GCP MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific GCP resources and actions, with clear boundaries between services like Compute Engine, Cloud Storage, IAM, and monitoring. However, some overlap exists between list_assets and other listing tools, and say_hello is an outlier that could cause confusion.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, such as create_instance, list_firewall_rules, get_bucket_details, and delete_object. The naming convention is uniform across all 56 tools, making them predictable and easy to understand.
Tool Count2/5
With 56 tools, the count is excessive for a single server, making it overwhelming and difficult for agents to navigate efficiently. While GCP is broad, this many tools suggests poor scoping and could lead to confusion or performance issues in tool selection.
Completeness4/5
The toolset provides comprehensive coverage across multiple GCP services, including authentication, compute, storage, networking, IAM, and monitoring, with CRUD operations for many resources. Minor gaps exist, such as missing update operations for some resources like firewall rules or service accounts, but core workflows are well-supported.
Average 3.2/5 across 56 of 56 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool creates a backup but doesn't describe what that entails—whether it's a full or incremental backup, how long it takes, if it requires downtime, what permissions are needed, or potential side effects. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured with clear sections for Args and Returns. It uses bullet-like formatting for parameters, making it easy to scan. There's no unnecessary verbosity, and the information is front-loaded with the main purpose stated first.
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 complexity (a mutation tool for backups), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return value beyond 'Result of the backup operation,' nor does it cover behavioral aspects like error handling or operational impact. For a tool with 3 parameters and significant implications, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds basic semantics by listing parameters and their purposes (e.g., 'project_id: The ID of the GCP project'), which helps clarify what each parameter means. However, it doesn't provide format examples, constraints, or deeper context, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Create a backup for a Cloud SQL instance.' It specifies the verb ('create') and resource ('backup for a Cloud SQL instance'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'create_snapshot' or 'list_snapshots', which might be related backup operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., instance must be running), when not to use it (e.g., during peak hours), or refer to sibling tools like 'create_snapshot' for comparison. The usage context is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a delete operation (implying destructive), but doesn't mention whether deletion is permanent, reversible, requires specific IAM permissions, has rate limits, or what happens with non-existent objects. The return value description ('Result of the delete operation') is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with clear sections (purpose, Args, Returns). The first sentence states the core purpose directly. The Args section could be more concise but isn't excessively verbose.
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 destructive operation with no annotations and no output schema, the description is inadequate. It doesn't explain what 'Result of the delete operation' means (success/failure indicators, error conditions), doesn't mention authentication requirements, and provides minimal behavioral context for a potentially irreversible action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a basic Args section naming the three parameters and their purpose, which adds meaningful context beyond the bare schema. However, it doesn't explain format requirements (e.g., bucket naming conventions), validation rules, or provide examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete an object') and resource ('from a Cloud Storage bucket'), providing specific verb+resource pairing. It doesn't explicitly differentiate from sibling tools like 'delete_instance' or 'download_object', but the cloud storage context is reasonably distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, permissions needed, or when this operation is appropriate versus other deletion tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool downloads a file but doesn't describe key behaviors: whether it overwrites existing local files, handles errors (e.g., missing files or permissions), supports partial downloads, or has rate limits. For a mutation tool (file download implies local write), this lack of detail is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by parameter details. It uses clear sections (Args, Returns) and avoids unnecessary words. However, the 'Returns' statement ('Result of the download operation') is vague and could be more informative, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (file download with 4 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return value format, error handling, or behavioral nuances (e.g., file overwriting). For a tool that performs I/O operations, more context is needed to ensure safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists all four parameters with brief explanations (e.g., 'The name of the bucket to download from'), adding meaning beyond the schema, which has 0% description coverage. However, it doesn't provide format details (e.g., path syntax, blob naming conventions) or examples, leaving some ambiguity. Since schema coverage is low, the description compensates partially but not fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Download a file from a Cloud Storage bucket.' It specifies the verb ('download') and resource ('file from a Cloud Storage bucket'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'upload_object' or 'delete_object' beyond the obvious verb difference, which is why it's not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication, permissions), when not to use it (e.g., for large files or streaming), or compare it to siblings like 'list_objects' for browsing or 'upload_object' for the opposite operation. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves billing information but does not describe traits like required permissions, rate limits, error handling, or output format. For a read operation with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a clear purpose statement followed by Args and Returns sections. However, the Returns section is vague ('Billing information') and could be more informative, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a read operation with potential complexity (billing data), the description is incomplete. It lacks details on authentication, permissions, data format, and error cases, making it inadequate for safe and effective use by an AI 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 description adds minimal semantics: it explains that 'project_id' is 'The ID of the GCP project to get billing information for.' With 0% schema description coverage and only one parameter, this provides basic meaning but does not elaborate on format (e.g., project ID structure) or constraints. The baseline is appropriate given the low parameter count.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get billing information for a GCP project.' It specifies the verb ('Get') and resource ('billing information'), and the context ('for a GCP project') is clear. However, it does not explicitly differentiate from sibling tools like 'get_gcp_project_details' or other 'get_' tools, which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., authentication), exclusions, or related tools. With many sibling tools available, this lack of context leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implying read-only), but doesn't specify authentication requirements, rate limits, error conditions, or what 'detailed information' includes (e.g., metadata, configuration, IAM policies). For a cloud resource tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Each sentence earns its place by defining the tool's function and parameters. It could be slightly more concise by integrating the purpose with the Args section, but overall it's efficient and front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is minimally complete. It covers the basic purpose and parameters but lacks details on authentication, error handling, return format, or integration with sibling tools. For a cloud storage tool in a server with many siblings, more contextual guidance would be beneficial, but it meets the minimum viable threshold.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds basic semantics by naming and briefly describing both parameters ('project_id: The ID of the GCP project', 'bucket_name: The name of the bucket to get details for'), which compensates partially. However, it doesn't provide format examples, constraints, or relationship between parameters, keeping it at a baseline adequate level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get detailed information') and resource ('Cloud Storage bucket'). It distinguishes from sibling tools like 'list_storage_buckets' by focusing on a single bucket rather than listing multiple. However, it doesn't explicitly contrast with 'get_gcp_project_details' or other 'get_*' tools, which would require more explicit differentiation for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'list_storage_buckets' for overviews or other 'get_*' tools for different resource types. There are no prerequisites, exclusions, or contextual hints provided, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets' information, implying a read-only operation, but doesn't specify whether it requires specific permissions, has rate limits, returns structured data, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first in a clear sentence. The Args and Returns sections are structured but could be more concise; for example, 'Returns: Detailed information about the specified GCP project' is somewhat vague. Overall, it avoids unnecessary verbosity while maintaining clarity.
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 complexity (a read operation with no output schema and zero annotation coverage), the description is incomplete. It lacks details on authentication requirements, error handling, return format (e.g., JSON structure), and how it differs from sibling tools. Without annotations or an output schema, the description should provide more context to guide effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'project_id' is 'The ID of the GCP project to get details for', which clarifies the parameter's purpose beyond the schema's basic type. However, it doesn't provide format examples (e.g., 'my-project-123'), validation rules, or context about where to find the ID, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific GCP project'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'list_gcp_projects' or 'get_instance_details', which would require mentioning it retrieves comprehensive metadata for a single project rather than listing projects or getting instance-specific 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 doesn't mention prerequisites (e.g., authentication), compare it to sibling tools like 'list_gcp_projects' for listing projects or 'get_instance_details' for instance-specific info, or specify scenarios where this tool is appropriate (e.g., retrieving project metadata for auditing or configuration).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Get active monitoring alerts' but doesn't disclose behavioral traits such as authentication requirements, rate limits, pagination, or what 'active' means (e.g., time range, severity). This leaves significant gaps for an agent to understand how to invoke it effectively.
