terraform-cloud-mcp

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific resources and actions, with clear boundaries like create/update/get/list for each resource type. However, some overlap exists in variable management between workspace and variable set contexts, and multiple run action tools (cancel, force_cancel, discard) could be confusing without careful reading of descriptions.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, with clear conventions like create_*, get_*, list_*, update_*, assign_*, and unassign_*. All names use snake_case consistently, making the tool set predictable and easy to navigate despite the large count.
Tool Count2/5
With 62 tools, this is an extremely large surface that feels heavy and overwhelming for the Terraform Cloud domain. While the API is comprehensive, this many tools will likely cause confusion and selection paralysis for agents, exceeding typical well-scoped MCP servers (3-15 tools).
Completeness5/5
The tool set provides complete CRUD/lifecycle coverage for all major Terraform Cloud resources (organizations, workspaces, projects, runs, variables, state versions, etc.). There are no obvious gaps—every resource has create, read, update, and delete/list operations where applicable, plus specialized actions like run management and workspace locking.
Average 4.1/5 across 62 of 62 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 2 community issues answered or closed 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
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
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If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a retrieval operation ('Get/Retrieves'), which implies read-only behavior, but doesn't explicitly confirm this or mention any side effects, authentication requirements, rate limits, or error conditions. The mention of an API endpoint ('GET /organizations/{organization}') hints at HTTP semantics but doesn't elaborate on behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It front-loads the purpose, provides additional context in the second sentence, and includes structured sections for Args and Returns. The 'See' reference is useful but could be considered slightly extraneous. Overall, most sentences earn their place without unnecessary verbosity.
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 (single parameter, no output schema, no annotations), the description is moderately complete. It covers the purpose, parameter, and return scope adequately. However, for a tool with no annotations, it lacks details on behavioral aspects like error handling, authentication, or rate limits, which would improve completeness for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, but the description compensates by documenting the single parameter: 'organization: The organization name to retrieve details for (required).' This adds meaning beyond the schema's basic type definition. However, it doesn't provide format details (e.g., string constraints, examples) or explain what constitutes a valid organization name, 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: 'Get details for a specific organization' and 'Retrieves comprehensive information about an organization including settings, email contact info, and configuration defaults.' This specifies the verb ('Get/Retrieves'), resource ('organization'), and scope of information returned. However, it doesn't explicitly differentiate from sibling tools like 'get_account_details' or 'get_project_details' 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. While it mentions retrieving details for 'a specific organization,' it doesn't clarify when to use this versus 'list_organizations' or 'get_organization_entitlements.' There's no mention of prerequisites, context, 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. It mentions retrieving 'comprehensive information' and lists some attributes (configuration, tag bindings, workspace count), but does not disclose critical behaviors such as authentication requirements, rate limits, error handling, or whether it's a read-only operation. The API endpoint hint ('GET') implies read-only, but this is not explicitly stated in the description text.
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, details, API endpoint, Args, Returns, See), and sentences are front-loaded with key information. It is appropriately sized for a simple retrieval tool, though the 'See' reference could be considered extraneous if not essential for agent use.
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 (single parameter, no output schema, no annotations), the description is minimally adequate. It covers the purpose and parameter semantics but lacks usage guidelines and full behavioral transparency. Without annotations or output schema, it should ideally provide more context on return values and operational constraints, leaving 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?
The description includes an 'Args' section that documents the single parameter 'project_id' with format details ('prj-xxxxxxxx'), adding value beyond the input schema which has 0% description coverage and only provides a title. However, it does not explain the semantics of the parameter further, such as where to obtain the ID or validation rules. With one parameter and low schema coverage, this partial compensation justifies a baseline score.
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 details for a specific project' and 'Retrieves comprehensive information about a project'. It specifies the verb ('Get', 'Retrieves') and resource ('project'), but does not explicitly differentiate it from sibling tools like 'get_organization_details' or 'get_workspace_details' beyond the resource name, which is implied but not stated.
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_projects' for listing projects or 'update_project' for modifying them, nor does it specify prerequisites or contexts for usage. The 'See' reference to external documentation is not a substitute for inline 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. It states the tool retrieves variables 'including their configuration and values', which hints at read-only behavior, but doesn't explicitly confirm it's non-destructive or safe. It also lacks details on rate limits, authentication needs, pagination, or error handling. The API endpoint mention adds some context but isn't sufficient behavioral disclosure for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by elaboration. The 'Args' and 'Returns' sections are structured but slightly verbose. The 'See' reference is helpful but could be integrated more seamlessly. Overall, it's efficient with minimal 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 (1 parameter, no output schema, no annotations), the description is moderately complete. It covers the basic purpose, parameter semantics, and return type ('List of variables in the variable set with their configuration'). However, it lacks usage guidelines, full behavioral transparency, and details on output structure (e.g., what fields 'configuration' includes), leaving gaps for an agent to use it effectively without external docs.
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 meaningful context for the single parameter: it explains that 'varset_id' is 'The ID of the variable set' and provides the format 'varset-xxxxxxxx'. Since schema description coverage is 0% (the schema only has a title 'Varset Id' with no description), this compensates well. However, it doesn't elaborate on where to obtain this ID or validation rules, keeping it at a baseline 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: 'List all variables in a variable set' and 'Retrieves all variables that belong to a specific variable set'. It uses specific verbs ('list', 'retrieves') and identifies the resource ('variables in a variable set'). However, it doesn't explicitly differentiate from sibling tools like 'list_variable_sets' or 'list_workspace_variables', which would be needed 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 sibling tools like 'get_variable_set' (which might retrieve metadata without variables) or 'list_ariable_sets' (which lists sets rather than variables within them). There's also no context about prerequisites (e.g., needing a valid variable set ID) or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions downloading content and API endpoint usage, but lacks critical behavioral details: authentication requirements, rate limits, error handling, or whether it's a read-only operation. The description is insufficient for a mutation-sensitive 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, API endpoint, args, returns, see). It is front-loaded with the core purpose and avoids redundancy. However, the 'See' reference could be integrated more seamlessly, and some sentences are slightly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, no annotations, and no output schema, the description is moderately complete. It covers parameters and return types but lacks behavioral transparency and usage guidelines. For a download tool in a complex system, more context on permissions, errors, and sibling differentiation would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates well by explaining both parameters: 'state_version_id' as the ID with format 'sv-xxxxxxxx' and 'json_format' as a boolean for JSON formatting with default False. This adds meaningful context beyond the bare schema, though it could detail output implications more.
