gcp-mcp

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools target distinct GCP resources and include the resource type in the name (e.g., list_compute_instances, list_storage_buckets). However, several configuration and auth tools (config_set_project, set_quota_project, auth_login, auth_list) overlap in purpose and could confuse an agent, and get_instance_details vs get_sql_instance_details may be ambiguous without careful attention.
Naming Consistency3/5
The majority of tools use a consistent verb_noun snake_case pattern (list_*, get_*, create_*, delete_*). But there are notable exceptions like config_set_project, auth_login, auth_list, set_quota_project, and say_hello that break the pattern, mixing noun_verb and generic verbs.
Tool Count2/5
56 tools is excessive for a coherent MCP server. Even though GCP is broad, many tools are repetitive list/get operations across services, making the set feel bloated and hard to navigate. This count pushes beyond the reasonable range for maintainability and agent usability.
Completeness2/5
The server is heavily read-focused and lacks full lifecycle coverage for many resources. There are no update/delete tools for buckets, service accounts, GKE clusters, SQL instances, firewall rules, alert policies, and many other resources, and no create operations for several listed services. This leaves obvious dead ends for common management workflows.
Average 3.6/5 across 56 of 56 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
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{
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  ]
}
```
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It only states that it creates a backup and returns a result, without mentioning mutating implications, potential long-running behavior, IAM requirements, or effects on existing backups. This leaves the agent without a clear understanding of side effects.
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 concise and well-structured, opening with a clear action statement, followed by a parameter list and return value. It contains no irrelevant information and is easy to scan.
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 no annotations and no output schema, the description is too sparse. It leaves out critical context such as prerequisites (e.g., the instance must exist), asynchronous behavior, what the returned result contains, and potential permissions. The vague 'Result of the backup operation' does not adequately prepare an agent for the tool's usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no parameter descriptions (0% coverage), so the description compensates by listing all three parameters with brief explanations. It clarifies that 'description' is optional, which adds context, but the explanations are largely restatements of the parameter names and lack detailed constraints or formatting.
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 'Create a backup' and the specific resource 'Cloud SQL instance', which is sufficiently precise. It does not explicitly compare with sibling tools, but the resource type differentiates it from other backup/snapshot tools.
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, prerequisites, or alternatives. The usage is only implied by the tool's name and description, with no explicit context such as 'use when you need to back up a Cloud SQL instance' or required permissions.
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. It states the operation and parameter intent but does not disclose side effects (e.g., overwriting existing files, directory creation), permission requirements, error behavior, or details about the returned 'Result'. The return value is vague and unexplained.
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 properly structured as a docstring with a clear one-sentence summary followed by parameter explanations and a returns line. It is concise and every section serves a purpose, though the 'Returns' line adds little value.
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 simple nature of the tool, the description covers the basic action, but it is incomplete for an AI agent. It lacks information about overwriting behavior, whether the destination directory must exist, error handling, or authentication requirements. The return value is undefined, and there is no output schema to compensate. The description is insufficient for reliable invocation in many scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the one-line explanations in the description add meaning beyond bare parameter names. For instance, 'destination_file_path' is clarified as 'The local path to save the file to', and 'source_blob_name' as 'The name of the file in the bucket'. However, the descriptions are minimal and largely restate the parameter names without deeper semantics like formats or constraints.
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 with a specific verb ('Download') and resource ('a file from a Cloud Storage bucket'). It distinguishes from sibling tools like upload_object and delete_object by explicitly naming the download operation, though it lacks a broader scope mention (e.g., project-specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when download is appropriate over upload/list, or mention any exclusions. The sibling list includes similar storage tools, but no comparative guidance is 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 full burden of disclosing behavior. It only states 'Stop a Compute Engine instance' and mentions a status message, but omits any side effects, permission requirements, whether the operation is asynchronous, or what happens if the instance is already stopped.
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 concise and front-loaded with the primary purpose. The Args and Returns sections are standard, though they add little beyond the schema, but they do not make the description unnecessarily 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?
The description covers the essential action, parameters, and return type. However, it lacks context about GCP permission prerequisites, lifecycle state dependencies, or how it differs from start_instance. For a simple tool, it is minimally adequate but leaves gaps that an agent might need to resolve externally.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description's Args section merely repeats the parameter names without adding formats, constraints, or examples. The schema already provides names and types, so the description adds no meaning beyond what the structured input schema offers.
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 opens with 'Stop a Compute Engine instance,' which is a clear verb+resource statement. It immediately distinguishes the tool from sibling operations like start_instance and delete_instance, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives. The description does not mention that it is for stopping running instances, nor does it reference start_instance for the reverse operation or prerequisites such as the instance existing in the specified zone.
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?
Annotations are absent, so the description carries the full burden of behavioral disclosure. It does not mention side effects, required permissions, idempotency, or any operational nuances beyond the basic action. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description follows a clear, organized docstring format with a one-line summary, Args section, and Returns. It is concise and front-loaded, though the Returns line is vague and could be more specific.
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 mutation tool with no annotations or output schema, the description lacks essential context such as permission requirements, potential side effects, or what the result precisely contains. It is minimally adequate but leaves gaps for an agent to use it safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully by explaining each parameter with concrete examples (e.g., role, member, project_id). This adds critical meaning that the bare schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Add an IAM policy binding to a GCP project.' This distinguishes it from sibling tools like check_iam_permissions and list_roles, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 vs alternatives. It does not mention any prerequisites, context, or sibling tools, leaving the agent without decision-making information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing side effects and requirements. It only states the action and return value, with no mention of permissions needed, whether the operation is asynchronous, whether the disk must exist, or any impact on the disk. This 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 well-structured and concise, with a clear purpose sentence, an Args list, and a Returns section. Every part serves a purpose, no redundant text exists, and it is front-loaded with the primary action. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no annotations, and no output schema, the description is incomplete. It omits usage guidance, prerequisites, error conditions, and behavioral details like synchronous vs asynchronous execution. The minimal Args/Returns structure does not suffice for an API operation of this complexity.
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 has no descriptions (coverage 0%), but the description includes an Args section that defines each parameter, adding meaning like the zone example ('us-central1-a') and noting description is optional. However, the explanations are minimal and lack constraints, dependencies, or format details, so it only partially compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action: 'Create a snapshot of a Compute Engine disk.' This identifies the verb, resource, and scope, distinguishing it from sibling tools like list_snapshots or create_backup. The purpose is immediately clear from the first sentence.
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., disk existence), exclusions, or situations where other tools (like create_backup) would be more appropriate. Usage context is only implied by 'Create a snapshot,' but no explicit direction is 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?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions a return status but omits that deletion is a destructive, likely irreversible action that may require specific IAM permissions and could affect attached resources like persistent disks. No warnings or side-effect information is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The docstring is well-structured with separate sections for Description, Args, and Returns. It is concise, with no redundant content, and each section directly contributes to understanding the tool's usage.
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 description covers the basic action and parameters but lacks critical context for a destructive operation. It does not mention that deletion is permanent, necessary permissions, behavior for running instances, or impact on associated disks. The return message is mentioned, but this alone is insufficient for a delete operation with no annotations or output schema.
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 has zero descriptions, so the description compensates by listing each parameter with a brief explanation and including an example for zone ('us-central1-a'). However, the explanations are largely restatements of the parameter names and add minimal depth beyond what a user would infer.