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 appropriately sized and front-loaded, starting with the core purpose, followed by Args and Returns sections. Every sentence earns its place without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of monitoring alerts and the lack of annotations and output schema, the description is incomplete. It doesn't explain return values beyond 'Active alerts', leaving the agent uncertain about the response format, structure, or any limitations. For a tool with no structured support, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by explaining that 'project_id' is 'The ID of the GCP project to get alerts for'. This clarifies the parameter's purpose beyond the schema's title 'Project Id'. However, with only one parameter and no additional details like format or constraints, it provides basic but not comprehensive semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'active monitoring alerts for a GCP project', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'list_monitoring_metrics' or 'list_uptime_checks', which might be related but not explicitly contrasted.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions 'active monitoring alerts' but doesn't specify prerequisites, exclusions, or compare it to other monitoring-related tools in the sibling list, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states this is a read operation ('Get'), but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, or what 'detailed information' includes. The description is minimal and lacks necessary context for safe use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with three sentences: purpose, parameters, and return value. It's front-loaded with the main purpose first. However, the Args/Returns sections could be more integrated into the flow rather than separate bullet points.
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 incomplete. It doesn't explain what 'detailed information' includes, authentication needs, error handling, or how it differs from similar tools. For a read operation with 2 parameters, this leaves significant gaps for an AI 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?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by naming the parameters and their purposes ('project_id: The ID of the GCP project', 'instance_id: The ID of the Cloud SQL instance'), but doesn't provide format details, constraints, or examples. This partially compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about a specific Cloud SQL instance.' It specifies the verb ('Get'), resource ('Cloud SQL instance'), and scope ('specific'). However, it doesn't explicitly differentiate from sibling tools like 'get_instance_details' or 'list_cloud_sql_instances'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_cloud_sql_instances' for listing instances or 'get_instance_details' for other instance types, nor does it specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implying read-only), but doesn't specify permissions needed, rate limits, error conditions, or what 'detailed information' includes (e.g., subnets, routes, peerings). For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by Args and Returns sections. It's appropriately sized with no redundant information. However, the 'Returns' section is vague ('Detailed information about the specified VPC network') and could be more specific without adding excessive length.
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 complexity of VPC networks and the lack of both annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' includes, potential authentication requirements, error handling, or how it differs from related tools. For a tool that likely returns complex network data, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by explaining 'project_id' as 'The ID of the GCP project' and 'network_name' as 'The name of the VPC network', which clarifies what each parameter represents. However, it doesn't provide format examples, constraints, or how to find valid values, leaving room for ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific VPC network'). It distinguishes from sibling tools like 'list_vpc_networks' by focusing on a single VPC rather than listing multiple. However, it doesn't explicitly mention how it differs from other 'get_*_details' tools like 'get_instance_details' or 'get_bucket_details' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to use 'get_vpc_details' instead of 'list_vpc_networks' for overviews, or how it relates to other 'get_*_details' tools. There's also no information about prerequisites, such as authentication or project access requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions listing triggers but fails to disclose behavioral traits like pagination, rate limits, permission requirements, or output format details. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose, followed by structured Args and Returns sections. It is appropriately sized with no redundant sentences, though the formatting could be slightly more streamlined.
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, no output schema, and low schema coverage, the description is incomplete. It lacks details on authentication, error handling, return structure, and behavioral constraints, making it inadequate for a tool that interacts with GCP resources.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by explaining that 'project_id' is for specifying the GCP project to list build triggers for. This compensates partially, though it doesn't detail format constraints or examples. With one parameter, the baseline is 4, but the lack of schema coverage reduces it to 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Cloud Build triggers in a GCP project'), making the purpose unambiguous. However, it does not differentiate from sibling tools like 'list_cloud_sql_instances' or 'list_gke_clusters' beyond the specific resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context about prerequisites (e.g., authentication), exclusions, or comparisons to other list tools, leaving the agent to infer usage based on the resource name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but fails to mention critical aspects like pagination, rate limits, authentication requirements, or error handling. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with three sentences that are front-loaded: the first states the purpose, followed by Args and Returns sections. There's no wasted text, though the structure is basic and could be more integrated.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain the return format (e.g., structure of the list, fields included), error conditions, or behavioral traits like pagination. For a tool with zero structured coverage, this leaves the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantic value beyond the input schema. It documents the single parameter 'project_id' and its purpose, but with 0% schema description coverage, it doesn't compensate by explaining format constraints (e.g., GCP project ID syntax) or providing examples. The baseline is 3 due to the single parameter, but it doesn't fully address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Cloud SQL instances in a GCP project'), making the purpose immediately understandable. It distinguishes from siblings like 'list_compute_instances' or 'list_databases' by specifying the resource type, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_sql_instance_details' (for specific instances) or 'list_gcp_projects' (for broader context). It lacks any mention of prerequisites, exclusions, or recommended contexts, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it states this is a list operation (implying read-only), it doesn't mention whether this requires specific IAM permissions, whether results are paginated, what format the returned list uses, or any rate limits. For a GCP API tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses minimal words to convey the essential information. Every sentence serves a purpose: the first states the tool's function, the args section documents parameters, and the returns section describes the output. It could be slightly more concise by combining the purpose and returns statements, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a read-only list operation with 2 parameters and no output schema, the description provides adequate but minimal coverage. It explains what the tool does and documents parameters, but doesn't address important contextual elements like authentication requirements, pagination behavior, error conditions, or how the returned list is structured. For a GCP API tool with no annotations, more completeness would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly documents both parameters (project_id and zone) with brief explanations, which adds value since the schema has 0% description coverage. However, it doesn't provide format details (e.g., GCP project ID format, valid zone patterns) or explain what happens when zone is omitted (returns all zones). With 2 parameters and schema coverage at 0%, the description provides basic but incomplete parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List Compute Engine instances') and resource ('in a GCP project'), making the purpose immediately understandable. It distinguishes from siblings like 'get_instance_details' (which retrieves details of a specific instance) and 'create_instance' (which creates new instances). However, it doesn't explicitly differentiate from other list tools like 'list_assets' or 'list_gke_clusters', which is why it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'get_instance_details' (for specific instance details) or 'list_assets' (which might include instances among other resources). There's no discussion of prerequisites, authentication requirements, or typical use cases for listing instances versus other list operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe important behaviors like whether this is a read-only operation, what permissions are required, how results are formatted, or if there are rate limits. The description is minimal and lacks 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Every sentence serves a purpose, though the Returns section could be more informative given there's no output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with 2 parameters and no output schema, the description covers the basics but lacks important context. Without annotations, it should explain more about the operation's safety profile, return format, and usage considerations. The parameter explanations help, but overall completeness is only adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly names and explains both parameters (project_id and instance_id) in the Args section, adding meaningful context beyond the schema which has 0% description coverage. However, it doesn't provide format examples, constraints, or additional semantic details about these parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('databases in a Cloud SQL instance'), making the purpose immediately understandable. It distinguishes from siblings like 'list_cloud_sql_instances' by specifying databases rather than instances, though it doesn't explicitly mention this distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. While the description implies it's for listing databases within a specific Cloud SQL instance, it doesn't mention prerequisites, related tools, or scenarios where other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions listing deployments but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, or what data is included in the list. This leaves significant gaps for a tool that likely interacts with cloud resources.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences: purpose, input, and output. It's front-loaded with the main action, and each sentence adds value without redundancy, though the Args/Returns formatting is slightly verbose.