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 the state file content' and specifies it retrieves raw or JSON formatted state for a specific state version. It uses specific verbs ('download', 'retrieves') and identifies the resource ('state file'), but does not explicitly differentiate from sibling tools like 'get_state_version' or 'get_state_version_output'.
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 the API endpoint but does not indicate scenarios, prerequisites, or comparisons with sibling tools such as 'get_state_version' or 'list_state_versions'. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions retrieving 'comprehensive information' and lists some content types (status, drift detection, links), but doesn't address important aspects like authentication requirements, rate limits, error conditions, or whether this is a read-only operation. The API endpoint format is helpful but insufficient for full 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 well-structured and appropriately sized. It front-loads the core purpose, then provides supporting details about what's retrieved, the API endpoint, parameter format, return content, and documentation reference. Each section serves a clear purpose with minimal 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 single-parameter read operation with no output schema, the description provides adequate but incomplete context. It covers the basic purpose, parameter format, and return content types, but lacks information about authentication, error handling, and how this tool relates to its many siblings. The documentation reference helps, but the description itself should be more self-contained.
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 provides essential semantic context that the schema lacks. It explains that 'assessment_result_id' identifies the specific result to retrieve and provides the expected format ('asmtres-xxxxxxxx'), which is crucial information not present in the schema's minimal title.
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 ('assessment result'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_assessment_json_output' or 'get_assessment_log_output', which appear to retrieve related but different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions related resources like JSON output and logs, but doesn't specify whether those should be retrieved via this tool or the sibling tools dedicated to them. No context about prerequisites or exclusions is 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 full burden for behavioral disclosure. It states this is a retrieval operation ('show', 'retrieves') which implies read-only behavior, but doesn't explicitly confirm it's non-destructive. It mentions the API endpoint but doesn't describe authentication requirements, rate limits, error conditions, or response format details beyond 'Entitlement set details'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, API endpoint, Args, Returns, See). It's appropriately sized for a single-parameter tool, though the 'See' reference could be considered extraneous. Most sentences earn their place by adding value beyond what's in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with 1 parameter and no output schema, the description provides adequate but minimal context. It explains what the tool does and the parameter meaning, but lacks details about the return structure ('Entitlement set details' is vague), authentication, or error handling. Without annotations or output schema, more behavioral context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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: 'organization: The organization name to retrieve entitlements for (required)'. With 0% schema description coverage and only 1 parameter, this adequately compensates by explaining what the parameter represents and that it's required. The schema itself only provides type information without description.
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: 'Show entitlement set for organization features' and 'Retrieves information about available features and capabilities based on the organization's subscription tier.' It specifies the verb ('show', 'retrieves'), resource ('entitlement set'), and scope ('organization features'), but doesn't explicitly differentiate from sibling tools like 'get_organization_details' or 'list_organizations'.
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_organization_details' or clarify whether this is for subscription-specific information versus general organization metadata. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, indicating a mutation operation. The description adds context: it specifies a PATCH endpoint, explains partial updates ('Only specified attributes will be updated; unspecified attributes remain unchanged'), and mentions the return format ('The updated variable set with all current settings and configuration'). However, it lacks details on permissions, rate limits, or error conditions. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with a purpose statement, behavioral note, API endpoint, Args, Returns, and See reference. However, it includes redundant elements like the API endpoint (which may be internal) and a reference link that doesn't add immediate value. The 'Args' section is helpful but could be more integrated. It's front-loaded but has some fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, 0% schema coverage, no output schema, and annotations only covering readOnlyHint, the description does a decent job. It explains parameters and return values, but lacks context on error handling, authentication, or how this fits with sibling tools. For a mutation tool with minimal structured data, it's adequate but has clear gaps in operational guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a detailed 'Args' section explaining 'varset_id' format and listing 'params' sub-parameters (name, description, global, priority) with brief explanations. This adds significant meaning beyond the bare schema, though it doesn't cover all nuances like string length limits or null handling. With 0% coverage, this is strong but 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: 'Update an existing variable set' and 'Modifies the settings of a variable set.' It specifies the verb ('update', 'modifies') and resource ('variable set'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'update_variable_in_variable_set' or 'create_variable_set', 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 mentions 'Only specified attributes will be updated; unspecified attributes remain unchanged,' which is a behavioral detail but not usage guidance. There's no mention of prerequisites, when to choose this over 'create_variable_set' or 'update_variable_in_variable_set', or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions retrieving comprehensive information but doesn't address key aspects like authentication requirements, rate limits, error conditions, or whether this is a read-only operation. The API endpoint hint (GET) suggests read-only behavior, but this isn't explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, API endpoint, Args, Returns, See) and avoids unnecessary verbosity. However, the 'See' reference to external documentation slightly reduces conciseness, as some information could be integrated directly.
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 single-parameter read operation with no output schema, the description provides adequate context about what information is returned (status, timestamps, resource change counts) and parameter format. However, it lacks details about response structure, error handling, and behavioral constraints that would be helpful given the absence of annotations.
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 despite 0% schema description coverage. It clearly explains the plan_id parameter's purpose ('The ID of the plan to retrieve details for') and provides crucial format information ('format: "plan-xxxxxxxx"') that isn't in the schema. This fully compensates 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 tool's purpose with a specific verb ('Get details') and resource ('plan'), and distinguishes it from siblings by focusing on comprehensive plan information retrieval. However, it doesn't explicitly differentiate from similar tools like get_plan_json_output or get_plan_logs, 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 retrieving 'comprehensive information' but doesn't specify scenarios where this is preferred over other plan-related tools like get_plan_json_output or get_plan_logs, nor does it mention 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 full burden but only partially discloses behavior. It states the tool retrieves a paginated list and includes pagination parameters, which is helpful. However, it doesn't cover critical aspects like whether this is a read-only operation (implied but not stated), rate limits, authentication needs, or error conditions, leaving significant gaps for an agent.
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 upfront, followed by parameter details and return information. The API endpoint and reference link are useful but could be considered slightly extraneous; overall, most sentences earn their place 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 3 parameters with 0% schema coverage, the description is moderately complete. It covers the purpose, parameters, and paginated return, but lacks details on output structure (e.g., what fields are in the list), error handling, or behavioral constraints, which are important for a list tool in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, which it does effectively. It explains all three parameters: 'organization' as the organization name, 'page_number' with default 1, and 'page_size' with default 20 and max 100. This adds clear meaning beyond the basic schema, though it doesn't detail format constraints (e.g., string patterns for organization).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'List variable sets in an organization' and specifies it retrieves a paginated list, which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_variable_set' (which retrieves a single variable set) or 'list_variables_in_variable_set' (which lists variables within a set), missing full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by mentioning variable sets allow reuse across workspaces, suggesting this tool is for viewing available sets. However, it lacks explicit guidance on when to use this versus alternatives like 'get_variable_set' for a specific set or 'list_variables_in_variable_set' for details within a set, and provides no exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that this is a read operation ('Get', 'Retrieves'), which is helpful, but lacks details on behavioral traits like authentication requirements, rate limits, error conditions, or whether it's idempotent. The API endpoint mention adds some context, but overall, the behavioral disclosure is minimal 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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by clarifying details, API endpoint, Args, Returns, and a See reference. Each section earns its place without redundancy, and the structure is logical and easy to parse. No sentences are wasted.