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 'Delete a Compute Engine instance' with a specific verb and resource. It distinguishes from sibling operations like start_instance, stop_instance, get_instance_details, and create_instance by specifying the delete action.
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 does not provide any guidance on when to use this tool over alternatives, such as prerequisites (e.g., stopping the instance first) or conditions where deletion might not be appropriate. No explicit exclusions or alternative tool references 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?
The description only states the basic function and return type. It does not disclose any behavioral traits such as whether instances are returned with full configuration or just summaries, whether pagination is used, or whether specific IAM permissions are required. Since no annotations are provided, the description carries the full burden of behavioral disclosure and falls short.
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 short and uses a structured Args/Returns format. However, it is slightly redundant: the first sentence says the same thing as the Args and Returns sections combined. Despite this, each sentence earns its place and there is no unnecessary fluff.
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 list tool, the description covers the basic purpose, parameter, and return value. However, given the lack of annotations and output schema, it should also clarify the scope of results (e.g., all instances in the project) and any access prerequisites. As is, it is minimally viable but leaves 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 provides only 'project_id' as a string with no description (0% coverage). The description explains the parameter as 'The ID of the GCP project to list Cloud SQL instances for', which adds minimal context beyond the parameter name itself. It does not clarify format, required role, or any constraints, but it does offer some semantic meaning.
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 Cloud SQL instances in a GCP project' with a specific verb and resource. It distinguishes from sibling tools like get_sql_instance_details (which focuses on a single instance) and list_compute_instances (which targets 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?
No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that get_sql_instance_details should be used for detailed information about a single instance, or that list_assets might offer broader asset discovery. The description assumes the agent already knows when to call 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 must disclose behavioral traits. It merely repeats the tool's name/function without stating that it is read-only, whether authentication is required, or what constitutes 'current configuration.' The verb 'List' hints at non-destructive behavior but does not explicitly guarantee it, which is insufficient without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, but the second sentence ('Returns: Current configuration settings') is mostly redundant with the first. Still, it is compact and free of unnecessary detail, earning a high 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?
For a parameterless read-only tool, the description is adequate for a basic understanding, but it lacks specifics about what fields are included in the configuration output or whether authentication is required. Given its simplicity, it is mostly complete but could benefit from clarifying the exact scope of what is listed.
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 schema coverage is 100% vacuously. The description adds context by mentioning 'Current configuration settings,' which gives a general idea of the output, but since there are no parameters to describe, the baseline of 4 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 tool's function: 'List the current Google Cloud configuration.' The verb 'List' and the resource 'current Google Cloud configuration' are specific and help distinguish it from sibling tools like config_set_project or auth_login. However, it does not explicitly call out alternatives or differentiate itself from other similarly named list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a user needs to see the current configuration, but provides no explicit guidance on when to use this tool versus alternatives like list_gcp_projects or get_gcp_project_details. It also doesn't mention any prerequisites or exclusions, leaving the context somewhat vague.
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 lists parameters and the return value but does not mention side effects such as resource persistence, potential costs, required permissions, or failure behavior, leaving significant operational context undisclosed for a mutating 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 well-structured docstring with a clear first sentence, an Args section covering all nine parameters, and a Returns section. Each line is informative and earns its place, though the parameter list necessarily makes the description longer than a simpler 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 covers all parameters and states that a status message is returned, which is useful given the absence of an output schema. However, for a complex create operation with no annotations, it lacks critical operational context such as IAM requirements, cost implications, or what the status message contains on failure, leaving clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only provides types and defaults; there are no property descriptions. The tool description fully compensates by explaining each parameter, including examples for zone, machine_type, and source_image, and clarifying optional/default values like network and external_ip. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Create a new Compute Engine instance,' which is a specific verb and resource. However, it does not explicitly distinguish this tool from sibling creation tools such as create_service_account or create_snapshot, though the resource type is clearly named.
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 get_instance_details, start_instance, or delete_instance. It only states what the tool does without any mention of use cases, prerequisites, or conditions under which it should be selected.
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 that detailed information is returned. It does not disclose authentication requirements, error behavior for invalid project IDs, or any read-only guarantees beyond the verb 'get', which is insufficient for a tool in a GCP 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 concise and well-structured with a clear one-sentence purpose followed by Args/Returns sections. Every sentence earns its place, and there is no redundant or vague 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?
For a simple single-parameter get tool, the description is minimally adequate but leaves gaps. It does not describe the output structure (no output schema), nor does it connect to the broader tool context (e.g., how to obtain project IDs). More detail would be needed to fully inform the agent.
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 0% coverage, but the description explains that project_id is the ID of the GCP project, adding basic semantic meaning. However, it lacks format details or examples, and does not compensate fully for the schema's silence.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets detailed information about a specific GCP project, using a specific verb and resource. It is easily distinguished from sibling list_gcp_projects by the verb 'get' vs 'list' and from other get_* tools by the resource type 'GCP project'.
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 does it mention required prerequisites like needing a project_id obtained from list_gcp_projects. Context is only implied by the parameter requirement, 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 must disclose behavioral traits. It only says 'Get detailed information' without mentioning that the operation is read-only (though implied), error behavior for non-existent networks, response format, or any permissions required. The description adds little beyond what the tool name suggests.
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 compact, using a standard Args/Returns docstring format. It is front-loaded with a clear purpose. However, the Returns line repeats the first sentence nearly verbatim, which is slightly redundant.
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 two-parameter getter, the description is adequate but not complete. It does not specify what 'detailed information' includes (no output schema exists), and it gives no context about when to use this vs. list_vpc_networks. The existing sibling tools and schema structure suggest a more detailed description could clarify return fields and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It provides one-liners for each parameter (project_id, network_name), but these add minimal meaning beyond the parameter names themselves, which are already self-explanatory. No format constraints, examples, or special values are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Get detailed information') and resource ('a specific VPC network'), using a specific verb and object. It distinguishes itself from sibling tools like list_vpc_networks by emphasizing 'specific' rather than listing all networks.
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 is implied: you need to provide a project_id and network_name to get details for one specific VPC. However, there is no explicit guidance on when to prefer this over list_vpc_networks or other list tools, and no prerequisites like knowing the network name beforehand are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it offers no extra context beyond restating the list action. It lacks any mention of required permissions, possible errors, or pagination behavior, making the description minimally transparent.
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 short but contains redundancy: the Returns line essentially repeats the initial purpose statement. The Args section is fine, but the overall structure could be tightened to one or two sentences without losing 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 list tool with one parameter, the description covers the basic functionality and parameter. However, it does not describe the format of the returned list (e.g., service account emails or full objects) or any edge-case behavior, leaving gaps for a tool with no output schema.
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?
Although the schema provides only a parameter title with no description, the description explicitly defines project_id as 'The ID of the GCP project,' adding the necessary meaning. This compensation is adequate for the single parameter present.
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?
Description clearly states the tool lists service accounts within a GCP project using the specific verb 'list' and resource 'service accounts'. It distinguishes itself from sibling tools like create_service_account which performs a different 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 such as create_service_account or other listing tools. The description simply states the function without any context for selection or exclusionary criteria.
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 full behavioral burden. It states the return is a list of VPC networks but does not disclose permissions, side effects, pagination, or any other behavioral traits. The word 'List' implies a read operation, 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 concise and well-structured with a purpose sentence followed by Args and Returns sections. It contains no fluff and is easy to scan.