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, no output schema, and low schema coverage, the description is incomplete. It lacks details on return format (e.g., structure of deployments), error handling, or prerequisites like authentication, which are crucial for a cloud resource tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by explaining that 'project_id' is for specifying the GCP project. This partially compensates, but it doesn't provide details like format or constraints. With one parameter and some added context, it meets the baseline for minimal viability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Deployment Manager deployments in a GCP project'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_deployment_details' or other list tools, which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., 'get_deployment_details' for specific deployments or other list tools for different resources). It only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the operation is a 'List' which implies read-only behavior, but doesn't mention authentication requirements, rate limits, pagination behavior, error conditions, or what format the returned list takes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Every sentence serves a purpose, though the Returns section could be more informative given there's no output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list operation with 1 parameter and no output schema, the description covers the basics but leaves gaps. It explains what the tool does and documents the parameter, but doesn't address behavioral aspects like authentication, error handling, or return format details that would be helpful for an AI 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 description explicitly documents the single parameter 'project_id' in the Args section, providing semantic meaning beyond the schema's 0% coverage. However, it doesn't explain format requirements (e.g., GCP project ID format) or provide examples. With 1 parameter and schema coverage at 0%, the description adds value but could be more comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('Firestore databases in a GCP project'). It distinguishes from siblings like 'list_databases' by specifying Firestore databases, but doesn't explicitly differentiate from 'list_firestore_collections' which operates at a different resource level.
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_databases' (which might list other database types) or 'list_firestore_collections' (which lists collections within a database). It only states what the tool does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool lists metrics but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, or whether it's read-only (implied by 'list' but not explicit). The description adds minimal context beyond the basic function, leaving gaps in understanding how the tool behaves operationally.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by Args and Returns sections. Each sentence earns its place by defining the tool and parameters. It could be slightly more concise by integrating the parameter explanations into the main text, but overall it's efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides basic context: purpose and parameters. However, for a tool with 2 parameters and operational complexity (e.g., interacting with GCP monitoring), it lacks details on return format (beyond 'List of available monitoring metrics'), error handling, or prerequisites. It's minimally adequate but has clear gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'project_id' as 'The ID of the GCP project to list metrics for' and 'filter_str' as 'Optional filter string to narrow down the metrics,' which clarifies purpose and optionality. However, it doesn't detail filter syntax or project ID format, leaving some semantic gaps. With 2 parameters and partial compensation, a baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List available monitoring metrics for a GCP project.' It specifies the verb ('list'), resource ('monitoring metrics'), and scope ('GCP project'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_monitoring_alerts' or other 'list_' tools, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions an optional filter parameter but doesn't explain when filtering is appropriate or compare to other monitoring-related tools (e.g., 'get_monitoring_alerts'). Without usage context or exclusions, the agent lacks decision-making cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists VPC networks but doesn't describe key behaviors: whether it requires specific permissions, how results are formatted (e.g., JSON, paginated), error handling, or rate limits. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured: a clear purpose statement followed by Args and Returns sections. It avoids redundancy and uses minimal sentences. However, the Returns section could be more specific (e.g., 'List of VPC network objects'), and the formatting includes unnecessary indentation, slightly affecting readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It lacks behavioral details (e.g., permissions, pagination), usage context, and output specifics. While the purpose is clear, the agent would struggle to use it effectively without additional context or trial-and-error, especially compared to more descriptive siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantic value beyond the input schema. It documents the single parameter ('project_id') in the Args section, but the schema already defines it as a required string with title 'Project Id'. With 0% schema description coverage, the description compensates slightly by confirming the parameter's purpose, but doesn't provide format examples (e.g., 'my-project-123') or constraints. This meets the baseline for adequate but not helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List Virtual Private Cloud (VPC) networks in a GCP project.' It specifies the verb ('List') and resource ('VPC networks'), and distinguishes it from siblings like 'get_vpc_details' (which likely retrieves details of a specific VPC) by focusing on listing all networks. However, it doesn't explicitly differentiate from other list tools (e.g., 'list_subnets'), so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication, project access), compare it to siblings like 'list_subnets' or 'get_vpc_details', or specify use cases (e.g., inventory, troubleshooting). The agent must infer usage from the name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the action ('say hello') but doesn't disclose behavioral traits like what 'say' means (e.g., output format, side effects, permissions needed). For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded with a single sentence that directly states the purpose. There is no wasted text, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what 'say hello' returns or how it behaves, leaving gaps for the agent to guess. It should provide more context for proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It implies a 'person' parameter but doesn't explicitly name or describe the 'name' parameter from the schema. The description adds minimal meaning beyond the schema, barely meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('say') and resource ('to a person'), making it immediately understandable. However, it doesn't differentiate from sibling tools, which are all unrelated GCP operations, so it doesn't need sibling differentiation but could be more specific about what 'say hello' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is an 'Add' operation (implying mutation) but doesn't address critical aspects like required permissions, whether this overwrites existing bindings, rate limits, or what constitutes a successful operation. The return value description ('Result of the policy binding operation') is too vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a clear purpose statement followed by parameter documentation. The Args/Returns structure is helpful, though the return description could be more specific. No wasted sentences, but the formatting with extra whitespace slightly reduces efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens on success/failure, permission requirements, or how this interacts with existing policy bindings. The return value description is vague, leaving the agent uncertain about what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by providing clear explanations for all three parameters, including format examples for 'role' and 'member'. This adds substantial value beyond the bare schema, though it could benefit from mentioning constraints like valid role formats or member types.
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 ('Add an IAM policy binding') and target resource ('to a GCP project'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'check_iam_permissions' or 'get_role_permissions', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. While the context suggests this is for IAM policy management, there's no explicit comparison with related tools like 'list_roles' or 'create_service_account'.
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 mentions the action ('Revoke') and a generic return ('Status message'), but lacks critical details such as authentication requirements, whether this affects all credentials or specific ones, potential side effects, or error conditions.
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 front-loaded, with the core purpose stated first and a return value note added efficiently. However, the return statement could be integrated more seamlessly, and some redundancy exists (e.g., 'credentials' repeated).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with security implications), no annotations, and no output schema, the description is insufficient. It misses details like what 'revoke' entails, authentication needs, or error handling, making it incomplete for safe agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Revoke') and resource ('Google Cloud credentials'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'auth_list' or 'auth_login', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing active credentials to revoke), exclusions, or related tools like 'auth_login' for context, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks permissions but doesn't mention whether this is a read-only operation, what authentication is required, potential rate limits, or error conditions. The description is minimal and lacks crucial behavioral details for a tool that likely interacts with GCP IAM.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the main purpose, followed by Args and Returns sections. It's concise with no wasted sentences, though the formatting includes extra whitespace. Every sentence earns its place by explaining the tool's function and parameters efficiently.
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 complexity of IAM permissions checking, no annotations, and no output schema, the description is incomplete. It doesn't explain the return format (e.g., list structure, permission strings), authentication requirements, error handling, or how it differs from similar tools. This leaves significant gaps for an AI agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'project_id' by explaining it's 'The ID of the GCP project to check permissions for.' This clarifies the parameter's purpose beyond the schema's basic title ('Project Id'). With 0% schema description coverage and only one parameter, this compensation is adequate, though not exhaustive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check IAM permissions for the current user in a GCP project.' It specifies the verb ('check'), resource ('IAM permissions'), and scope ('current user in a GCP project'). However, it doesn't explicitly differentiate from sibling tools like 'get_role_permissions' or 'list_roles', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_role_permissions' or 'list_roles', nor does it specify prerequisites such as authentication or project access. The only implied context is checking permissions for the current user, but no explicit usage 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return content but doesn't cover critical aspects like whether this requires specific permissions, how it handles authentication state, or potential rate limits. This is inadequate for a tool that interacts with credentials.