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 (1 parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It explains the parameter and return value at a high level, but without annotations or output schema, it lacks details on response structure, error handling, or prerequisites. For a read-only tool, this is adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only 1 parameter, the description compensates well by explaining the 'workspace_id' parameter in the Args section: 'The ID of the workspace (format: "ws-xxxxxxxx")'. This adds crucial semantic meaning beyond the bare schema, specifying the format and purpose. However, it doesn't cover edge cases or examples, preventing a perfect score.
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 the current state version for a workspace' and specifies it retrieves the input state for Terraform operations. It uses specific verbs ('Get', 'Retrieves') and identifies the resource ('state version for a workspace'). However, it doesn't explicitly differentiate from sibling tools like 'get_state_version' or 'list_state_versions', which is why it doesn't achieve 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 retrieving the 'current' state version but doesn't clarify when to choose this over 'get_state_version' (which might fetch a specific version) or 'list_state_versions' (which lists multiple). There are no explicit when/when-not instructions or named alternatives, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 discloses that the tool 'retrieves' (read operation) and mentions automatic following of redirects to log files, which is useful behavioral context. However, it doesn't cover important aspects like authentication requirements, rate limits, error handling, or whether logs might be large/paginated. The API endpoint reference adds some transparency but isn't comprehensive.
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 statement, API context, Args, Returns, and reference. Each sentence adds value without redundancy. It could be slightly more concise by integrating the API endpoint into the main description rather than as a separate line, but overall it's efficiently 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?
For a single-parameter read tool with no annotations and no output schema, the description provides adequate basics: purpose, parameter details, and return behavior. However, it lacks context about the log format (text, JSON, size), error scenarios, or how this fits into broader Terraform Cloud workflows. The documentation reference helps but doesn't substitute for self-contained 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?
With 0% schema description coverage for the single parameter, the description compensates well by explaining 'plan_id: The ID of the plan to retrieve logs for (format: "plan-xxxxxxxx")'. This provides clear semantic meaning and format guidance beyond the bare schema. However, it doesn't explain where to obtain this ID or validate the format pattern.
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: 'Retrieve logs from a plan' with specific context about Terraform Cloud plan operations. It distinguishes this from sibling tools like 'get_plan_details' or 'get_plan_json_output' by focusing on raw log retrieval rather than plan metadata or structured output. However, it doesn't explicitly contrast with 'get_apply_logs' which might retrieve logs from apply 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 context by mentioning it retrieves logs from 'plan operations' and references an API endpoint, suggesting it's for accessing execution plan details. It doesn't provide explicit when-to-use guidance versus alternatives like 'get_plan_json_output' for structured data or 'get_apply_logs' for apply operation logs. The 'See' reference to documentation offers potential guidance but isn't direct.
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 'retrieves comprehensive information' and mentions what's included (variables, workspace assignments, configuration), which adds value. However, it doesn't disclose critical behavioral traits like whether it's read-only, requires authentication, has rate limits, or error handling. The API endpoint mention is helpful but insufficient for full 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. The additional sections (Args, Returns, See) are structured but slightly verbose; the API endpoint line could be integrated more seamlessly. Overall, most sentences earn their place, though minor trimming is possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage and no output schema, the description does well on parameters but lacks output details. It mentions return content in general terms but doesn't specify structure or examples. For a detail-retrieval tool with no annotations, this leaves gaps in understanding the full behavior and response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully. It provides the parameter name 'varset_id', specifies its purpose ('The ID of the variable set'), and gives format details ('format: "varset-xxxxxxxx"'), which adds significant meaning beyond the bare schema. This fully compensates for the lack of schema 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 ('Get details', 'Retrieves') and resource ('variable set'), specifying it's for a specific variable set. It distinguishes from sibling tools like 'list_variable_sets' by focusing on details retrieval rather than listing. However, it doesn't explicitly contrast with other detail-retrieval tools like 'get_workspace_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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when details for a specific variable set are needed, but doesn't explicitly state when to use this versus alternatives like 'list_variable_sets' or other detail tools. It mentions the API endpoint format, which provides some context, but lacks explicit guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves a list (implying read-only behavior) and mentions the API endpoint (GET), which hints at safe, non-destructive operations. However, it lacks details on permissions, rate limits, error handling, or pagination, which are important 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, starting with the core purpose. It includes necessary details like the API endpoint and return format, but the 'See:' reference to external documentation adds minor verbosity. Overall, it is efficient with minimal 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 (1 parameter, no output schema, no annotations), the description is mostly complete but has gaps. It explains the purpose, parameter, and return value, but lacks behavioral details like error handling or pagination. With no output schema, it should ideally describe the return structure more thoroughly, but it does provide a basic outline.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, so the description must compensate. It adds meaning by specifying the parameter 'project_id' with its format ('prj-xxxxxxxx'), which clarifies the expected input beyond the schema's basic type. Since there are no other parameters, this is sufficient for a high score, though not perfect as it doesn't cover edge cases.
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 tag bindings for a project' and 'Retrieves the list of tags bound to a specific project.' It specifies the verb ('list', 'retrieves') and resource ('tag bindings', 'project'), but does not explicitly differentiate it from sibling tools like 'add_update_project_tag_bindings' or 'list_projects', which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by mentioning that tags are 'inherited by all workspaces within the project,' suggesting context for when this information is relevant. However, it does not provide explicit guidance on when to use this tool versus alternatives like 'list_projects' or 'get_project_details,' nor does it mention prerequisites or exclusions, keeping it at an implied level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what information is retrieved (status, plan output, relationships) and mentions the API endpoint format, which adds useful context. However, it doesn't disclose important behavioral aspects like whether this is a read-only operation (implied but not stated), rate limits, authentication requirements, 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 and appropriately sized. It starts with the core purpose, provides usage guidance, includes the API endpoint, documents the parameter with format details, describes the return value, and references external documentation. Each section adds value, though the 'See:' reference could be integrated more smoothly.