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 tool, the description provides the essential input and output information. However, since there is no output schema, it does not describe the structure of the returned VPC networks or pagination behavior, leaving it minimally viable 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 schema has one parameter (project_id) with no description, and the description explains it as 'the ID of the GCP project to list VPC networks for,' which adds a bit of meaning. However, it lacks format examples or additional context, so it only partially compensates for the 0% 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 tool lists VPC networks in a GCP project with a specific verb and resource. It does not explicitly distinguish from siblings like get_vpc_details or list_subnets, but the scope and action are clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need to list VPC networks, but it does not provide explicit when-to-use guidance or alternatives among the sibling tools. There is no mention of scenarios where this tool is preferred over get_vpc_details or list_subnets.
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 'Resize a node pool in a GKE cluster' and returns 'Result of the node pool resize operation.' It does not reveal that this is a mutating operation with potential side effects like scaling, cost impact, long-running operations, 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 concise and well-structured, with a one-line purpose statement followed by a straightforward Args list and a brief Returns note. It is front-loaded and contains no redundant or filler content, making efficient use of space.
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?
This is a mutating operation with five required parameters and no output schema or annotations. The description only provides a high-level purpose and a vague return statement. It lacks critical context such as whether node_count is incremental or absolute, potential wait times, prerequisites like cluster availability, and side effects like cost or resource changes, making it incomplete for an agent to invoke reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The Args section lists all parameters with brief descriptions, but most are rephrased parameter names (e.g., 'project_id: The ID of the GCP project'). Only 'node_count' adds meaningful clarification by stating it is the 'new node count,' implying a target value rather than a delta. Constraints and allowed values are absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb+resource: 'Resize a node pool in a GKE cluster.' This distinguishes it from sibling tools like list_node_pools, which focuses on listing pools, by explicitly targeting the resize action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a node pool's node count needs adjustment, but it does not provide explicit when-to-use or when-not-to-use guidance, alternatives, or prerequisites. There is no mention of when to choose this tool over other node pool 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?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the action without mentioning irreversibility, required IAM permissions, or whether the operation is idempotent. The vague 'Result of the delete operation' adds no insight into side effects or error behavior.
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 standard docstring format with a one-line summary, an Args list, and a Returns line. Every sentence provides necessary information with no redundancy.
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 there is no output schema and no annotations, the description should explain return values and any side effects in more detail. It only states 'Result of the delete operation,' which is too vague to be actionable, and it omits error conditions or prerequisites.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates by explaining each required parameter succinctly: project_id, bucket_name, and blob_name. This adds meaningful context beyond the bare parameter names, though it lacks constraints or format 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 clearly states it deletes an object from a Cloud Storage bucket, specifying the exact verb (delete) and resource (object in a bucket). This distinguishes it from other delete tools like delete_instance, which target different GCP resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as list_objects or download_object. It does not mention any prerequisites, exclusions, or competing 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 gets and returns detailed information, without mentioning permissions, side effects, error behavior, or what constitutes 'detailed information.' This is minimal transparency for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured as a clear docstring with Args and Returns sections. It is succinct, but the Returns line ('Detailed information about the specified Cloud Storage bucket') is redundant with the opening sentence, adding minor waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description lacks details about the return format or any prerequisites (e.g., bucket exists, required permissions). Since there is no output schema, the description should clarify what 'detailed information' includes. It is adequate for a basic get operation but leaves 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 provides no descriptions for project_id or bucket_name, but the description's Args section adds clear definitions: 'The ID of the GCP project' and 'The name of the bucket to get details for.' This compensates for the 0% schema coverage and gives the agent meaningful parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about a specific Cloud Storage bucket.' It uses a specific verb ('get') and resource ('Cloud Storage bucket'), and the word 'specific' distinguishes it from list_storage_buckets and other get tools like get_instance_details.
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 given on when to use this tool versus alternatives. It does not mention that list_storage_buckets should be used for listing all buckets, nor any conditions or exclusions. The only implicit hint is 'specific,' but no explicit alternatives or when-not-to-use scenarios are provided.
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 behavior beyond confirming it returns information. It lacks any mention of read-only nature, required permissions, side effects, or how the response is structured. The 'Returns' line simply restates the purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized, front-loaded with the main purpose, and uses a clear Args/Returns structure. The Returns line is somewhat redundant ('Detailed information' again), but it does not waste much space.
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 read operation, the description gives the essential inputs and a generic outcome. However, with no output schema, it does not specify what fields the returned 'detailed information' contains. It also does not mention prerequisites or how this tool relates to list_gke_clusters. It is adequate but not rich.
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 Args section adds some meaning over the schema by describing each parameter. 'location' is clarified as 'region or zone', which is valuable. However, 'project_id' and 'cluster_name' descriptions are trivial (just restating the parameter names). Since schema coverage is 0%, the description partially compensates but is not thorough.
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 opens with a specific verb and resource: 'Get detailed information about a specific GKE cluster.' This clearly distinguishes it from sibling tools like list_gke_clusters (listing clusters) and get_sql_instance_details (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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need details for a specific cluster but does not explicitly state when to use this tool versus alternatives like list_gke_clusters. No exclusions or alternative recommendations are provided.
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 aspects beyond the listing action itself. It fails to explicitly state that the operation is read-only or mention permission requirements, side effects, or potential limitations.
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 fairly concise and structured with Description, Args, and Returns sections. However, the Returns section redundantly repeats the main description ('List of Firestore databases in the specified GCP project'), which prevents 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?
For a simple one-parameter list tool, the description is minimally adequate but does not describe the return format (e.g., database names, metadata, or complete resource objects). With no output schema, more detail about the returned list 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 Args section clarifies that project_id is the ID of the GCP project to list Firestore databases for, adding semantic meaning not present in the schema. Since schema_description_coverage is 0%, this parameter explanation is essential and informative.
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 'List Firestore databases in a GCP project' with a specific verb and resource. It distinguishes itself from sibling tools like list_databases by explicitly naming Firestore.
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_databases or list_firestore_collections. It merely restates the function without 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 provided, so the description carries full burden. It only states the action without disclosing side effects, return value, authentication needs, or any other behavioral traits. For a 'hello' tool, the behavior might be obvious, but it fails to state what happens or what is returned.
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, focused sentence with no wasted words. It is appropriately concise for the tool's simplicity and does not repeat schema 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?
Given the tool's very low complexity (one parameter, no output schema), the description covers the core action but omits return value and any side effects. It is minimally complete for a simple tool, but could still benefit from a brief mention of what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'name' with 0% description coverage. The description does not explicitly explain that 'name' refers to the person being greeted, though it is loosely implied. The tool fails to compensate for the lack of schema descriptions.
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 'Say hello to a person' uses a specific verb ('say') and resource ('person'), clearly distinguishing this from all sibling GCP management tools. It fully communicates the tool's purpose with no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied—'say hello' naturally indicates when to invoke this tool. However, there is no explicit guidance on when not to use it or mention of alternatives, but given the trivial nature and clear purpose, the implied usage is sufficient.
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 for behavioral disclosure. It only says 'Get details' without describing side effects, permissions required, error behaviors, or return format specifics. While 'Get' implies a read operation, this is not explicitly stated, and no additional behavioral context is added.
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 concise and well-structured with clear Args and Returns sections. No unnecessary words or repetition, and it efficiently conveys the essential information in a few lines.