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 highly concise with two brief sentences: one stating the purpose and another describing the return value. It's front-loaded with the core functionality and wastes no words, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of credential management and the lack of annotations and output schema, the description is incomplete. It doesn't explain authentication requirements, error conditions, or the format of returned data (e.g., structure of the list), leaving significant gaps for an agent to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('active Google Cloud credentials'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_service_accounts' or 'config_list', which might also list credential-related information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication status) or compare it to siblings like 'auth_login' or 'auth_revoke', leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool returns 'current configuration settings', but lacks details on what specific settings are included, format of the output, whether it's a read-only operation, or any permissions required. This leaves significant gaps for an agent to understand the tool's 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 and well-structured, with just two sentences that directly state the purpose and return value. Every word earns its place, and it is front-loaded with the core functionality, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of configuration tools and the lack of annotations and output schema, the description is insufficient. It vaguely mentions 'current configuration settings' without specifying scope, format, or examples, leaving the agent uncertain about what to expect. This is inadequate for a tool that likely returns structured data in a cloud environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, so there is no need for parameter documentation in the description. The description appropriately does not discuss parameters, which is efficient and avoids redundancy, earning a high score for this dimension.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('current Google Cloud configuration'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_gcp_project_details' or 'list_gcp_projects', which might provide overlapping or related configuration information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools that could retrieve configuration-related data (e.g., 'get_gcp_project_details', 'list_gcp_projects'), there is no indication of context, prerequisites, or exclusions to help an agent choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states this is a 'Get' operation, implying read-only behavior, but doesn't disclose authentication requirements, rate limits, error conditions, or what 'detailed information' includes (e.g., structure, fields). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the purpose, followed by structured Args and Returns sections. Every sentence earns its place, though the Returns statement is somewhat vague ('Detailed information'). No wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 required parameters, no annotations, no output schema), the description is minimally adequate. It covers the purpose and parameters but lacks behavioral context (e.g., auth, errors) and output details. Without annotations or output schema, more completeness is needed for a read 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 description explicitly lists all three parameters (project_id, cluster_name, location) with brief explanations, adding meaning beyond the schema which has 0% description coverage. It clarifies what each parameter represents, though it doesn't provide format details (e.g., location syntax). With 0% schema coverage, this compensates well but not fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about a specific GKE cluster.' It specifies the verb ('Get') and resource ('GKE cluster'), though it doesn't explicitly differentiate from sibling tools like 'list_gke_clusters' or 'get_instance_details' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_gke_clusters' for listing clusters or 'get_instance_details' for other resource types, nor does it specify prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get details' implies a read-only operation, the description doesn't specify authentication requirements, rate limits, error conditions, or what format the returned details will be in. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It uses a clear three-part format (purpose, args, returns) with no redundant information. Every sentence serves a distinct purpose, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description provides a basic but incomplete picture. It covers the purpose and parameters adequately but lacks behavioral context, usage guidance relative to siblings, and details about the return format. For a read operation with no output schema, more information about what 'Details' includes would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description compensates by listing both parameters with brief explanations ('The ID of the GCP project', 'The name of the deployment to get details for'), which adds meaningful context beyond the bare schema. However, it doesn't provide format examples, constraints, or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get details') and resource ('Deployment Manager deployment'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'list_deployment_manager_deployments', which might cause confusion about when to use one versus the other.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling 'list_deployment_manager_deployments' tool or clarify that this is for retrieving details of a specific deployment rather than listing multiple deployments. No context or exclusions 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, so the description carries the full burden. It states this is a 'get' operation, implying read-only behavior, but doesn't disclose other traits like authentication requirements, rate limits, error conditions, or what 'detailed information' includes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with the core purpose, then lists parameters with helpful examples, and ends with return information. Every sentence adds value, with no redundant or vague phrasing. Minor improvements could include briefer parameter explanations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description partially compensates by explaining parameters and stating the return is 'detailed information.' However, it lacks specifics on what that information includes (e.g., permissions list, role metadata) and behavioral aspects like error handling. For a 2-parameter tool with zero structured coverage, this is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It clearly explains both parameters: 'role_name' (with examples like 'roles/compute.admin') and 'project_id' (optional, for custom roles, not needed if fully qualified). This adds meaningful context beyond the bare schema, though it could specify format constraints more explicitly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about an IAM role, including its permissions.' It specifies the verb ('get') and resource ('IAM role'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_roles' or 'check_iam_permissions', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_roles' (which might list roles without details) or 'check_iam_permissions' (which might verify permissions), leaving the agent to infer usage context. The parameter notes offer some operational hints but not comparative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists disks and returns a list, but lacks critical details: it doesn't mention pagination, rate limits, authentication requirements, error handling, or whether the operation is read-only (though implied by 'List'). For a tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized: it starts with a clear purpose statement, followed by parameter and return value sections. Each sentence adds value without redundancy. Minor improvements could include briefer formatting or more front-loaded key information, but it's efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 parameters, no nested objects) but lack of annotations and output schema, the description is minimally adequate. It covers the basic purpose and parameters but misses behavioral details like pagination or error handling. Without an output schema, it should ideally describe the return format more thoroughly, but the current level is acceptable 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 description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'project_id' is for listing disks in a GCP project and 'zone' is an optional filter (e.g., 'us-central1-a'), clarifying their roles and providing an example. However, it doesn't detail format constraints or validation rules, slightly limiting the value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List Compute Engine persistent disks in a GCP project.' It specifies the verb ('List'), resource ('Compute Engine persistent disks'), and scope ('in a GCP project'). However, it doesn't explicitly differentiate from sibling tools like 'list_compute_instances' or 'list_snapshots' that operate on related resources, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_compute_instances' or 'list_snapshots' that might be relevant for related tasks, nor does it specify prerequisites, exclusions, or contextual usage scenarios. The only implicit guidance is the parameter descriptions, which are insufficient for usage decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return type ('List of project IDs') but lacks critical details: whether it requires specific permissions, how it handles pagination or large result sets, if there are rate limits, or what happens on authentication failure. For a read operation with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences: one stating the purpose and one specifying the return value. It's front-loaded with the core functionality. There's no wasted text, though it could be slightly more structured (e.g., bullet points for returns).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is moderately complete. It covers the basic purpose and return type, but lacks behavioral context (e.g., permissions, pagination) that would be helpful for an agent. Without annotations or output schema, the description should do more to explain how the tool behaves in practice.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline of 4 is appropriate. It correctly implies no inputs are required, aligning with the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('GCP projects'), specifying 'all available' and 'for the authenticated user'. It distinguishes from siblings like 'get_gcp_project_details' (which gets details of a specific project) by focusing on listing all projects. However, it doesn't explicitly differentiate from other list tools (e.g., 'list_assets'), though the resource specificity helps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication status), compare to similar tools like 'list_assets' or 'get_gcp_project_details', or specify use cases (e.g., project selection for operations). The agent must infer usage from the name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the action but doesn't disclose behavioral traits such as required permissions, rate limits, pagination, or error handling. For a read operation in GCP with no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose, followed by structured Args and Returns sections. Every sentence earns its place, though the formatting could be slightly more streamlined.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low complexity, the description is minimally adequate but incomplete. It covers the basic purpose and parameter semantics but lacks behavioral details and usage guidelines, which are needed for a tool in a complex environment like GCP.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the input schema by explaining that 'project_id' is for 'the ID of the GCP project to list services for'. With 0% schema description coverage and only 1 parameter, this adequately compensates, providing clear semantics for the single required input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('enabled services/APIs in a GCP project'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_gcp_projects' or 'list_assets', which reduces clarity in a crowded namespace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'list_gcp_projects', 'list_assets'), the description lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('List') and return type ('List of GKE clusters'), but lacks critical details: permissions required, pagination behavior, rate limits, error conditions, or whether it's a read-only operation. For a cloud resource listing tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It front-loads the core purpose in the first sentence, followed by organized Args and Returns sections. Every sentence earns its place: the purpose statement is essential, parameter descriptions are necessary given 0% schema coverage, and the return statement clarifies output. No wasted words 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?