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 single-parameter retrieval tool with no annotations and no output schema, the description provides adequate coverage of the tool's purpose, usage, parameter, and return value. However, it lacks details about the structure of the returned data (beyond mentioning it includes 'status, plan, and relationships') and doesn't address potential error conditions or authentication requirements that would be important for an API tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant value beyond the input schema. With 0% schema description coverage and only one parameter, the description provides the parameter name ('run_id'), explains its purpose ('The ID of the run to retrieve details for'), and specifies the expected format ('format: "run-xxxxxxxx"'). This fully compensates for the lack of schema documentation.
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 run' and specifies it retrieves 'comprehensive information about a run including its current status, plan output, and relationship to other resources.' This is a specific verb+resource combination. However, it doesn't explicitly distinguish this from sibling tools like 'get_plan_details' or 'get_apply_details' which might retrieve related but different information.
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 usage context: 'Use to check run progress or results.' This gives a specific scenario when to use the tool. However, it doesn't mention when NOT to use it or explicitly name alternative tools for related but different purposes (like using 'get_plan_details' for plan-specific information).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively adds context beyond basic functionality: it specifies that the redirect to the log file is automatically followed, mentions admin-level access requirements, and notes it cannot be accessed with organization tokens. This provides useful behavioral insights like authentication needs and operational details, though it could benefit from mentioning rate limits 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 and appropriately sized. It starts with a clear purpose statement, provides details in sections (Args, Returns, Note, See), and avoids unnecessary fluff. Every sentence adds value, such as the API endpoint reference and access note, making it efficient and front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a single-parameter read operation), no annotations, and no output schema, the description does a solid job. It explains what the tool does, the parameter, return value, access requirements, and provides a reference. It could be more complete by detailing the log format or error cases, but for a tool with minimal structured data, it covers key aspects adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for the single parameter: 'assessment_result_id: The ID of the assessment result to retrieve logs for (format: "asmtres-xxxxxxxx")'. This clarifies the parameter's purpose and format, which is not covered in the schema. Since there's only one parameter and the description fully documents it, this earns a high score.
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: 'Retrieve logs from an assessment result' and 'Gets the raw log output from a Terraform Cloud assessment operation'. It specifies the resource (assessment logs) and action (retrieve/get), but doesn't explicitly differentiate from sibling tools like 'get_apply_logs' or 'get_plan_logs', which is why it doesn't reach 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context: it mentions that this is for Terraform Cloud assessment operations and includes a note about admin access requirements. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_assessment_json_output' or other log-retrieval tools in the sibling list, leaving usage somewhat implied rather than clearly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false (indicating a write operation), which aligns with the 'Create' action. The description adds useful context about what gets created (variable set with configuration/metadata) and mentions the API endpoint, but doesn't disclose behavioral traits like authentication requirements, rate limits, or error conditions beyond what annotations already indicate.
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, API endpoint, args, returns, see). It's appropriately sized and front-loaded with the core purpose. The 'See' reference could be considered slightly extraneous but doesn't significantly detract from conciseness.
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 creation tool with no output schema and 0% schema description coverage, the description provides substantial context: clear purpose, parameter documentation, return value description, and API endpoint. It adequately covers what the tool does and what to expect, though it could benefit from more behavioral details like error cases or permissions required.
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 carries full burden. It clearly documents all 3 parameters (organization, name, params) and provides meaningful details about the params subfields (description, global, priority). This significantly compensates for the lack of schema descriptions, though it doesn't cover all possible parameter constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Create a new variable set') and resource ('in an organization'), and distinguishes it from siblings by explaining its unique purpose ('manage variables across multiple workspaces and projects'). It goes beyond just restating the name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning variable management across workspaces and projects, but doesn't explicitly state when to use this tool versus alternatives like 'create_workspace_variable' or 'update_variable_set'. No explicit when-not-to-use guidance or prerequisite information is provided.
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 discloses key behavioral traits: pagination behavior, search/filtering capabilities, and that it returns metadata with pagination info. However, it doesn't mention rate limits, authentication requirements, error conditions, or whether results are sorted. The description adds useful context but leaves gaps in behavioral understanding.
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, parameters, returns, reference). Every sentence adds value, though the 'See:' reference could be integrated more smoothly. It's appropriately sized for a tool with 5 parameters and no annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description provides good coverage. It explains what the tool does, all parameters, and the return format. The main gap is lack of output schema details, but the description compensates by describing the return structure. For a list/read tool, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining all 5 parameters in detail. It clarifies that 'q' searches both name and email, while 'query_email' and 'query_name' are specific filters. It also explains default values and the pagination parameters' purpose, 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 ('List organizations'), resource ('organizations'), and scope ('the current user has access to'). It distinguishes this tool from siblings like 'get_organization_details' (which gets a single organization) and 'create_organization' (which creates rather than lists).
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 multiple organizations with filtering, but doesn't explicitly state when to use this versus alternatives like 'get_organization_details' for single organizations or 'list_projects' for different resources. It mentions the API endpoint but doesn't provide contextual guidance about prerequisites or constraints.
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 mentions 'powerful filtering' and 'pagination details', which are useful behavioral traits. However, it lacks details on rate limits, authentication requirements, error handling, or whether this is a read-only operation (though 'List' implies reading). The API endpoint hint adds some technical context but not full behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, usage context, API endpoint, parameter list, return info, and reference link. It's appropriately sized for a tool with 13 parameters, though the 'Args' section is somewhat verbose but necessary given the parameter count. Every section adds value.
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 (13 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose, usage, parameters, and returns, but lacks details on output structure (beyond 'List of runs with metadata'), error cases, or authentication. For a tool with many filtering options, more guidance on parameter usage would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides an 'Args' section that lists all 13 parameters with brief explanations, adding significant meaning beyond the bare schema. However, it doesn't explain parameter formats (e.g., what values 'filter_operation' accepts) or interactions between filters, leaving some gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'runs across all workspaces in an organization', specifying the scope as organization-wide. It distinguishes from the sibling tool 'list_runs_in_workspace' by emphasizing the broader organizational scope rather than workspace-specific runs.
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 this tool: 'organization-wide auditing, monitoring deployments across teams, or finding specific runs by commit or author.' It implies this is for cross-workspace analysis but does not explicitly state when NOT to use it or name alternatives like 'list_runs_in_workspace' as a direct comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions filtering and pagination capabilities, which is helpful. However, it doesn't address important behavioral aspects like rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though implied by 'List'). The API endpoint reference adds some technical context but doesn't fully compensate for missing behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, usage, API endpoint, args, returns, reference). It's appropriately sized for a tool with 12 parameters. The 'See' reference to external documentation is useful but could be considered extraneous. Most sentences earn their place by adding value beyond the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, no annotations, no output schema), the description does a reasonable job but has gaps. It explains the purpose and parameters well, but lacks details about return structure (only mentions 'List of runs with metadata, status info, and pagination details' without specifics), error handling, or authentication requirements. For a tool with this many parameters and no structured output schema, more detail would be beneficial.
