takes no arguments.
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 'List all SageMaker Model Cards' uses a specific verb and resource, clearly stating it lists model cards. It distinguishes itself from sibling tools like list_endpoints_sagemaker and list_training_jobs_sagemaker, which target other SageMaker 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?
No guidance is provided on when to use this tool versus closely related siblings such as list_model_card_versions or list_model_card_export_jobs. There is no mention of exclusions, prerequisites, or alternative tools.
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 only states that the tool lists all steps, but does not mention pagination behavior, whether the execution must be in a particular state, authentication needs, or any read-only caveats. The verb 'list' implies read-only, but this is not explicit.
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 a single, front-loaded sentence that names the verb and resource with no redundant words. It is appropriately sized for a simple, one-parameter list 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?
The tool is simple, has one fully documented parameter, and provides an output schema. However, the description does not mention prerequisites (beyond the required ARN), pagination, or relationship to sibling tools. It is adequate for a straightforward list operation but lacks some context that would make it 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?
The schema already describes the single parameter (pipeline_execution_arn) with 100% coverage, including its purpose. The tool description adds no extra semantic detail beyond what the schema provides, so the baseline of 3 is appropriate.
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 uses a specific verb ('List') and a precise resource ('Pipeline Execution Steps' for a SageMaker Pipeline Execution). It clearly differentiates this tool from siblings such as list_pipeline_executions (which lists executions) and describe_pipeline_execution (which describes a single execution).
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 does not explicitly state when to use this tool or provide alternatives. However, the purpose and the required pipeline_execution_arn parameter imply that it should be used when you have an execution ARN and want to see its steps. This is implied usage rather than explicit guidance.
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 bears full responsibility. It discloses the basic read-only nature of listing, but does not mention pagination, authorization needs, or the meaning of 'all' (e.g., account-wide vs per-domain). This is minimal behavioral disclosure.
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?
A single, clear sentence that directly states the action and target. No wasted words.
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 zero-parameter list tool, the description is functional, but it lacks any note on scope or pagination, and does not clarify whether 'all' is domain-scoped. The presence of an output schema somewhat covers return values, yet the description is still thin.
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 zero parameters, the empty schema fully documents the input surface. The baseline for 0 params is 4, and the description adds no conflicting or redundant parameter information.
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 uses the specific verb 'List' with a clear resource 'SageMaker User Profiles', distinguishing it from sibling list tools for other resources. It clearly states the 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 instead of alternatives, and no exclusions or context about scoping. It merely restates the resource name without positioning it against sibling list operations.
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 only says 'Create a presigned URL' without disclosing any side effects, authentication requirements, or behavior such as whether the notebook instance must be in a specific state. This is a thin description for an operation that presumably generates a time-limited URL.
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 a single, concise sentence that immediately conveys the tool's purpose. There is no redundant or filler text.
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 low complexity (2 parameters, no nested objects) and the presence of an output schema, the description is mostly complete. However, it does not mention any usage context, such as the fact that the notebook instance must exist or that the URL is for accessing the notebook instance UI. Still, the essential operation is clear.
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 100% since both parameters have descriptions in the schema. The tool description does not add any semantic meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a presigned URL for a SageMaker Notebook Instance', using a specific verb and resource. It distinguishes itself from sibling tools like create_presigned_url_for_mlflow_tracking_server_sagemaker and create_presigned_url_for_domain_sagemaker by naming 'Notebook Instance'.
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?
Usage guidance is implicit through the resource name and the presence of sibling presigned URL tools for other AWS SageMaker resources. However, there is no explicit statement about when to use this tool versus the MLflow or Domain presigned URL tools, nor any mention of prerequisites or alternatives.
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 is the sole source of behavioral info. The verb 'Describe' implies a read-only operation, but the description adds no details about permissions, side effects, or response contents beyond what the output schema provides. The description is minimal but not misleading.
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 a single sentence with no waste, fully front-loaded. It is appropriately concise for a simple describe operation.
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 single parameter, existing output schema, and the simple read-only nature, the description is sufficient. It does not explain return values because the output schema covers that. However, it could have noted that the job must already exist, but that is implied by a describe 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?