Given 2 parameters with 0% schema coverage and no output schema, the description does a decent job covering basics: purpose and parameter semantics. However, as a cloud resource tool with no annotations, it lacks behavioral context (e.g., auth needs, side effects) and output details (structure of returned clusters). For a simple list operation, this is minimally adequate but leaves the agent to assume safe defaults.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description compensates by documenting both parameters in the Args section: 'project_id: The ID of the GCP project to list GKE clusters for' and 'region: Optional region to filter clusters (e.g., "us-central1")'. This adds clear meaning beyond the bare schema, explaining purpose and providing an example for region. However, it doesn't cover format constraints or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List Google Kubernetes Engine (GKE) clusters in a GCP project.' This includes a specific verb ('List'), resource ('GKE clusters'), and scope ('in a GCP project'). It distinguishes from siblings like 'list_compute_instances' or 'list_storage_buckets' by specifying the resource type, though it doesn't explicitly differentiate from similar list tools beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), compare to siblings like 'get_cluster_details' for detailed info, or specify scenarios where filtering by region is beneficial. The agent must infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't mention important behavioral aspects like pagination behavior, rate limits, authentication requirements, error conditions, or whether this is a read-only operation. The description is functionally correct but lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by Args and Returns sections. It's appropriately sized for a 4-parameter tool with no wasted words. The formatting with clear section headers makes it easy to parse, though the triple quotes in the provided text suggest potential formatting issues in the original.
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 list operation with 4 parameters and no annotations or output schema, the description provides adequate but minimal coverage. It explains what the tool does and documents parameters, but lacks behavioral context (pagination, errors, auth) and doesn't describe the return format beyond 'List of objects'. Given the complexity and lack of structured metadata, it meets minimum viable standards.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides meaningful parameter documentation that compensates well. It explains all 4 parameters with clear semantics: project_id as 'GCP project', bucket_name as 'bucket to list objects from', prefix as 'filter objects by', and limit with its default value. This adds substantial value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List objects') and resource ('in a Cloud Storage bucket'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'list_storage_buckets' or 'list_assets', but the resource specificity (objects within a bucket) provides implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'list_storage_buckets' (lists buckets themselves) and 'list_assets' (potentially broader resource listing), there's no indication of when this specific object-listing tool is appropriate versus other listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action 'List' but does not mention whether this is a read-only operation, if it requires specific permissions, rate limits, or what the return format entails (e.g., pagination, structure). This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by structured Args and Returns sections. It avoids unnecessary verbosity, though the formatting with blank lines could be slightly tighter. Every sentence adds value without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description covers the basic purpose and parameter semantics adequately. However, it lacks details on behavioral aspects like permissions or return format, which are important for a list operation in a cloud environment, making it minimally viable but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'project_id' by specifying it as 'The ID of the GCP project', which clarifies its purpose beyond the schema's minimal title 'Project Id'. With 0% schema description coverage and only one parameter, this compensation is adequate, though not exhaustive (e.g., no format examples).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'service accounts in a GCP project', making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'list_roles' or 'list_assets', which list different resources, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'list_roles' for roles or 'list_assets' for broader asset listings. It lacks context on prerequisites or exclusions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It mentions the action and return type but doesn't disclose permissions needed, rate limits, pagination, error handling, or whether it's read-only (implied but not stated). For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose in the first sentence. The Args and Returns sections are clear and efficient, with no redundant information. Every sentence adds value without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema coverage, the description is minimally adequate. It covers the basic action and parameter but lacks details on behavior, output format, error cases, and integration context. For a simple list tool, it's passable but leaves gaps an agent might need.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds the parameter 'project_id' with a brief explanation ('The ID of the GCP project to list buckets for'). This clarifies the parameter's purpose beyond the schema's title 'Project Id'. However, it doesn't provide format details, constraints, or examples, so it only partially compensates for the low 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 verb ('List') and resource ('Cloud Storage buckets in a GCP project'), making the purpose unambiguous. It distinguishes from siblings like 'list_objects' or 'list_gcp_projects' by specifying storage buckets. However, it doesn't explicitly differentiate from all list tools, so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), compare to other listing tools (like 'list_assets' or 'list_gcp_projects'), or specify use cases. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't mention authentication requirements, rate limits, pagination, error handling, or what 'List of Uptime checks' entails (e.g., format, fields). For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections are structured clearly, though the formatting with extra whitespace slightly reduces efficiency. Every sentence adds value, with no 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?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks behavioral details (e.g., authentication, output format) and usage guidelines. Without annotations or output schema, more context would improve completeness for agent 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?
The description adds meaningful context for the single parameter 'project_id' by explaining it's 'The ID of the GCP project to list Uptime checks for', which clarifies its role beyond the schema's basic title. With 0% schema description coverage and only one parameter, this adequately compensates, though it doesn't detail format constraints (e.g., GCP project ID patterns).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Uptime checks in a GCP project'), making the purpose specific and understandable. However, it doesn't distinguish this tool from other list_* siblings (like list_cloud_sql_instances or list_compute_instances) beyond the resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), compare it to other monitoring tools (like get_monitoring_alerts), or specify scenarios where it's appropriate versus other list operations. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a mutation operation ('Set'), but doesn't mention whether this affects global state, requires specific permissions, has side effects, or provides error handling. The description lacks critical behavioral context needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args/Returns sections. Every sentence serves a purpose with zero waste, making it easy to parse while maintaining completeness for its current 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 mutation tool with no annotations and no output schema, the description provides basic purpose and parameter explanation but lacks critical context about behavioral traits, error conditions, and relationship to sibling tools. It's minimally adequate but leaves significant gaps in understanding how and when to use this tool safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only one parameter and 0% schema description coverage, the description compensates well by explaining what 'project_id' represents ('The ID of the project to set as default'). This adds meaningful context beyond the bare schema, though it doesn't specify format constraints or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Set') and resource ('default Google Cloud project'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'set_quota_project' or 'config_list', which reduces clarity about when to choose this specific configuration tool over alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'config_list' or 'set_quota_project'. It mentions neither prerequisites (e.g., authentication state) nor exclusions, leaving the agent with insufficient context for proper tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions pagination ('page_size') and filtering ('asset_types'), which adds some behavioral context, but lacks critical details like authentication requirements, rate limits, error handling, or whether it's read-only (implied by 'List' but not explicit). This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by clear parameter explanations in a standard 'Args'/'Returns' format. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 covers parameters well but lacks behavioral context (e.g., auth, errors) and output details (e.g., asset structure). It's minimally adequate for a listing tool but leaves gaps that could hinder agent usage in complex scenarios.