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 getter tool, the description covers the core purpose and parameters. However, it lacks details about the return value structure (no output schema), does not mention potential error cases, and provides no usage guidance relative to siblings. 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.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description compensates with an Args section explaining both parameters: 'project_id' as the GCP project ID and 'deployment_name' as the deployment name. This adds meaningful context beyond the schema's bare labels, though it lacks format constraints or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets details of a specific Deployment Manager deployment, using a specific verb ('Get') and resource ('Deployment Manager deployment'). It distinguishes from sibling tools like list_deployment_manager_deployments by emphasizing 'specific', making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, exclusions, or comparison to other tools like list_deployment_manager_deployments. The usage context is only implied by the name, not explained.
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 only repeats the tool's name and return value, offering no information about read-only nature, required permissions, pagination, or alert lifecycle. This is a significant gap 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 concise and front-loaded, with the main action in the first sentence. The Args and Returns sections are clean and relevant, with no superfluous 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?
For a simple read-only tool with one parameter and no output schema, the description covers the core operation but omits expected return format, IAM requirements, and behavior when no alerts exist. These gaps are more critical because annotations and output schema are absent, making the description the sole source of behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description's Args section rephrases the parameter as 'The ID of the GCP project to get alerts for.' This adds basic context but lacks format, constraints, or examples, providing only marginal value beyond the parameter name.
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 'Get active monitoring alerts for a GCP project,' with a specific verb, resource, and scope. This distinguishes it from sibling tools like list_monitoring_metrics (metrics) and create_alert_policy (creating policies).
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 indicates the tool is for retrieving alerts for a GCP project, but does not provide explicit guidance on when to use it versus related monitoring tools. No alternatives or exclusions are mentioned, so the usage context is implied rather than 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. It mentions default behaviors for destination_blob_name and content_type, and states a return value, but it does not disclose whether existing blobs are overwritten, required permissions, or what the 'Result' actually looks like. This is a significant gap for a mutating 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 structured as a Python docstring with a clear purpose sentence followed by Args and Returns sections. It is concise and front-loaded, avoiding unnecessary filler, though the Args list could be more compact.
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 5 parameters, no annotations, and no output schema, the description should provide more complete context. It lacks crucial details about overwrite semantics, error behavior, prerequisites, and the exact shape of the return value. This leaves the agent with ambiguity when invoking 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?
Schema description coverage is 0%, but the description explains every parameter's purpose and provides default behavior for destination_blob_name and content_type. This adds meaningful context beyond the schema, though it could provide more details on valid formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Upload a file to a Cloud Storage bucket,' which is a specific verb-resource pair. It distinguishes itself from sibling tools like download_object, delete_object, and list_objects by focusing solely on the upload action.
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 when to use the tool (when uploading files to GCS) but does not explicitly mention alternatives or exclusions. No guidance is given on prerequisites like bucket existence or permissions, or when to choose this over other object 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 states that it creates a policy and returns a vague 'Result'. It does not disclose permissions required, idempotency, failure behavior, or any side effects beyond the creation itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with Args and Returns sections, making it easy to scan. It lists all 8 parameters without excessive prose. It earns a 4 because it is appropriately sized for the complexity, though it could be slightly tighter.
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 covers all parameters and states the creation action, but it lacks details about the return value format, potential errors, prerequisites, or how the created policy manifests. Given there is no output schema, some of this information would be helpful for a complete picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides an Args section that defines every parameter, including defaults and example values for metric_type and comparison. This adds meaningful context beyond the parameter names, though some descriptions are terse (e.g., filter_str).
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 states 'Create a new alert policy in a GCP project' with a specific verb and resource. This is unambiguous and distinguishes the tool from sibling monitoring tools that list alerts or metrics, though no sibling creates alert policies.
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 is implied by the action 'Create a new alert policy' – the tool is for creating policies when needed. However, there is no explicit statement of when to use it versus alternatives, nor any exclusions or prerequisites.
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. It states it returns detailed information but does not disclose potential side effects, permission requirements, or limits. For a read-only getter, this is adequate but does not enrich beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with Args and Returns sections and is not overly verbose. The opening sentence is concise and informative, though the Args section partially duplicates schema fields.
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 2-parameter getter, the description covers purpose and parameters, but the return value is vaguely described as 'detailed information'. Since there is no output schema, it should provide more specifics about what details are returned. It also lacks any usage context or error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description adds meaning. It defines both parameters: 'The ID of the GCP project' and 'The ID of the Cloud SQL instance', giving semantic context that the bare schema lacks. However, it does not include formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get detailed information about a specific Cloud SQL instance' – a clear verb+resource combination. It distinguishes itself from sibling tools like list_cloud_sql_instances and get_instance_details (which likely refers to compute instances) by naming the specific resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention that it should be used after listing instances, nor does it contrast with the sibling list_cloud_sql_instances. Usage is only implied by the tool name and the word 'specific'.
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 only states the operation and returns, without mentioning read-only behavior, side effects, pagination, or required permissions. The absence of such context 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 compact and structured with a one-line purpose, Args, and Returns. Every sentence adds value, and the format is immediately scannable. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter list operation, the description covers purpose, parameter, and return. However, it lacks explicit confirmation of read-only behavior or pagination details, which would make it more complete given the absence of annotations.
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 schema provides no description for the project_id parameter, but the docstring adds meaning: 'The ID of the GCP project to list build triggers for'. It also clarifies the return value. This compensates well for the schema's 0% 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 clearly states 'List Cloud Build triggers in a GCP project' with a specific verb, resource, and scope. It distinguishes itself from sibling list tools (e.g., list_compute_instances, list_gke_clusters) by naming Cloud Build triggers explicitly.
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 exclusions, prerequisites, or alternative tools, leaving the agent to infer usage solely from the name and generic 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 behavior. 'List' implies a read-only operation and the Returns line indicates the output, but it omits important context such as required API permissions, behavior when the instance or project is invalid, and whether any state is modified.
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 concise and well-structured: the first sentence states the core purpose, followed by minimal Args and Returns sections. Every line earns its place with no filler.
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 read-only list tool with two straightforward parameters, the description covers the action, arguments, and return value. However, since there is no output schema or annotations, it could be slightly more explicit about the exact result format and access prerequisites, though the current level is largely 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 schema has 0% description coverage, but the description's Args section defines each parameter meaningfully: project_id is the GCP project and instance_id is the Cloud SQL instance. This adds value beyond the bare schema titles.
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 resource ('databases in a Cloud SQL instance'), with the parameters identifying the project and instance. This distinguishes it from sibling tool list_cloud_sql_instances, which lists instances rather than databases.
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_cloud_sql_instances or get_sql_instance_details. There are no prerequisites, exclusions, or explicit use cases beyond the basic operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden, but only states the basic listing action and optional filter. It omits authentication requirements, pagination behavior, and error handling, providing little beyond the function name.
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 front-loaded with the main sentence, but the 'Args' and 'Returns' sections duplicate schema information and add minor whitespace overhead.
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 read-only list tool, the description provides the essential purpose and parameter semantics, but lacks details about the exact structure of the returned subnet objects since there is no output schema.
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 schema provides no parameter descriptions, but the tool description explains 'project_id' as the GCP project ID and 'region' as an optional filter. This adds meaningful context that the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists subnets in a GCP project with an optional region filter. This distinguishes it from sibling tools like list_vpc_networks which target a different resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing a list of subnets for a project, but does not explicitly state when to prefer this over alternatives like list_vpc_networks, nor does it mention any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action and return status, but does not mention consequences like whether all credentials are revoked, whether it is reversible, or whether it affects the current session. This is a destructive operation needing more 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 two short sentences, front-loaded with the purpose and including the return value. 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?