The schema already provides full coverage with a clear description for 'processing_job_name'. The tool description adds no extra parameter context, so baseline 3 is appropriate.
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 uses specific verb 'Describe' and resource 'SageMaker Processing Job', clearly distinguishing it from sibling describe tools for other SageMaker resources. It is a concise statement of purpose, though it closely mirrors the tool 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 like list_processing_jobs or stop_processing_job. There is no mention of scenarios, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a safe read operation but does not disclose pagination behavior, response size, permissions needed, or any other operational characteristics beyond the basic listing 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 a single short sentence, 'List all SageMaker Apps', with no filler words. It is front-loaded and directly states the operation, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read tool with an output schema, the description is minimally sufficient. It states the tool's purpose, and the output schema handles return details. However, it could benefit from noting any scoping (e.g., account-level, pagination), though it remains adequate for a simple listing operation.
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 zero parameters, so there is nothing to describe. The baseline for zero-parameter tools is 4, and the description correctly does not attempt to add unnecessary parameter details.
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 uses a specific verb ('List') and resource ('SageMaker Apps'), clearly indicating a read-only enumeration operation. It distinguishes itself from siblings like create_app_sagemaker, describe_app_sagemaker, and delete_app_sagemaker by focusing on listing all apps.
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 explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites, exclusions, or alternative tools. The usage context must be inferred solely from the tool name and sibling list, which 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 only says 'List Model Card Export Jobs', which implies a read-only operation, but it does not disclose other behavioral traits such as pagination, ordering, required permissions, or error behavior. The description is minimal and does not add context beyond the action itself.
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 a single sentence, front-loaded with the verb and resource, and contains no unnecessary words. It is appropriately concise for a simple list operation.
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 simplicity, single parameter, and the presence of an output schema, the short description is sufficient. The name and parameter make the purpose clear, and the output schema covers return values. There are no critical gaps, though a bit more context about usage could improve it slightly.
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 input schema has 100% coverage with a clear parameter description ('The name of the SageMaker Model Card to list export jobs for'). The tool description does not add any parameter-specific meaning, but the schema fully documents the single parameter, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with the resource 'Model Card Export Jobs' and scopes to 'a SageMaker Model Card'. This clearly distinguishes it from sibling tools like list_model_cards_sagemaker and list_model_card_versions_sagemaker, making the tool's purpose unambiguous.
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 states what the tool does but does not explicitly say when to use it versus alternatives. Usage is implied by the name and resource: use when you need to see export jobs for a specific model card. No alternatives, exclusions, or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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. However, it only repeats the tool's function without disclosing additional traits such as read-only behavior, error conditions, pagination, or result ordering. The description adds no value beyond the name itself.
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 a single sentence that is direct and free of fluff. It is appropriately sized for the operation it describes.
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?
For a simple list operation with one parameter and an output schema, the description is largely complete. It conveys the essential purpose, and the output schema handles return value details. However, with no annotations and minimal behavioral context, it's not maximally complete, but it suffices for the tool's simplicity.
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 schema description coverage is 100% (the parameter 'model_card_name' is fully described in the schema). The description adds no further meaning to the parameter, so the baseline of 3 applies.
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 'List' and the resource 'versions of a SageMaker Model Card'. It distinguishes itself from sibling tools like list_model_cards_sagemaker (which lists cards, not versions) and describe_model_card_sagemaker (which describes a single card). The purpose is unambiguous.
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 context (list versions for a given model card name) but provides no explicit guidance on when to use this tool versus alternatives. There are no mentions of when-not-to-use or alternative tools, so the usage is only implied by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 clearly states this is a list operation (implying read-only) and scopes to all executions for a pipeline, but it does not disclose pagination, result limits, ordering, or any other relevant behavioral traits. This is adequate for a simple list tool but lacks deeper 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 a single, clear sentence that directly states the tool's purpose. No filler or redundant wording, making it highly concise and efficient.
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 simplicity (one required parameter, output schema present), the description is nearly complete. It fully explains the operation without needing to mention return values due to the output schema. However, it lacks any usage context or caveats, which keeps it from a perfect score.
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 100%, so the pipeline_name parameter is fully described in the schema. The tool description adds no additional meaning beyond the schema, matching the baseline of 3 for high coverage.