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 12 parameters, the description provides significant value by explaining the purpose of most parameters in the 'Args' section. It clarifies what each filter does (e.g., 'filter by operation type', 'filter by status', 'search by VCS username') and provides format guidance for workspace_id. However, it doesn't explain parameter formats for filters like 'filter_timeframe' or 'filter_status_group', leaving some ambiguity.
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 runs in a workspace with filtering and pagination'), identifies the resource ('runs'), and distinguishes it from siblings like 'list_runs_in_organization' by specifying workspace scope. It provides a verb+resource+scope combination that 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 explicitly states when to use this tool ('Useful for auditing changes, troubleshooting, or monitoring deployment history'), providing clear context. However, it doesn't specify when NOT to use it or mention alternatives like 'list_runs_in_organization' for organization-level runs, which would be helpful for sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully describes that the tool follows redirects automatically and provides access to state data for recovery, but lacks details about permissions needed, rate limits, error handling, or response format. It adequately covers the core behavior but misses operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. Each sentence adds value: the first states what it does, the second elaborates context, the third gives API details, and subsequent sections clarify parameters, returns, and references. There is 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 no annotations and no output schema, the description provides adequate context for a simple read operation with one parameter. It covers purpose, usage, parameter details, and behavioral notes like redirect following, but lacks information on response structure, error cases, or authentication requirements, leaving some gaps for an 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?
Schema description coverage is 0%, so the description must compensate. It provides the parameter name (apply_id) and clarifies its format ('apply-xxxxxxxx') and context ('The ID of the apply with a failed state upload'), adding meaningful semantics beyond the bare schema. However, it does not explain validation rules 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 tool's purpose with specific verbs ('Retrieve', 'Gets') and resources ('errored state from a failed apply', 'information about a state file that failed to upload'). It distinguishes itself from siblings by focusing on recovery of failed state uploads, unlike general state tools like get_state_version or download_state_file.
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 this tool ('from a failed apply', 'during an apply', 'for recovery purposes'), but does not explicitly state when not to use it or name specific alternatives. It implies usage for recovery scenarios without detailing prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that it 'retrieves comprehensive information' and mentions the API endpoint, but does not cover behavioral traits like authentication requirements, rate limits, error handling, or whether it's idempotent. The description adds some context but leaves gaps for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, bullet-like sections for Args and Returns, and a See reference. It's appropriately sized but includes minor redundancy (e.g., 'Get details' and 'Retrieves comprehensive information'). Every sentence adds value, though it could be slightly more front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter, no output schema, and no annotations, the description provides good coverage: clear purpose, parameter details, return value explanation, and API endpoint. It lacks output structure details and behavioral context, but for a simple read tool, it's mostly complete. The reference to external docs helps fill 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 explicitly documents the single parameter 'state_version_id' with its purpose and format ('sv-xxxxxxxx'), adding essential meaning beyond the schema's minimal title. This fully compensates for the lack of schema descriptions, though it doesn't cover edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get details' and resource 'specific state version', with elaboration on what details are retrieved (status, download URLs, resource information). It distinguishes from sibling tools like 'list_state_versions' (which lists multiple) and 'get_current_state_version' (which gets a specific type).
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 by specifying 'specific state version' and referencing the API endpoint, but does not explicitly state when to use this versus alternatives like 'get_current_state_version' or 'list_state_versions'. It provides clear prerequisites (need a state version ID) but lacks explicit exclusions or comparison to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool is a retrieval operation ('Get details', 'Retrieves comprehensive information'), which implies it's read-only and non-destructive. However, it doesn't mention authentication requirements, rate limits, error conditions, or response format details beyond high-level fields.
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 API endpoint reference and 'See' section are useful but could be considered slightly extraneous; however, they don't significantly detract from clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no output schema, the description is reasonably complete. It explains what the tool does, what parameter it needs, and what information it returns. It could benefit from more behavioral details (e.g., error handling), but covers the essentials given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description compensates well. It explains the single parameter 'state_version_output_id' as 'The ID of the state version output' and provides the exact format ('wsout-xxxxxxxx'), which adds crucial meaning beyond the schema's basic string type.
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 ('Get details for a specific state version output') and resource ('state version output'), distinguishing it from siblings like 'list_state_version_outputs' (which lists multiple) and 'get_state_version' (which gets the version itself, not its outputs). It explicitly mentions retrieving comprehensive information including name, value, type, and sensitivity.
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 by specifying it's for a 'specific' state version output, suggesting it should be used when you have a known ID. It doesn't explicitly state when not to use it or name alternatives, but the specificity provides clear guidance compared to list operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal important behavioral traits: pagination behavior, filtering capabilities, and that it retrieves configuration settings and metadata. However, it doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation (though 'list' and 'retrieves' imply reading).
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 statement, detailed explanation, API endpoint reference, parameter documentation, return value description, and documentation reference. While slightly longer than minimal, every section adds value. The front-loaded purpose statement is clear and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description provides good coverage. It explains what the tool does, how to use parameters, what it returns, and references additional documentation. The main gap is lack of explicit behavioral constraints (auth, rate limits, errors) which would be helpful for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for the lack of parameter documentation in the schema. It does this well by explaining all 4 parameters in the 'Args' section with clear semantics: organization context, pagination controls (with defaults and max), and search filtering purpose. The description adds significant value beyond what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('list', 'retrieves', 'filter') and resources ('workspaces in an organization', 'paginated list'). It distinguishes itself from siblings like 'get_workspace_details' by focusing on listing multiple workspaces rather than fetching details of a single one. The description explicitly mentions filtering capabilities and use cases.
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 this tool ('to discover existing workspaces, check workspace configurations, or find specific workspaces by partial name match'). It doesn't explicitly state when NOT to use it or name specific alternatives, but the context is sufficient to understand this is for listing/filtering workspaces rather than creating or modifying them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, confirming this is a mutation tool. The description adds valuable behavioral context beyond annotations: it specifies this is an 'additive operation that doesn't remove existing tags' and mentions the API endpoint (PATCH), which helps the agent understand the operation's effect and implementation 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 well-structured and front-loaded with the core purpose, followed by parameter explanations, return value, and reference. Every sentence adds value without redundancy, and the 'See' section provides helpful documentation pointers without cluttering the main description.