The tool is very simple (0 params, no output schema), but the description lacks context about preconditions (e.g., requiring previous auth_login) and specific side effects. It is minimally complete for the complexity, but could be more helpful by clarifying what credentials are being revoked and any irreversible effects.
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 properties, so no parameter documentation is needed. The baseline for 0 parameters is 4, and 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 clearly states the action ('Revoke') and the resource ('Google Cloud credentials'), distinguishing it from sibling auth tools like auth_login and auth_list. It is specific and actionable.
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 verb 'revoke' but there is no explicit when-to-use or alternative guidance. It doesn't mention prerequisites such as being authenticated or that this complements auth_login/auth_list. No exclusions or alternatives are provided.
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?
Since no annotations are provided, the description carries full burden for behavioral disclosure. It only restates the action and returns vague 'detailed information' without addressing permissions, side effects, error behavior, or the read-only nature. This is a significant gap for a tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose sentence, Args, and Returns sections. It is concise, front-loaded, and every sentence contributes essential information without redundancy.
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 output schema or annotations, so the description must adequately explain return values. 'Detailed information' is vague and does not specify what fields or data are included. Given the presence of a list_compute_instances sibling, more detail about the return structure would help the agent decide when to use this 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 schema has 0% description coverage, but the description's Args section explains each parameter meaningfully, including an example for zone ('us-central1-a'). It compensates well for the schema gap, though it could provide more format or constraint 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 clearly states the action ('Get'), the resource ('Compute Engine instance'), and the scope ('specific', distinguishing from listing). This also differentiates from sibling tools like list_compute_instances and get_sql_instance_details.
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 use for retrieving details of a single instance but does not explicitly mention when to use this vs list_compute_instances or other alternatives. No exclusions or conditional guidance are provided, making the usage implied 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 of behavioral disclosure. It does not mention whether the operation is read-only, what errors may occur (e.g., role not found), authentication requirements, or the structure of the returned details. The description only states the return is 'detailed information,' which is generic and lacks behavioral depth.
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 concise, front-loaded with the purpose, and logically structured with Args and Returns sections. Every sentence contributes value: the purpose sentence, the parameter explanations, and the return statement. 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?
Given the low complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It lacks specific return detail fields and error handling behavior. However, for a simple read-only tool, the description sufficiently conveys what the tool does and how to invoke it. The vague 'detailed information' leaves some ambiguity.
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 schema provides only parameter names and types with 0% description coverage. The description compensates by explaining role_name with concrete examples ('roles/compute.admin' or fully-qualified custom role paths) and clarifying that project_id is optional for custom roles. This adds meaningful context beyond the schema, though it could be more explicit about interactions between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get detailed information about an IAM role, including its permissions.' The verb 'Get' is specific, the resource 'IAM role' is well-defined, and the scope 'including its permissions' distinguishes it from sibling tools like list_roles (which lists roles) and check_iam_permissions (which checks permissions for principals).
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 parameter guidance (role_name format, optional project_id) but does not explicitly state when to use this tool versus alternatives. No exclusions or comparison with sibling tools are given. Usage context is implied through the parameter explanations but not directly addressed.
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. It mentions using the Cloud Asset Inventory API and lists page_size with a max of 1000, which implies pagination, but it does not disclose permission requirements, potential rate limits, cost implications, or whether all asset types are returned if no filter is provided. The read-only nature is implied by 'List' but not explicitly stated.
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 core description is a single front-loaded sentence, which is good. However, the Args and Returns sections largely duplicate schema information and the Returns line adds little value. It is somewhat over-specified for an experienced user but not excessively 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?
The tool has no output schema and no annotations, so the description must compensate. It provides parameter details and a basic return type, but it lacks usage guidance, potential side effects, or any caveats about the Cloud Asset Inventory API. This is adequate for a simple list operation but leaves gaps around when to use it and what to expect in terms of data scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema description coverage is reported as 0%, the description includes an Args section that thoroughly explains each parameter beyond the schema. For project_id it defines the purpose, for asset_types it gives an example and notes it's a filter, and for page_size it specifies default and max values. This significantly adds meaning to the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'List assets in a GCP project using Cloud Asset Inventory API', which uses a specific verb (list) and resource (assets via Cloud Asset Inventory). This distinguishes it from sibling tools like list_compute_instances or list_storage_buckets, which target specific resource types.
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 exclusions or specify that this is the broad asset discovery tool while other list tools are for specific resource types. The description simply states what it does without providing decision criteria.
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 shoulder the burden of disclosing behavior. It only restates the action and return type, with no mention of permissions, pagination, or whether any side effects occur (even though it is read-only, this is not explicit). This falls short of informative 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 compact and well-structured with Args/Returns sections, matching a typical docstring. Every sentence provides necessary information, and there is no redundant 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?
For a simple one-parameter list operation, the description covers the core purpose and return type. However, it omits practical context such as required permissions, potential pagination behavior, or how this listing fits with the broader Deployment Manager workflow. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description is the sole source of parameter meaning. It explains that project_id is 'the ID of the GCP project to list deployments for', which adds clear purpose beyond the schema's bare 'Project Id'. However, it does not specify allowed formats or validation 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 ('Deployment Manager deployments') within a defined scope ('in a GCP project'). It clearly distinguishes itself from sibling get_deployment_details, which focuses on a single deployment.
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 use when you need to enumerate deployments in a project, but it does not explicitly state when to choose this over alternatives, nor does it mention any exclusions or prerequisites. Guidance is only 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?
With no annotations, the description carries the full burden of behavioral disclosure. It states the action and return type but fails to mention permissions, pagination, error handling, or the exact structure of returned machine types. This is minimal transparency for a tool that could have additional behaviors.
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 uses a standard docstring format with Args and Returns sections. It is front-loaded with the purpose and every sentence contributes value. While slightly more verbose than necessary, it remains efficient and well-structured, without redundancy.
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 (2 simple string parameters) and no output schema, the description provides the essential inputs and a high-level return type ('List of available machine types'), but it does not specify the fields of each machine type or any pagination. It is adequate but not fully complete for an agent expecting exact return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by documenting both parameters: project_id (GCP project) and zone (with an example 'us-central1-a'). This adds meaningful context beyond the bare schema, giving the agent clear guidance on what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List available machine types in a specific zone.' It uses a specific verb ('List') and resource ('machine types') with a clear scoping qualifier ('in a specific zone'). This distinguishes it from sibling tools like list_compute_instances or list_gcp_projects.
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 when to use the tool (when needing machine types for a specific zone) but does not explicitly state alternatives or exclusions. It lacks any mention of when not to use it or comparison to other list tools, so usage guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses a read-only listing operation and a return type ('List of disk snapshots'), but does not mention pagination, required IAM permissions, or behavior with large results.
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 organized with Description, Args, and Returns sections, with the purpose front-loaded. The Returns line somewhat repeats the first sentence, but overall it is compact and free of unnecessary detail.
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 tool with one parameter and no output schema, the description covers what it does, the scope, the parameter meaning, and the return value. It lacks advanced details like pagination, but these are less critical for a simple list 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 no parameter descriptions (0% coverage), but the description's Args section clarifies project_id as 'The ID of the GCP project to list snapshots for', adding meaning beyond the schema title 'Project Id'.