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 'List all Pipeline Executions for a SageMaker Pipeline' uses a specific verb and resource, clearly distinguishing this from sibling tools like list_pipeline_execution_steps_sagemaker or describe_pipeline_execution_sagemaker. It states exactly what is listed and for which resource.
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 describe_pipeline_execution_sagemaker or list_pipeline_execution_steps_sagemaker. There is no mention of when-not-to-use or which sibling is better for a particular scenario.
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?
There are no annotations, and the description merely states 'List SageMaker Pipelines'. It does not disclose any behavioral traits such as read-only nature, pagination, result ordering, or potential errors. With the full burden on the description, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words, achieving maximum efficiency and 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?
The tool is extremely simple (no parameters, output schema exists), so a minimal description is arguably sufficient. However, it lacks any extra context about what the returned list contains or any limitations, making it only slightly above adequate.
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 tool has zero parameters and schema coverage is 100%, so there is nothing for the description to add about parameters. Baseline 4 applies.
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 'List SageMaker Pipelines' uses a specific verb and resource, clearly indicating that the tool lists SageMaker pipeline resources. It distinguishes from sibling list tools by naming the resource, even if it doesn't explicitly separate pipelines from pipeline executions; the tool name already does that.
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 list_pipeline_executions_sagemaker or describe_pipeline_sagemaker. It does not mention any prerequisites or typical scenarios, so the agent receives no direction on selection.
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, the description carries the full burden of behavioral disclosure. 'Describe' clearly implies a read-only operation, but the description does not add details about what information is returned, permission requirements, or failure behavior. It is minimal but not misleading, so a score of 3 is appropriate.
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 a single, front-loaded sentence that states the essential purpose without any filler. Every word contributes to clarity, making it highly concise and well-structured for the tool's simplicity.
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?
For a simple describe operation with a single parameter and an output schema present, the description is nearly complete. It does not explain return values, but the output schema serves that purpose. The only minor gap is the lack of explicit context about when to use this tool, but that is already covered under 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 input schema covers 100% of the parameters, including a clear description for the required training_job_name. The tool description itself adds no additional parameter-level meaning, so the baseline of 3 applies.
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 'Describe a SageMaker Training Job' clearly identifies the action (describe) and the resource (SageMaker Training Job). It distinguishes from sibling tools that target other resources like pipelines, endpoints, or models.
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 through the verb 'describe' and the resource name, but it does not explicitly state when to use this tool versus alternatives such as list_training_jobs_sagemaker. No exclusions or alternative recommendations are provided, so the usage context is inferred rather than explicit.
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, but it only states 'List all...' without disclosing behaviors such as pagination, response structure, or potential side effects. While 'List' implies a read-only operation, no additional behavioral context is given, leaving gaps about how the tool actually behaves.
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 a single, front-loaded sentence with no unnecessary words. It directly and efficiently states the action and the resource.
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?
For a simple zero-parameter list tool with an output schema, the description is largely complete. However, it does not mention pagination or whether 'all' jobs requires multiple calls, which could be relevant to an agent. Since the output schema is present, return value details are covered elsewhere.
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 tool has zero parameters, so the description is not required to explain parameter syntax or semantics. According to the rubric, a zero-parameter tool receives a baseline score of 4.
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 uses the specific verb 'List' and clearly identifies the resource as 'SageMaker Inference Recommender Jobs', distinguishing it from sibling tools like list_training_jobs_sagemaker and list_inference_recommendations_job_steps_sagemaker. The purpose is unambiguous.
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 its usage through 'List all', but it does not provide explicit guidance on when to use this tool over alternatives, such as list_inference_recommendations_job_steps_sagemaker. There are no exclusions or additional context to clarify the exact scenario.
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, the description carries the burden of behavioral disclosure. 'List all SageMaker Models' implies a read-only, no-side-effect operation, but it does not mention pagination, response shape, or other behavioral traits. This is minimal but acceptable for a trivial list 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 a single, concise, front-loaded sentence. Every word adds value, with no wasted content.
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?
For a zero-parameter list tool, the description is essentially complete: it states the exact action and scope. The output schema likely explains the return structure, so the description only needs to convey the purpose and scope.