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 mutation tool with 2 parameters, 0% schema coverage, no output schema, and minimal annotations, the description does a good job covering purpose, parameters, and behavior. It could be more complete by detailing error conditions or TagBinding constraints, but it's largely adequate given the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by explaining both parameters: 'project_id' format and 'tag_bindings' as 'List of TagBinding objects with key-value pairs to add or update'. However, it doesn't provide detailed semantics for TagBinding structure beyond what's implied, leaving some gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('add or update'), resource ('tag bindings on a project'), and scope ('additive operation that doesn't remove existing tags'). It distinguishes from sibling tools like 'list_project_tag_bindings' by specifying mutation rather than querying.
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 this tool ('add or update tag bindings on a project') and mentions it's additive, but doesn't explicitly state when not to use it or name specific alternatives among siblings like 'update_project' for other modifications.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false (mutation operation), which the description confirms with 'Assign'. The description adds useful behavioral context about the API endpoint format and the empty 204 response, but doesn't mention authentication requirements, rate limits, or error conditions beyond success indication.
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 purpose statement, effect explanation, API endpoint reference, parameter details, return value, and documentation link. Every sentence serves a distinct purpose with zero redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 2 parameters and no output schema, the description provides comprehensive information about what the tool does, parameter formats, and expected response. The main gap is lack of error handling information or prerequisites, but the documentation link partially compensates.
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 providing clear parameter explanations: varset_id format ('varset-xxxxxxxx') and project_ids format (array of 'prj-xxxxxxxx'). This adds significant value beyond the bare schema, though it doesn't explain where to obtain these IDs.
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 ('Assign a variable set to one or more projects') and the resource involved ('variable set', 'projects'). It distinguishes from sibling tools like 'assign_variable_set_to_workspaces' by specifying the target resource type (projects vs workspaces).
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 this tool ('Makes the variables in a variable set available to all workspaces within the specified projects'), but doesn't explicitly mention when NOT to use it or name specific alternatives like 'assign_variable_set_to_workspaces' for workspace-level assignments.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false (indicating mutation), and the description adds useful behavioral context: it explains precedence rules ('Variables from variable sets take precedence over workspace variables if the variable set has priority enabled') and mentions the API endpoint and HTTP 204 response. However, it doesn't cover other behavioral aspects like error conditions, permissions needed, or rate limits.
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 upfront, followed by key behavioral details, parameter explanations, return information, and a reference link. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no output schema and minimal annotations, the description provides good context: purpose, behavior, parameters, and response. It could be more complete by mentioning error cases or prerequisites, but it covers the essentials well given the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining both parameters: 'varset_id' as 'The ID of the variable set' with format example, and 'workspace_ids' as 'List of workspace IDs' with format example. This adds significant 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 ('Assign a variable set to one or more workspaces') and resource ('variable set', 'workspaces'), distinguishing it from sibling tools like 'assign_variable_set_to_projects' and 'unassign_variable_set_from_workspaces' by specifying the target 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 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 this tool (to make variables available to workspaces with precedence rules) but doesn't explicitly mention when not to use it or name alternatives like 'assign_variable_set_to_projects' for different targets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the readOnlyHint annotation. It explains that variables can be marked as sensitive to hide values, mentions the specific API endpoint being called, and provides reference documentation. While it doesn't cover rate limits or authentication needs, it adds meaningful 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 clear sections (purpose, parameters, returns, reference). While slightly longer than minimal, every sentence adds value. The front-loaded purpose statement is clear, and the parameter documentation is organized efficiently.
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 creation tool with no output schema and 0% schema description coverage, the description provides comprehensive context. It covers purpose, parameters, return value description, and reference documentation. The main gap is the lack of explicit error conditions or response format details, but overall it's quite complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by providing detailed parameter information. It explains all 4 parameters, their purposes, formats, and optional sub-parameters. The description adds significant value beyond what the bare schema provides, making parameter usage clear.
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 variable'), resource ('in a variable set'), and scope ('Terraform or environment variable'). It distinguishes this tool from sibling tools like 'create_workspace_variable' by specifying it operates on variable sets rather than workspaces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning variable sets and variable types, but doesn't explicitly state when to use this tool versus alternatives like 'create_workspace_variable' or 'update_variable_in_variable_set'. It provides some guidance about sensitive variables but lacks explicit when/when-not directives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations only provide readOnlyHint=false, indicating this is a mutation tool. The description adds significant behavioral context beyond annotations: it discloses that this creates a new workspace (a write operation), mentions the API endpoint (POST), describes what a workspace contains, and lists numerous optional parameters that affect behavior (e.g., auto_apply, execution_mode). However, it doesn't mention authentication requirements, 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, API endpoint, args, params, returns, see). It's appropriately sized for a complex tool with many parameters. The 'Args' section could be more front-loaded, but overall, most sentences add value. The 'See' reference is useful but could be integrated more concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, many optional sub-parameters), no output schema, and minimal annotations, the description does a good job of providing context. It explains what the tool does, lists parameters with semantics, describes the return value, and references documentation. However, it lacks information about error handling, authentication, or how to handle the created workspace data.
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 carries the full burden of explaining parameters. It provides detailed semantic information: it lists all three parameters (organization, name, params), explains that params is optional, and enumerates 16 specific sub-parameters with brief explanations (e.g., 'execution_mode: How Terraform runs are executed'). This significantly compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Create') and resource ('new workspace in an organization'), and distinguishes it from siblings like 'create_organization' or 'create_project' by specifying it's for Terraform Cloud workspaces. The second sentence provides additional context about what workspaces contain, further clarifying the purpose.
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 context (creating a workspace in Terraform Cloud) but doesn't explicitly state when to use this tool versus alternatives like 'update_workspace' or 'list_workspaces'. It mentions the API endpoint, which provides technical context, but lacks explicit guidance on prerequisites or scenarios where this tool is appropriate versus other workspace-related tools.
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 discloses that the tool retrieves information (implying read-only behavior) and mentions the API endpoint, but lacks details on authentication needs, rate limits, error handling, or pagination. It adds some context about what's included in the details but doesn't fully cover behavioral traits like response format or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by details in clear sections (Args, Returns, See). Each sentence adds value without redundancy, such as specifying the API endpoint and referencing documentation, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is mostly complete: it explains the purpose, parameter, return values, and references external docs. However, without annotations or output schema, it could benefit from more details on error cases or exact return structure, though the reference to documentation mitigates this gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It provides the parameter 'apply_id' with its purpose and format ('The ID of the apply to retrieve details for (format: "apply-xxxxxxxx")'), adding meaningful semantics beyond the bare schema. However, it doesn't clarify if the ID is case-sensitive or where to obtain it, leaving minor gaps.