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 'List disk snapshots in a GCP project', using a specific verb and resource. This distinguishes it from sibling tools like list_disks (disks) and create_snapshot (create).
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 scenarios, prerequisites, exclusions, or reference sibling tools such as list_disks or create_snapshot.
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 for behavioral disclosure. It only states the action and return value, omitting details about required permissions, asynchronous behavior, idempotency, or failure conditions.
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 compact and front-loaded with the purpose. The Args/Returns structure is clean and avoids redundancy, with each sentence serving a clear role.
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 straightforward operation, the description covers the action, all parameters, and return type. It lacks edge-case context (e.g., behavior if the instance is already running), but the core usage is adequately specified for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The Args block thoroughly explains each parameter: project_id as the GCP project, zone with an example format, and instance_name as the target. Since the schema has no field descriptions (0% coverage), this fully compensates and adds clear meaning.
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 opens with 'Start a Compute Engine instance', which is a specific verb+resource statement. This clearly distinguishes the tool from siblings like stop_instance, create_instance, and get_instance_details.
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, exclusions, or suggest other tools for related operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It does state the return value (list of credentials and default account), which is helpful. However, it does not explicitly state that the tool has no side effects or whether it requires prior authentication, leaving some behavioral ambiguity.
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 two short sentences, front-loaded with the main action. No wasted words 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 list tool with no parameters and no output schema, the description reasonably captures the return value. It could mention that the list reflects currently authenticated accounts, but that is already implied by 'active.' Overall sufficient.
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 is appropriate given the description adds no parameter information because none exists.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists active Google Cloud credentials, a specific action on a specific resource. The mention of returning the default account adds clarity, and it distinguishes from sibling auth tools like auth_login and auth_revoke.
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 a read-only check or that auth_login must be called first to populate credentials. No exclusion or alternative tools are named.
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. It mentions the browser-based OAuth flow and the side effect of setting a default project when project_id is provided. However, it omits details about credential persistence, user interaction (e.g., opening a browser window), or whether authentication modifies global GCP configuration.
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 succinct and front-loaded, with a main sentence followed by structured Args and Returns sections. There is no redundant or filler text; every sentence contributes useful 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 simple tool with one optional parameter and no output schema, the description adequately covers the action, the parameter's purpose, and the return status. It does not discuss error conditions or the need for an existing GCP account, but these are minor given the tool's simplicity.
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 'Args' section explains that project_id is optional and sets the default project after login, adding meaning beyond the schema's bare type and default. This compensates for the schema having no property descriptions (0% schema description 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 clearly states the tool authenticates with Google Cloud Platform using browser-based OAuth flow, specifying a distinct verb and resource. It naturally stands apart from siblings like auth_list and auth_revoke by focusing on the login action.
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 gives minimal usage context (authentication) but no explicit guidance on when to use this tool versus alternatives like auth_list or auth_revoke, nor does it mention prerequisites or exclusions. The usage is implied rather than clearly instructed.
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?
Without annotations, the description carries the full burden of behavioral disclosure. It only restates that it lists checks and returns a list, without mentioning auth requirements, pagination, or what fields are included. The read-only nature is implied but 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 docstring format is well-structured with Args and Returns sections. It is concise, front-loaded, and contains no fluff—every sentence earns its place.
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 tool with no output schema, the description covers the essential purpose, parameter semantics, and return value. It lacks some behavioral details (e.g., auth, inclusivity of checks), but is adequate for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates adequately by explaining that project_id is 'The ID of the GCP project to list Uptime checks for.' This adds meaning beyond the bare schema property name.
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+resource+scope: 'List Uptime checks in a GCP project.' This clearly distinguishes it from sibling tools like list_gcp_projects or list_monitoring_metrics, which target 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context (requires a GCP project_id) but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites such as required permissions.
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 creation action but does not mention side effects, idempotency, reversal, or response structure. The Returns line is vague ('Result of the firewall rule creation'), offering no insight into failure modes or what the returned object contains. This is a significant gap for a mutating 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 well-structured docstring with a clear one-sentence summary, then Args, and Returns. Though lengthy to cover 12 parameters, every line adds necessary information. There is no fluff or repetition, and the most critical information (action and required parameters) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (12 parameters, 5 required, no output schema), the description covers all parameters with valuable context, including direction-dependent behavior and protocol format examples. However, it omits edge cases like whether allowed and denied protocols are mutually exclusive, and the return value is described only vaguely. Overall, it is nearly complete for invocation but lacks some operational detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description is the sole source of parameter meaning. It compensates thoroughly: each parameter is described with type constraints (e.g., direction values 'INGRESS'/'EGRESS'), value ranges (priority 0-65535, lower=higher), conditional relevance (source_ranges for INGRESS, destination_ranges for EGRESS), and concrete examples for allowed_protocols and denied_protocols. This adds substantial meaning beyond the bare schema types.
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 opens with 'Create a firewall rule in a GCP project,' which clearly states a specific verb and resource. It distinguishes itself from sibling tools like list_firewall_rules by indicating a create action, and there are no other create-firewall-rule siblings, so its 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 by the verb 'create' but does not explicitly state when to use this tool versus alternatives (e.g., list_firewall_rules for inspecting existing rules). It also lacks guidance on preconditions like network existence or IAM permissions. Thus, usage context is only implied, not explicitly articulated.
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 behavioral disclosure. It only states that it 'gets' and 'returns' billing information, without describing side effects, required permissions, error behavior, or output shape. The verb 'Get' implies a read-only operation, but this is not made 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 compact: one purpose sentence plus minimal Args/Returns docstring. No filler or redundancy.
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 parameter getter, the description is moderately complete, but the return value is only described as 'Billing information', which is ambiguous. With no output schema or annotations, a slightly fuller description of what fields are returned 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 only parameter, project_id, is described as 'The ID of the GCP project', adding semantic clarity beyond the bare schema field. However, it does not specify expected format or related requirements, and schema coverage is 0%.
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 ('Get') and resource ('billing information for a GCP project'), making the tool's purpose unmistakable. No sibling tool covers billing, so it is well differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly scopes use to a GCP project via project_id, which is sufficient context for when to call it. It does not explicitly name alternatives or exclusions, so it falls short of a 5.
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 disclosure. It states the return type (list) and the filtering behavior, but does not mention permissions, pagination, or error handling. The added network filter context is slightly useful but minimal.
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 standard docstring with a concise summary, Args, and Returns sections. It is front-loaded and clear, though slightly repetitive (e.g., 'optionally filtered by network' appears in both summary and Args). No unnecessary fluff.
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 tool with two parameters, the description covers what it does, parameters, and return value. It does not discuss edge cases or errors, but given the simplicity and lack of an output schema, it is sufficiently 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 schema has no descriptions (0% coverage), so the description compensates by explaining each parameter: 'The ID of the GCP project' and 'Optional network name to filter firewall rules by'. This adds meaning beyond the bare parameter names and types.
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 'List firewall rules in a GCP project' with an optional network filter, using a specific verb and resource. This distinguishes it from sibling tools like list_vpc_networks or create_firewall_rule.
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 when to use (listing firewall rules, optionally filtered by network) but does not provide explicit exclusions or alternative tool references. Context is clear but no direct comparison to siblings.