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 effectively explains all three parameters: 'project_id' (GCP project ID), 'asset_types' (optional filter with example), and 'page_size' (default and max values). This adds significant meaning beyond the bare schema, though it could provide more detail on asset type formats or pagination behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List assets') and resource ('in a GCP project using Cloud Asset Inventory API'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_compute_instances' or 'list_gcp_projects', which also list resources but with different scopes or APIs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools that list specific resources (e.g., 'list_compute_instances', 'list_storage_buckets'), there's no indication that this tool is for broader asset inventory across multiple resource types, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists collections but doesn't mention whether this is a read-only operation, if it requires specific permissions, potential rate limits, pagination behavior, or error conditions. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with a clear purpose statement, followed by organized sections for Args and Returns. Each sentence adds value without redundancy, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral details, usage context, and output specifics. For a simple listing tool, this is borderline acceptable but leaves gaps in 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 description adds meaningful context for both parameters: it explains that 'project_id' is 'The ID of the GCP project' and 'database_id' is 'The ID of the Firestore database (default is "(default)")'. Since schema description coverage is 0%, this compensates well by providing semantic meaning beyond the bare schema, though it doesn't cover all potential nuances like format 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 tool's purpose: 'List collections in a Firestore database.' It specifies the verb ('List') and resource ('collections in a Firestore database'), making the action and target explicit. However, it doesn't differentiate from sibling tools like 'list_firestore_databases' or 'list_databases', which reduces clarity about when to choose this specific listing tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_firestore_databases' or 'list_databases', nor does it specify prerequisites, exclusions, or appropriate contexts. This leaves the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists machine types, which implies a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or provides error handling. For a tool with zero annotation coverage, this leaves significant behavioral gaps, though it at least clarifies the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the purpose stated clearly in the first sentence. The Args and Returns sections are structured efficiently, using minimal words to convey necessary information without redundancy. Every sentence earns its place, making it highly concise and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the purpose and parameters adequately, but lacks behavioral details like authentication needs or error handling. Without annotations or an output schema, it should provide more context on what the return value entails (e.g., format, fields), leaving 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 description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'project_id' is 'The ID of the GCP project' and 'zone' is 'The zone to check machine types in (e.g., "us-central1-a")', including an example for the zone parameter. This compensates well for the schema's lack of descriptions, though it doesn't detail constraints or formats beyond the example.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List available machine types in a specific zone.' It specifies the verb ('List'), resource ('machine types'), and scope ('in a specific zone'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like 'list_compute_instances' or 'list_disks', which also list resources in zones, so it doesn't reach the highest level of sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or compare it to sibling tools such as 'list_compute_instances' or 'list_disks', which might be relevant in similar contexts. Usage is implied by the purpose statement alone, but no explicit guidelines 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the return type ('List of node pools') but doesn't describe pagination behavior, rate limits, authentication requirements, error conditions, or what happens if the cluster doesn't exist. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by parameter and return value sections. Every sentence serves a distinct purpose with zero wasted words, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only list operation with 3 parameters and no output schema, the description covers the basic purpose and parameters adequately. However, it lacks information about return format details, error handling, and behavioral constraints that would be helpful given the complete 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 description explicitly lists all three parameters with brief explanations, adding meaningful context beyond the 0% schema description coverage. While it doesn't provide format details or examples, it clearly maps each parameter to its purpose in the operation, compensating well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('node pools in a GKE cluster'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'list_gke_clusters', but the specificity of 'node pools' versus 'clusters' provides implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_gke_clusters' or 'get_cluster_details', nor does it mention prerequisites or contextual constraints. It simply states what the tool does without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it's a listing operation, which implies read-only behavior, but doesn't mention authentication requirements, rate limits, pagination behavior, or what format the returned list takes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence serves a purpose with no wasted words, and the information is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one parameter and no output schema, the description covers the basic purpose and parameter meaning adequately. However, without annotations and with no output schema, it should ideally describe the return format more specifically than just 'List of disk snapshots' to be 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?
With only one parameter and 0% schema description coverage, the description compensates well by explaining what 'project_id' represents ('The ID of the GCP project to list snapshots for'). This adds meaningful context beyond the schema's basic string type, though it doesn't specify format requirements (like project ID patterns).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('disk snapshots in a GCP project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_disks' or 'list_compute_instances' that also list GCP resources, so it doesn't reach the highest clarity level.
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. There's no mention of when this tool is appropriate compared to other listing tools (like 'list_disks' or 'list_assets'), nor any prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Upload a file' implies a write operation, the description doesn't mention authentication requirements, permissions needed, whether the operation overwrites existing files, rate limits, error conditions, or what the 'Result of the upload operation' actually contains. This leaves significant behavioral gaps 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 perfectly structured and concise. It starts with a clear purpose statement, then provides a well-organized Args section with bullet-like formatting, and ends with a Returns statement. Every sentence earns its place, and the information is front-loaded with the most important details first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description has significant gaps. While parameter documentation is excellent, the description lacks crucial context about authentication requirements, error handling, what the return value actually contains, and behavioral constraints. For a tool that modifies cloud storage, this leaves the agent with incomplete operational understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides excellent parameter documentation with clear explanations for all 5 parameters, including defaults for destination_blob_name and content_type. Since schema description coverage is 0%, the description fully compensates by explaining what each parameter means and how it's used, going well beyond the bare schema field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Upload a file to a Cloud Storage bucket' which is a specific verb+resource combination. It distinguishes itself from sibling tools like 'download_object' and 'delete_object' by specifying the upload direction. However, it doesn't explicitly differentiate from other potential file manipulation tools beyond the obvious upload/download distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like authentication), when this tool is appropriate versus other storage operations, or any exclusions. The agent must infer usage from the purpose statement alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool creates a new alert policy but doesn't disclose behavioral traits like required authentication, rate limits, whether the operation is idempotent, error conditions, or what happens to existing policies. The return statement is vague ('Result of the alert policy creation').
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 a clear purpose statement followed by parameter details. It's appropriately sized for an 8-parameter tool, though the return statement is vague and could be more informative. Every sentence adds value, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral context (e.g., permissions, side effects), detailed usage guidelines, and a clear output specification. For a creation tool in a cloud environment, this leaves significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by explaining all 8 parameters in the Args section, including examples (e.g., metric type), defaults, and optionality. It adds meaning beyond the bare schema, though some details like format constraints for 'project_id' or 'filter_str' could be more specific.
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 new alert policy') and resource ('in a GCP project'), distinguishing it from sibling tools like 'get_monitoring_alerts' (which retrieves alerts) or 'list_monitoring_metrics' (which lists metrics). The verb 'create' is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites (e.g., required permissions), or exclusions. It lacks context about when alert policies are appropriate compared to other monitoring or notification tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation, implying mutation, but doesn't mention required permissions, whether it's idempotent, potential side effects (e.g., network security changes), rate limits, or what happens on failure. The return statement is vague ('Result of the firewall rule creation'). For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses bullet-like formatting for parameters. Every sentence earns its place by providing essential information. It could be slightly more concise by avoiding the boilerplate 'Args:' and 'Returns:' labels, but overall it's efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, mutation operation, no annotations, no output schema), the description is partially complete. It excels at parameter documentation but lacks crucial behavioral context like permissions, side effects, error handling, and return value details. The parameter coverage is excellent, but other aspects are underdeveloped for a tool of this complexity.