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 ('Get details for a specific apply') and resource ('apply'), distinguishing it from sibling tools like 'get_apply_logs' or 'get_run_details' by focusing on comprehensive apply information rather than logs or run details. It specifies the scope includes status, logs, resource counts, and relationships.
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 by stating it retrieves details for 'a specific apply' and references an API endpoint, suggesting it's for querying individual applies. However, it doesn't explicitly state when to use alternatives like 'get_apply_logs' for logs only or 'get_run_details' for related run information, missing explicit exclusions or 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 that the tool follows redirects automatically and uses a specific API endpoint, which is useful behavioral context. However, it doesn't mention authentication requirements, rate limits, error handling, or whether this is a read-only operation (though 'Retrieve' implies it).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, API endpoint, Args, Returns, See). Every sentence adds value: the first states the purpose, the second elaborates on content, the third specifies the endpoint, and the parameter/return sections provide essential usage details without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and no output schema, the description provides good coverage: it explains what the tool does, what parameter it needs, what it returns, and includes a reference for further documentation. The main gap is lack of explicit behavioral details like authentication or error handling, but overall it's quite complete for this tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides the parameter name ('apply_id'), clarifies its purpose ('The ID of the apply to retrieve logs for'), and specifies the expected format ('apply-xxxxxxxx'). This adds substantial meaning beyond the bare schema, though it doesn't explain where to obtain this ID.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieve logs'), target resource ('from an apply'), and scope ('raw log output from a Terraform Cloud apply operation'). It distinguishes itself from sibling tools like 'get_apply_details' by focusing on logs rather than general apply metadata.
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 this tool ('Gets the raw log output... providing detailed information about resource changes and any errors'), but does not explicitly mention when not to use it or name alternatives. It implies usage for debugging apply operations but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool retrieves data (implying read-only behavior) and mentions automatic redirect following, which adds useful context. However, it lacks details on authentication needs, rate limits, error handling, or response format beyond 'complete JSON formatted plan', leaving behavioral gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose in the first sentence. Each subsequent sentence adds value: clarifying the output format, noting automatic redirect following, and providing references. There is no wasted text, and the structure with clear sections (Args, Returns, See) enhances readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is fairly complete. It covers purpose, parameter semantics, and return value details, and includes a reference link. However, it lacks explicit error handling or usage boundaries, which could improve completeness for a tool with no structured output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'run_id' is for retrieving plan JSON output, specifies the format ('run-xxxxxxxx'), and clarifies its purpose. With only one parameter, this compensates well for the schema's lack of descriptions, though it could detail parameter constraints more.
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 ('Retrieve', 'Gets') and resource ('JSON execution plan from a run', 'JSON representation of a run's current plan execution details'), distinguishing it from siblings like get_plan_details or get_plan_json_output by focusing on the JSON output format for a specific run's plan. It explicitly mentions 'machine-readable format of the planned resource changes' which adds specificity.
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 by specifying it retrieves JSON output for a run's plan, suggesting it's for accessing structured plan data rather than logs or details. However, it does not explicitly state when to use this tool versus alternatives like get_plan_details or get_plan_json_output, nor does it mention prerequisites or exclusions, leaving some ambiguity.
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 this is a read operation ('Get', 'Retrieves') and mentions the API endpoints, but doesn't cover authentication requirements, rate limits, error conditions, or pagination behavior. It adds some context about what information is returned but could be more comprehensive for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections: purpose, usage context, identification methods, API endpoints, args, returns, and reference. While comprehensive, some sentences could be more concise (e.g., 'This is useful for...' could be integrated more tightly). Overall it's appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and no output schema, the description does an excellent job explaining parameter semantics and return values. It covers identification methods, API endpoints, and what information is retrieved. The main gap is lack of behavioral details like authentication or error handling, but overall it's quite complete for the given context.
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 explaining all three parameters in detail: workspace_id format ('ws-xxxxxxxx'), organization and workspace_name requirements ('required if workspace_id not provided'), and the two identification methods. It provides essential semantic information not present in the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'workspace details', specifying it retrieves comprehensive information including configuration, VCS settings, execution mode, and other attributes. It distinguishes from siblings like 'list_workspaces' (which lists multiple) and 'get_organization_details' (different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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 this tool: 'checking workspace settings before operations or determining the current state of a workspace.' It doesn't explicitly state when not to use it or name specific alternatives among siblings, but the purpose is sufficiently distinct from other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly describes the tool as a read operation ('Retrieves'), specifies pagination behavior, includes the API endpoint, and mentions the return format. However, it doesn't cover potential errors, authentication requirements, or rate limits, which would be helpful for a tool with no annotations.
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, behavior, parameters, returns, reference). While efficient, the 'See:' reference could be integrated more seamlessly, and some sentences could be slightly more concise. Overall, it's appropriately sized and front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read/list tool with no annotations and no output schema, the description does a good job covering purpose, behavior, parameters, and return format. It includes the API endpoint and reference documentation. The main gap is lack of error handling or authentication context, but given the tool's relative simplicity, it's reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by providing detailed parameter information. It explains all three parameters: 'state_version_id' (with format example), 'page_number' (with default), and 'page_size' (with default and max value). This adds significant value beyond what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('List outputs for a state version') and resource ('state version outputs'), distinguishing it from siblings like 'get_state_version_output' (singular) and 'list_state_versions'. It explicitly mentions what is retrieved ('paginated list of all outputs') and what information they contain ('name, value, and sensitivity information').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by specifying it's for retrieving outputs for a 'specific state version', but doesn't explicitly state when to use this tool versus alternatives like 'get_state_version_output' (singular output) or other list tools. No guidance on prerequisites, exclusions, or comparison with sibling tools is provided.
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 discloses key behavioral traits: pagination behavior, filtering capability, and the fact it retrieves configuration settings and metadata. However, it doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation (though 'List' implies it).
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?
Well-structured with purpose statement, behavioral details, parameter explanations, and return value description in logical sections. The 'See' reference could be omitted for pure conciseness, but overall it's efficiently organized with minimal fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 5-parameter list tool with no annotations and no output schema, the description provides good coverage: purpose, behavior, all parameters with semantics, and return format. It could improve by mentioning authentication or linking to sibling tools more explicitly, but it's largely complete for the agent's needs.
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 explaining all 5 parameters in the 'Args' section with clear semantics: what each parameter represents, defaults for page_number and page_size, constraints (max: 100), and valid values for filter_status. 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 ('List state versions'), resource ('in a workspace'), and scope ('Retrieves a paginated list of all state versions in a Terraform Cloud workspace'). It distinguishes from sibling tools like 'get_state_version' (singular) and 'get_current_state_version' (specific version).