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 must carry the behavioral burden. It states that it returns a list of permissions for the current user, implying a read-only check, but does not explicitly say it makes no modifications, what permission types are included, or any error conditions. It adds some context by specifying scope to the current user and project, but lacks richer 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?
The description is concise and well-structured: a one-line purpose statement followed by Args and Returns sections. Every sentence adds value, and the essential information is front-loaded. There is no wasted 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?
For a simple read-only tool with one parameter and no output schema, the description covers the core aspects: what it does, the parameter, and the return type. It lacks some nuance (e.g., whether permissions are project-level or resource-level), but it is sufficiently complete for a basic check 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 provides only a title 'Project Id' with no description (0% coverage). The description compensates with an Args section explaining that project_id is 'The ID of the GCP project to check permissions for.' This adds meaningful semantics for the single parameter, though it could be more detailed about expected formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Check') and resource ('IAM permissions') scoped to 'the current user in a GCP project.' This distinguishes it from siblings like add_iam_policy_binding (which modifies permissions) and get_role_permissions (which lists permissions for a role).
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 is implied by the purpose: if you need to check the current user's permissions in a project, use this tool. However, there is no explicit guidance on when to use it versus alternatives, no exclusions, and no mention of related tools like list_roles or get_role_permissions.
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. It discloses that it returns a list of collections, which implies a read-only operation, but it does not explicitly state safety, permissions, or pagination behavior. The description is adequate for a simple list but lacks deeper 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 concise docstring with a clear header sentence followed by structured Args and Returns sections. Every part earns its place, with no redundant or filler 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 simple list tool with two parameters and no output schema, the description covers the purpose, parameters, and return value adequately. It could optionally mention pagination or error behavior, but given the low complexity, this is nearly 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?
Schema description coverage is 0%, so the description must compensate. It does so by explaining both parameters: 'project_id' as the GCP project ID and 'database_id' as the Firestore database ID with a default value. This adds meaningful semantic detail beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and clearly identifies the resource ('collections in a Firestore database'). It naturally distinguishes from sibling tools like list_firestore_databases and list_storage_buckets by specifying the exact object type being listed.
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 gives no explicit guidance on when to prefer it over alternatives, nor does it mention any exclusions or prerequisites. Usage is implied by the tool's name and function, but there is no direct comparative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the action (listing), the input, and the return value, but omits details such as authentication requirements, pagination, or error behavior. For a read-only list operation, this is adequate but minimal.
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 concise docstring with a one-sentence summary, an Args section, and a Returns section. It is well-structured, front-loaded with the main purpose, and contains no fluff.
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 tool, the description covers the function, the parameter, and the return value. It lacks advanced context like permissions or pagination, but given the tool's simplicity, it is sufficiently complete for an agent to select and invoke it correctly.
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 schema only defines project_id as a string without description. The description adds meaning by stating 'The ID of the GCP project to list services for', which clarifies the parameter's purpose beyond what the schema 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 clearly states 'List enabled services/APIs in a GCP project' using a specific verb and resource. The term 'enabled services/APIs' distinguishes this from sibling tools like list_gcp_projects, which lists projects.
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 gives no explicit guidance on when to use this tool vs alternatives. However, the tool's purpose is clear from the name and description, so usage is implicitly understood. With many sibling list tools, a note differentiating it from list_gcp_projects or list_assets would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It mentions listing clusters but does not explicitly state this is a read-only operation, nor does it mention pagination or any other behavior. For a simple list tool, 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 concise with a one-sentence summary followed by Args and Returns sections. No fluff, and the essential information is front-loaded. Every sentence adds value.
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, the description is mostly complete: it states the purpose, parameters, and return type. However, it does not detail the structure of the returned cluster objects or mention pagination, which could be useful if the list is large. This is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions (0% coverage), so the Args section adds meaningful context: project_id is defined as the GCP project ID, and region is described as optional with a concrete example ('us-central1'). This compensates for the schema gap, though it does not specify the exact format of project_id.
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), resource (Google Kubernetes Engine (GKE) clusters), and scope (GCP project). This distinguishes it from sibling tools like list_compute_instances or list_node_pools.
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 context by explaining the project_id and optional region filter, but it does not explicitly state when to use this tool versus alternatives like get_cluster_details or list_node_pools. Usage is implied but not directly contrasted with siblings.
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 for behavioral disclosure. It states it returns a list of metrics and mentions an optional filter, but does not disclose safety, permissions, or error behavior. Since it's a simple read-only list operation, the lack of side effects is implied but not explicitly stated.
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 brief and structured with Args and Returns sections, but it repeats the purpose ('List available monitoring metrics') in both the opening and the Returns line, introducing slight redundancy. It is still appropriately sized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with only two parameters and no output schema, the description is largely complete: it explains the function, parameters, and return type. It lacks minor context like error conditions or pagination, but covers the essential 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.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description's Args section clearly explains both parameters: project_id as the GCP project ID and filter_str as an optional filter. This fully compensates for the schema gap by adding meaning beyond the structured fields.
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 'List available monitoring metrics for a GCP project' with a specific verb and resource. It distinguishes itself from sibling monitoring tools like get_monitoring_alerts and list_uptime_checks by focusing on metrics.
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 by stating it lists metrics for a GCP project, but does not explicitly discuss when to use it versus alternatives or mention any prerequisites. There are no exclusions or alternative tool recommendations, so guidance is only implied.
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?
Annotations are absent, so the description carries full responsibility for behavioral disclosure. It states the return value ('Returns: List of node pools in the specified GKE cluster') but does not explicitly declare the operation as read-only, mention permission requirements, or describe error behavior. This is adequate but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, starting with a clear one-line purpose, followed by structured Args and Returns sections. There is no redundancy or filler, and every sentence adds value.
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 simple with three parameters and no output schema, and the description documents all parameters and the return type. However, it lacks behavioral context such as authentication requirements or error handling, which would make it 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 provides only generic titles (Project Id, Cluster Name, Location), while the description explains each parameter with meaningful details, such as 'location (region or zone)'. Since schema coverage is 0%, this compensation is valuable, though the explanations are not exhaustive (e.g., no format or allowed values).
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'), the resource ('node pools'), and the context ('in a GKE cluster'), which distinguishes it from sibling tools like list_compute_instances and list_gke_clusters. It is specific 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 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, nor any exclusions or prerequisites. The description does not name sibling tools or conditions for use, so it falls at the 'implied usage' level.
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 explaining behavior. It mentions the 'limit' parameter as maximum objects and 'prefix' as a filter, which are behavioral details. However, it does not disclose pagination behavior, permissions required, or error conditions, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with Args and Returns sections, front-loaded with the main purpose. It is concise but slightly repetitive in the Returns line echoing the first sentence. Overall efficient and readable.
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 no output schema, the description covers the essential information: purpose, parameters, and return value. It does not explain pagination or edge cases, but the tool is straightforward and the documentation is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description fully explains each parameter: project_id, bucket_name, prefix as an optional filter, and limit with a default value. This adds meaning beyond the schema's bare types and titles.
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 states 'List objects in a Cloud Storage bucket' with a specific verb and resource, clearly distinguishing it from sibling tools like list_storage_buckets and upload_object. The tool's 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?
Usage context is implied by the name and description: use this tool to enumerate objects within a specific bucket. No explicit when-to-use or alternative guidance is provided, but it is clear enough for a straightforward listing operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The word 'List' implies a read-only operation and the return of a list of buckets. However, it does not disclose permissions, pagination, or error behavior. For a simple list operation, this 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 concise and well-structured: a clear operation sentence, followed by an Args section and a Returns section. There is no redundant text, making it easy to parse quickly.