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 provides excellent parameter semantics beyond the schema. With 0% schema description coverage, the description compensates fully by explaining all 12 parameters, including optional/required status, data types, examples (e.g., for allowed_protocols), and conditional relationships (e.g., source_ranges for INGRESS, destination_ranges for EGRESS). This adds substantial value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a firewall rule') and resource ('in a GCP project'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'list_firewall_rules' or mention any unique aspects of this creation operation beyond the basic verb+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. There's no mention of prerequisites (e.g., network must exist), when not to use it, or how it relates to sibling tools like 'list_firewall_rules' or other GCP management tools. The description only states what it does, not when to use 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 fully disclose behavioral traits. It states this is a creation tool, implying mutation, but lacks critical details: required permissions (e.g., IAM roles), whether the operation is idempotent, potential side effects (e.g., billing implications), or error handling. The description adds minimal behavioral context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by parameter and return sections. It uses bullet-like formatting for readability. However, the 'Returns' section is vague ('Result of the service account creation'), and some sentences could be more direct (e.g., merging the purpose with parameter context).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a mutation tool in GCP with no annotations and no output schema), the description is incomplete. It lacks behavioral transparency (e.g., permissions, side effects), usage guidelines, and details on return values. While parameter semantics are covered, the overall context for safe and effective use is insufficient.
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 meaningful semantics for all four parameters: 'project_id' specifies the GCP project, 'account_id' includes a length constraint (6-30 characters), 'display_name' clarifies it's user-friendly, and 'description' notes it's optional. This adds significant value beyond the bare schema, though it could detail formats (e.g., project ID pattern).
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 new service account') and resource ('in a GCP project'), using a precise verb. It distinguishes this tool from sibling tools like 'list_service_accounts' or 'get_gcp_project_details' by focusing on creation rather than listing or retrieval.
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., authentication, project permissions), when not to use it, or how it relates to sibling tools like 'list_service_accounts' for verification. Usage is implied only by the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'resize' implies a mutation, it doesn't address critical aspects like required permissions, whether the operation is reversible, potential downtime, rate limits, or error conditions. This leaves significant gaps for safe agent usage.
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 a clear purpose statement followed by parameter documentation. It's appropriately sized and front-loaded, though the Returns section is somewhat vague ('Result of the node pool resize operation') and could be more specific.
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 mutation tool with 5 parameters, no annotations, and no output schema, the description provides good parameter documentation but lacks behavioral context. It's minimally adequate but has clear gaps in usage guidance and operational transparency that would help an agent use it 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?
The description provides clear, meaningful documentation for all 5 parameters in the Args section, explaining what each parameter represents. This is excellent compensation for the 0% schema description coverage, adding substantial value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('resize') and resource ('node pool in a GKE cluster'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from potential siblings like 'list_node_pools' or 'create_instance', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or constraints. It lacks any mention of when-not-to-use scenarios or how it relates to sibling tools like 'list_node_pools' or 'get_cluster_details' for verification.
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. While it states the action ('Start') and mentions a return value, it doesn't disclose critical behavioral traits like required permissions, whether this is a mutating operation, potential costs, time to complete, error conditions, or side effects. The description is minimal beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses minimal but effective language. Every sentence serves a purpose, though the 'Returns' section could be slightly more specific about what 'Status message' entails.
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 mutating tool with no annotations and no output schema, the description is insufficient. It doesn't address permissions, costs, side effects, error handling, or what constitutes 'successfully' started. The agent would need to guess about important behavioral aspects of this infrastructure management 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?
With 0% schema description coverage, the description fully compensates by clearly documenting all 3 parameters with meaningful explanations. Each parameter gets a brief but helpful description that adds semantic context beyond what the bare schema provides, including an example for the zone parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Start') and resource ('Compute Engine instance'), distinguishing it from siblings like 'stop_instance' and 'create_instance'. It provides a complete verb+resource combination that leaves no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'stop_instance' or 'create_instance'. While the purpose is clear, there's no explicit mention of prerequisites, dependencies, or when-not-to-use scenarios that would help an agent select between sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a deletion operation (implying destructive mutation) but doesn't mention critical behaviors: whether deletion is permanent/irreversible, if it requires specific IAM permissions, what happens to attached resources (disks, IPs), or typical execution time. The return value description is vague ('status message').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured with clear sections (purpose, args, returns). Every sentence adds value, though the return statement could be more specific. The formatting with bullet-like sections enhances readability without unnecessary verbosity.
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 destructive mutation tool with no annotations and no output schema, the description is incomplete. It lacks critical context: irreversible nature, permission requirements, side effects on attached resources, error conditions, and detailed return format. The sibling tool list shows many instance-related tools, but no comparison is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It provides clear semantic explanations for all three parameters: 'project_id' identifies the GCP project, 'zone' specifies location with an example, and 'instance_name' identifies the target instance. This adds essential meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Delete') and resource ('a Compute Engine instance'), making the purpose unambiguous. It distinguishes this destructive operation from sibling tools like 'create_instance', 'start_instance', and 'stop_instance' that manipulate instances differently.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., instance must be stopped), irreversible consequences, or compare with similar tools like 'delete_object' for storage or 'create_snapshot' for backup before deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves information, implying a read-only operation, but does not disclose behavioral traits such as authentication requirements, rate limits, error handling, or what 'detailed information' includes. The description is minimal and lacks context beyond the basic 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 appropriately sized and front-loaded, with the purpose stated first, followed by parameter explanations and return information. Every sentence adds value, though the return statement is vague. It avoids redundancy and is structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, no output schema), the description is adequate but has gaps. It covers the purpose and parameters well but lacks details on behavior, authentication, and output format. For a read operation, this is minimally viable, but more context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining each parameter: 'project_id' as 'The ID of the GCP project', 'zone' with an example ('e.g., "us-central1-a"'), and 'instance_name' as 'The name of the instance to get details for'. This clarifies semantics beyond the schema's titles, though it could provide more detail on format constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about a specific Compute Engine instance.' It specifies the verb ('Get'), resource ('Compute Engine instance'), and scope ('detailed information'), distinguishing it from sibling tools like 'list_compute_instances' (which lists multiple instances) and 'get_gcp_project_details' (which focuses on projects).
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 sibling tools like 'list_compute_instances' for listing instances or 'get_sql_instance_details' for SQL instances, nor does it specify prerequisites or exclusions. Usage is implied by the purpose but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states basic functionality. It doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though implied by 'list'). For a GCP API tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value: the first states what the tool does, the second explains parameters, and the third describes the return. No wasted words 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 list tool with 2 parameters and no output schema, the description covers basics adequately but lacks important context. Without annotations or output schema, it should ideally mention response format, pagination, or common use cases. It's minimally viable but leaves gaps for agent understanding.
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 provides clear semantic meaning for both parameters: 'project_id' identifies the GCP project, and 'network' optionally filters rules by network name. This compensates well for the schema's lack of descriptions, though it doesn't specify format details like network path structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List firewall rules') and resource ('in a GCP project'), with optional filtering by network. It distinguishes from siblings like 'create_firewall_rule' by focusing on listing rather than creation, but doesn't explicitly differentiate from other list tools like 'list_vpc_networks' or 'list_subnets'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving firewall rules with optional network filtering, but provides no explicit guidance on when to use this versus alternatives like 'list_vpc_networks' or 'get_vpc_details' for network-related queries. It mentions the optional filter but doesn't explain trade-offs or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose critical traits like pagination, rate limits, authentication needs, or error handling. For a tool with no annotations, this leaves significant behavioral gaps, though it minimally indicates the action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose, followed by structured Args and Returns sections. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema coverage, the description is minimally complete. It covers the purpose and parameter semantics adequately but lacks behavioral details (e.g., return format, error cases) and usage context. For a simple list tool, it's functional but could be more informative.