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 zero parameters, and the description adds no parameter information, but none is needed. The schema fully covers the parameter surface, so the baseline of 4 is appropriate.
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 identifies the action ('List') and the resource ('SageMaker Models'), making it distinct from sibling tools like describe_model_sagemaker or list_endpoints_sagemaker. It is immediately obvious what this tool does.
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 describe_model_sagemaker for model details or other list tools for different resources. There is no mention of exclusions or preferred context.
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, the description carries the behavioral disclosure burden. 'List all SageMaker Spaces' implies a read-only enumeration and 'all' indicates no filtering, but it does not mention pagination, permissions, or other runtime behavior. It adds minimal context beyond what the tool name already communicates.
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 a single sentence, front-loaded with the action and resource, with no extraneous words or information. It is highly concise and properly structured.
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?
For a low-complexity, parameterless tool with an output schema, the description is mostly complete. However, it lacks any mention of pagination or service-level caveats that could affect usage, so it is not fully complete.
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 zero parameters with 100% coverage, so there are no parameter semantics for the description to clarify. The use of 'all' reinforces the parameterless nature by suggesting no filtering options exist.
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 uses the specific verb 'List' and clearly identifies the target resource ('SageMaker Spaces'). The word 'all' clarifies scope, and the resource name distinguishes it from sibling tools like list_apps_sagemaker and list_domains_sagemaker.
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 the many sibling list_* tools, nor any context about prerequisites or typical use cases. This is a bare listing with no 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 the full burden. It only states the action without disclosing behavioral traits such as read-only safety, pagination, or return format. The agent must infer that listing is safe.
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 a single short sentence with no filler and is front-loaded with the verb and resource. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the zero-parameter simplicity and the presence of an output schema, the description is sufficient to convey the tool's scope. It covers the essential 'list all' nature without needing to describe return values.
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 tool has zero parameters, so there is nothing to explain. The baseline of 4 applies since no parameter information is needed.
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 uses a specific verb 'List' and a clear resource 'SageMaker Endpoint Configurations', which clearly states what the tool does and distinguishes it from sibling tools like list_endpoints_sagemaker and describe_endpoint_config_sagemaker.
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 a top-level enumeration of all configurations, but it does not explicitly state when to use this tool versus describe_endpoint_config_sagemaker for details or list_endpoints_sagemaker for endpoints. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It accurately indicates a read-only operation ('List'), but it doesn't mention any details about response format, prerequisites, or potential limitations. It is adequate but not rich.
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 a single, clear sentence with no wasted words. It is perfectly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list operation with one well-described parameter and an output schema, the description is complete. It adequately covers the needed information for an agent to select and invoke the tool correctly.
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 coverage is 100% for the single parameter 'job_name', and the schema already describes it. The description adds no additional meaning beyond the schema, so the baseline of 3 applies.
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 action ('List') and the resource ('steps for a SageMaker Inference Recommender Job'), distinguishing it from sibling tools like list_inference_recommendations_jobs (list jobs) and describe_inference_recommendations_job (describe job).
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 usage is implied by the tool name and description, but there is no explicit guidance on when to use this tool versus alternatives or any exclusion criteria. The sibling names provide context, but the description itself doesn't mention them.
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, the description relies on the verb 'List' to convey this is a read-only operation. It does not disclose details about pagination, response size, or whether any server metadata is returned. The description is essentially a restatement of the name with minimal added behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that exactly states the tool's purpose. Every word earns its place, and there is no redundant information.
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?
For a no-parameter list operation with an output schema present, the description is complete. It clearly states the resource type and scope. Minor gaps such as not mentioning pagination are acceptable given the simplicity of the 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?
The tool has zero parameters, so the description need not explain parameter meaning. The schema is empty and fully covered; the baseline of 4 applies because no parameter documentation is required.
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 uses a specific verb ('List') and resource ('Managed MLflow Tracking Servers in SageMaker'), clearly distinguishing it from sibling tools that describe, create, start, stop, or delete individual servers. The word 'all' clarifies that this is an enumeration operation without filtering.
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 intended use is implied by the name and description: use this tool to enumerate all MLflow tracking servers. However, there is no explicit guidance on when not to use it or mention of alternative tools like describe for specific servers, so it stops at implied usage.
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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