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 simple (one parameter, no output schema), and the description covers the purpose, the parameter, and the return type. It is complete enough for an agent to invoke correctly, though it omits details about permissions or edge cases that could be important in some contexts.
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 schema has 0% description coverage for project_id, but the description's Args section explicitly defines it: 'The ID of the GCP project to list buckets for'. This fully compensates for the schema's lack, giving clear semantic meaning to 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 'List Cloud Storage buckets in a GCP project', using a specific verb and resource with a defined scope. This distinguishes it from sibling tools like get_bucket_details, which targets a single bucket. The Args and Returns sections further clarify 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions. Usage is implied by the purpose and the required project_id, but there is no reference to sibling tools like get_bucket_details for single-bucket lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool sets a default project and returns a status message, implying a persistent configuration change. However, it does not mention permissions needed, side effects, or whether the change is reversible.
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 concise and well-structured with separate sections for summary, arguments, and return value. It contains no extraneous information and is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter setter, the description covers the purpose, parameter meaning, and return type. It lacks usage guidance and prerequisites, but given the simplicity of the tool and the absence of an output schema, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly explains the only parameter, project_id, as 'The ID of the project to set as default', adding semantic meaning beyond the schema which only provides type and title. Since schema description coverage is 0%, this is essential context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Set') and resource ('default Google Cloud project'), making its purpose unambiguous. It is easily distinguished from sibling tools like set_quota_project and list_gcp_projects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one needs to set the default project, but it does not explicitly state when to use this tool versus alternatives like set_quota_project. No exclusions or contextual guidance is provided beyond the literal purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It clearly indicates a read-only list operation (based on 'List'), but doesn't add context about authentication, permissions, rate limits, or behavior on empty results. It discloses core behavior but is minimal.
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?
Compactly structured docstring: one-line summary, Args with two bullets, Returns line. No fluff, though the Returns line slightly repeats the summary. Efficient and well-organized.
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 tool with no annotations and no output schema, the description covers the purpose, both parameters, and return type. It could mention that listing is across all zones unless zone is specified, but the optional zone implies that. Adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has no descriptions (0% coverage), but the description provides clear semantics for both parameters: project_id and zone, including an example for zone. This fully compensates for the schema gap.
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?
Describes the tool as 'List Compute Engine instances in a GCP project' – a specific verb and resource. Distinguishes from siblings like list_gcp_projects and get_instance_details by targeting the instance listing specifically.
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?
Provides implied usage through its description (list instances when needed), and the optional zone parameter indicates filtering usage. However, it lacks explicit guidance on when to use this vs alternatives like get_instance_details or start_instance, and doesn't mention any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the core behavior (listing projects) and the return type (list of project IDs), which is useful. However, it does not mention pagination, potential large result sets, authentication requirements beyond 'authenticated user', or error conditions. 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 two sentences, front-loading the purpose and then clearly stating the return value. There is no redundant information; every word contributes to understanding the tool's function.
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, parameterless, read-only listing tool, the description is complete: it states what it lists, for whom, and what it returns. No output schema exists, so including the return type is necessary and sufficient. Edge cases like empty lists are not critical for this minimal 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, and the schema coverage is 100% (vacuously). The baseline for 0 parameters is 4. The description adds no parameter-specific details because none are needed, but it does clarify the return format, which is a minor bonus beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('GCP projects') with a clear scope ('all available ... for the authenticated user'). This clearly distinguishes it from siblings like get_gcp_project_details, which focuses on a single project's details.
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 use when an overview of all accessible GCP projects is needed, but it does not explicitly contrast with alternatives or state when not to use this tool. No exclusions or alternative references are provided, leaving usage guidance to inference from the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral transparency burden. It discloses that the output depends on project_id, changing from predefined to custom roles. It also states the return type. However, it doesn't mention potential errors, permissions, or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured in a docstring with Args and Returns sections, containing only essential information. The Returns line is concise but adds marginal value, keeping the description 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?
For a simple list tool with one optional parameter, the description covers the parameter behavior and return type. It lacks details on pagination or large result sets, but the simplicity of the tool makes this acceptable.
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 schema provides only the parameter name and type (null/string). The description adds meaning by explaining project_id selects custom roles, and its absence yields predefined roles. This fully compensates for the 0% 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 clearly states the tool lists IAM roles, specifying predefined or custom variants. It uses a specific verb and resource, distinguishing it from sibling tools like get_role_permissions which focus on permissions.
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 explains when to provide project_id (for custom roles) and the default behavior (predefined roles), but it does not compare against alternative tools or state explicit exclusions. This provides context but lacks when-not guidance.
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. It provides parameter constraints but does not disclose behavioral traits like idempotency, permission requirements, or error handling. The return value is vaguely described as 'Result of the service account creation.'
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 docstring is concise and well-structured, stating the purpose first, then listing each argument and the return value without 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 create tool with no output schema and no annotations, the description is adequate but lacks detail on return values and edge cases (e.g., duplicate account_id). It does not mention prerequisites like IAM permissions or project existence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains all four parameters, including the 6-30 character constraint on account_id, adding meaning beyond the bare schema types. This fully compensates for the 0% schema description 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 clearly states 'Create a new service account in a GCP project,' using a specific verb and resource. It distinguishes itself from sibling tools like list_service_accounts and create_instance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: this tool is for creating a service account in a GCP project. However, it does not explicitly mention when not to use it or alternatives, though none obvious exists among siblings.
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 transparency burden. It accurately states the effect (setting a quota project), the contextual warning it resolves, and the return format (confirmation or error). However, it does not disclose side effects, persistence, or permission requirements, which are relevant for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description uses a clear docstring structure with purpose, context, args, and returns. The quoted warning is valuable but adds length; overall it remains focused and free of filler.
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 tool with no output schema, the description covers what, why (the warning), parameter semantics, and return behavior. It could additionally mention persistence or side effects, but it is appropriately complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only labels project_id as 'Project Id' with no description, and schema coverage is 0%. The description compensates fully by explaining it as 'The ID of the GCP project to use for quota attribution', clearly conveying the meaning and role of the 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 states a specific action ('Set a quota project') with its resource ('for Google Cloud API requests'), clearly distinguishing it from siblings like config_set_project by focusing on quota attribution rather than project config. The explicit mention of the warning scenario adds scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a clear trigger for use by quoting the specific warning message ('Your application has authenticated using end user credentials from Google Cloud SDK without a quota project'). This tells an agent when to invoke the tool, though it does not explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the core behavior (listing disks, optional zone filter) and the return type, but does not explicitly state read-only semantics, pagination behavior, or permission requirements, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded, with a clear one-line summary, an Args section, and a Returns section. Every sentence earns its place without unnecessary verbosity.
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 simple with only two parameters and no output schema. The description adequately covers the purpose, parameters, and return value. It could mention edge cases like empty results or required permissions, but the core information is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions for parameters (0% coverage), but the description compensates by explaining both `project_id` and `zone`, including an example for `zone`. This adds meaningful guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Compute Engine persistent disks in a GCP project, using a specific verb and resource. It is distinct from sibling tools like list_compute_instances and list_storage_buckets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (listing disks in a project, optionally filtered by zone). It does not explicitly mention alternatives or when not to use it, but the context is sufficient for most cases.
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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