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 adds clear semantics for the single parameter (project_id), explaining its optional nature and effect on output (custom vs. predefined roles). This fully documents the parameter beyond the schema, though it doesn't cover format or validation details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('IAM roles'), specifying both predefined and custom roles. It distinguishes the tool's purpose from many siblings that list other resources (e.g., list_objects, list_service_accounts), though not from all list_* tools generically. The purpose is specific but could be more distinctive among list operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the parameter explanation: use project_id for custom roles, omit for predefined roles. However, it lacks explicit guidance on when to choose this tool over alternatives (e.g., vs. get_role_permissions for permissions details) or any prerequisites. Usage is contextually implied but not clearly 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?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Create' implies a write/mutation operation, it doesn't mention critical behaviors: required permissions (IAM roles), cost implications, rate limits, whether the operation is idempotent, or what happens on failure. The return statement is vague ('Status message') without specifying format or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by organized Args/Returns sections. Every sentence serves a purpose, though the return statement could be more specific. The formatting with bullet-like parameter explanations is efficient and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex 9-parameter creation tool with no annotations and no output schema, the description provides good parameter semantics but lacks critical behavioral context. It covers what parameters mean but not how the tool behaves operationally (permissions, costs, errors). The return description is minimal ('Status message'), leaving output format ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by providing clear semantic explanations for all 9 parameters. Each parameter includes purpose clarification (e.g., 'zone to create the instance in'), format examples (e.g., 'us-central1-a'), and default values where applicable. This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Create a new Compute Engine instance') with the exact resource, distinguishing it from sibling tools like 'delete_instance', 'start_instance', and 'stop_instance'. It uses precise technical terminology that matches the GCP context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication, project setup), nor does it differentiate from related tools like 'create_snapshot' or 'create_backup'. The agent must infer usage context solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the tool creates a snapshot and returns a status message, but lacks details on permissions required, whether the disk must be stopped, potential costs, rate limits, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses bullet-like formatting. It's appropriately sized, though the 'Returns' section could be more specific about the status message format. Every sentence adds value 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?
For a mutation tool with 5 parameters, no annotations, and no output schema, the description is adequate but incomplete. It covers parameters well and states the basic action, but lacks critical context like behavioral constraints, error handling, or detailed output expectations, leaving gaps for safe agent operation.
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 adds significant value beyond the schema's 0% coverage. It explains each parameter's purpose (e.g., 'zone: The zone where the disk is located'), clarifies optionality ('description: Optional description'), and provides an example ('e.g., "us-central1-a"'), fully compensating for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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') and resource ('Compute Engine disk'), distinguishing it from sibling tools like 'list_snapshots' or 'create_backup'. It precisely defines the tool's function without being tautological.
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. While it's clear this creates snapshots, there's no mention of prerequisites (e.g., disk must be stopped), limitations, or comparison to similar tools like 'create_backup' for other resources.
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. While it indicates this is a read operation ('List'), it doesn't mention important behavioral aspects like authentication requirements, rate limits, pagination behavior, error conditions, or what format the returned subnet data will have. The description is minimal beyond stating the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured with a clear purpose statement followed by well-organized Arg/Return sections. Every sentence earns its place with zero wasted words, and the information is front-loaded with the most important details first.
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 with 2 parameters and no output schema, the description covers the basic purpose and parameters adequately. However, without annotations and with no output schema, it should ideally provide more behavioral context about what the returned subnet data includes, authentication requirements, or error handling to be 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?
With 0% schema description coverage, the description compensates well by clearly explaining both parameters: 'project_id' as 'The ID of the GCP project' and 'region' as 'Optional region to filter subnets by'. This adds meaningful semantic context beyond the bare schema, though it doesn't provide format examples or constraints for either parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('List subnets'), target resource ('in a GCP project'), and optional scope ('optionally filtered by region'). It distinguishes itself from sibling tools like list_vpc_networks or list_compute_instances by focusing specifically on subnets.
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 about when to use the tool ('list subnets in a GCP project') and mentions the optional filtering capability. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools for different subnet-related 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 provided, the description carries full burden but only states the basic action. It doesn't disclose critical behavioral traits like required permissions, whether this is a destructive operation, rate limits, or what happens to attached resources. For a mutation tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Perfectly structured with a clear purpose statement followed by well-organized Args and Returns sections. Every sentence earns its place with zero waste, and information is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description covers parameters well but lacks critical behavioral context about permissions, side effects, and return format. The description is complete for basic usage but inadequate for safe operation in production contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by clearly documenting all 3 parameters with meaningful explanations. Each parameter's purpose is explicitly stated, adding significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Stop') and resource ('Compute Engine instance'), distinguishing it from siblings like 'start_instance' and 'delete_instance'. The verb+resource combination is precise 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (stopping a running instance) but doesn't explicitly state when to use this vs. alternatives like 'delete_instance' or 'start_instance'. It provides clear context but lacks explicit exclusions or sibling comparisons.
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 full burden. It discloses the authentication method ('browser-based OAuth flow') and mentions the optional project_id parameter, but doesn't describe important behavioral aspects like whether this initiates a new browser window, what happens if already authenticated, error conditions, or timeout behavior. It provides basic context but lacks operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place, providing essential information without redundancy. The formatting with clear sections makes it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an authentication tool with no annotations and no output schema, the description provides adequate basics but lacks depth. It explains what the tool does and the parameter, but doesn't cover important authentication-specific context like required browser interaction, session management, error handling, or what 'successful' authentication actually means in practical terms.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only 1 parameter, the description adds significant value by explaining the project_id parameter's purpose ('Optional project ID to set as default after login'). This goes beyond the schema's minimal documentation, though it doesn't specify format constraints or provide 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 specific action ('Authenticate with Google Cloud Platform') and method ('using browser-based OAuth flow'), distinguishing it from sibling tools like auth_list or auth_revoke. It provides a complete verb+resource+method combination that leaves no ambiguity about what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is the primary authentication entry point ('Authenticate with Google Cloud Platform'), suggesting it should be used to establish initial credentials. However, it doesn't explicitly state when NOT to use it (e.g., after already authenticated) or mention alternatives like auth_list for checking current authentication status.
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. It implies a write/mutation operation ('Set'), mentions authentication context, and describes success/error outcomes. However, it lacks details about permissions required, whether changes are persistent, side effects, or rate limits. The behavioral disclosure is adequate but not comprehensive 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 front-loaded: purpose statement first, followed by usage context, then parameter and return details. Every sentence earns its place with no redundancy. The four-sentence format efficiently covers all necessary aspects without waste.
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 single-parameter mutation tool with no annotations and no output schema, the description provides good coverage: clear purpose, usage context, parameter explanation, and return value description. It could be more complete by mentioning authentication prerequisites or persistence of changes, but it addresses the core needs adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It provides a clear 'Args' section explaining 'project_id' as 'The ID of the GCP project to use for quota attribution,' which adds essential semantic meaning beyond the schema's basic type information. This fully addresses the single parameter's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Set a quota project for Google Cloud API requests.' It specifies the verb ('Set') and resource ('quota project'), and distinguishes it from siblings by addressing a specific authentication warning scenario. However, it doesn't explicitly differentiate from similar configuration tools like 'config_set_project'.
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: to resolve the specific warning about 'end user credentials from Google Cloud SDK without a quota project.' This gives practical guidance. However, it doesn't mention when NOT to use it or explicitly compare it to alternatives like 'config_set_project' for general project configuration.
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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