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 this tool ('to find specific state versions' via filtering) and mentions the API endpoint. However, it doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools like 'get_state_version' for retrieving a single version.
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 API endpoint and return format ('List of workspace variables with their configuration and values'), which is useful behavioral context. However, it doesn't mention pagination, rate limits, authentication requirements, or error conditions that would be important for a production 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 with clear sections (purpose, API endpoint, Args, Returns, See). Every sentence earns its place - the first two sentences establish purpose, subsequent sections provide technical details without redundancy. The reference documentation link is appropriately placed at the end.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with 1 parameter and no output schema, the description provides good coverage: purpose, parameter details, return format, and API endpoint. It lacks information about authentication, error handling, and pagination which would be useful for completeness, but covers the essential context for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only 1 parameter, the description provides the parameter name 'workspace_id' and clarifies its format ('ws-xxxxxxxx'), which adds meaningful semantics beyond the bare schema. It doesn't fully explain what a workspace ID is or how to obtain one, but provides essential format guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'all variables for a workspace', specifying both Terraform and environment variables. It distinguishes from siblings like 'list_variables_in_variable_set' by focusing on workspace-specific variables rather than variable sets.
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 this tool ('for a specific workspace'), but doesn't explicitly state when not to use it or name alternatives. It implies usage when needing workspace variables rather than variable set variables, but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, correctly indicating this is a mutation tool. The description adds valuable behavioral context beyond annotations: it specifies that updates are partial ('Only specified attributes will be updated'), mentions the API endpoint (PATCH /organizations/{organization}), and indicates what the tool returns ('The updated organization with all current settings'). It doesn't cover rate limits, authentication requirements, or error conditions, but adds meaningful 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, API endpoint, args, returns, see reference) and front-loads the core functionality. It's appropriately sized for a complex tool with many parameters, though the parameter list is lengthy. 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (mutation with many parameters), no output schema, and 0% schema description coverage, the description does an excellent job of providing necessary context. It explains what the tool does, documents parameters thoroughly, specifies the return value, and references external documentation. The main gap is lack of explicit error handling or permission requirements.
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 detailed parameter information. It lists all 11 possible parameters within 'params' with clear explanations of what each controls (e.g., 'email: Admin email address for the organization'), and specifies that 'organization' is required. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('Update'), target resource ('an existing organization in Terraform Cloud'), and scope ('Modifies organization settings such as email contact, authentication policy, or other configuration options'). It distinguishes itself from sibling tools like 'create_organization' by specifying it updates existing organizations rather than creating new ones.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by stating 'Only specified attributes will be updated,' which suggests partial updates are possible. However, it doesn't explicitly state when to use this tool versus alternatives like 'create_organization' or provide any prerequisites, exclusions, or comparison with other update 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations. While annotations only indicate readOnlyHint=false (implying mutation), the description clarifies that 'only specified attributes will be updated; unspecified attributes remain unchanged', which is a critical partial-update behavior. It also mentions the API endpoint and references external documentation, though it does not detail authentication needs, rate limits, 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 clear sections (purpose, usage, args, returns, see) and front-loads the core purpose. However, it includes some redundancy (e.g., repeating 'update' in the first sentence) and could be more concise by integrating the parameter list more seamlessly, though the detailed parameter explanations are justified given the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters with 0% schema coverage, no output schema, and no annotations beyond readOnlyHint), the description is largely complete. It explains the tool's purpose, parameters, and behavior, and references external documentation. However, it lacks details on return values (since no output schema) and does not fully address all behavioral aspects like error conditions or side effects.
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 extensive parameter semantics that compensate for the 0% schema description coverage. It lists and explains 14 specific parameters (e.g., 'execution_mode: How Terraform runs are executed (remote, local, agent)'), adding meaning not present in the schema. This is crucial given the low schema coverage and the tool's 3 parameters, including a complex nested object.
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 'updates an existing workspace' and specifies it 'modifies the settings of a Terraform Cloud workspace', providing a specific verb (update/modify) and resource (workspace settings). It distinguishes from sibling tools like 'create_workspace' by focusing on existing workspaces and from 'update_workspace_variable' by targeting workspace settings rather than variables.
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 modifying workspace settings and mentions that 'only specified attributes will be updated', which provides some context. However, it lacks explicit guidance on when to use this tool versus alternatives like 'update_organization' or 'update_project', and does not mention prerequisites such as required permissions or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false (mutation), which aligns with the description's 'Remove' action. The description adds valuable behavioral context: it specifies the API endpoint (DELETE), mentions the empty response with HTTP 204 status, and references external documentation. This goes beyond what annotations provide.
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, effect, API endpoint, args, returns, see). It is appropriately sized but could be slightly more front-loaded; the API endpoint detail might be less critical upfront.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the mutation nature (annotations: readOnlyHint=false), 2 parameters with no schema descriptions, and no output schema, the description is complete: it explains the action, parameters, response, and provides a documentation reference. It adequately covers the tool's context.
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 documenting both parameters: 'varset_id' (ID of the variable set with format) and 'workspace_ids' (list of workspace IDs with format). It provides clear semantic 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 ('Remove a variable set from one or more workspaces') and distinguishes it from siblings like 'unassign_variable_set_from_projects' by specifying workspace targets. It explains the effect ('variables will no longer be available in those workspaces'), providing a complete purpose statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the effect statement, but does not explicitly state when to use this tool versus alternatives like 'unassign_variable_set_from_projects' or 'assign_variable_set_to_workspaces'. It lacks explicit guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false (mutation), which the description confirms with 'Unlock' and 'Removes the lock.' The description adds valuable behavioral context beyond annotations: it specifies the API endpoint (POST), mentions enabling 'normal operation' and 'allowing runs to be queued,' and references external documentation. No contradiction with annotations exists.
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, API endpoint, Args, Returns, See). It's front-loaded with the core purpose and uses efficient sentences. The external documentation reference is useful but slightly extends length.
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 mutation tool with no output schema, the description adequately covers purpose, parameters, and behavior. It mentions the return value ('workspace with updated lock status') and links to documentation. However, it lacks details on error cases, permissions, or side effects, which would be helpful given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for the single parameter 'workspace_id,' the description compensates by specifying the parameter in the Args section with format details ('ws-xxxxxxxx'). This adds essential meaning beyond the bare schema, though it doesn't explain where to obtain the ID or validation rules.
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 ('Unlock a workspace'), the resource affected ('workspace'), and the outcome ('removes the lock... allowing runs to be queued'). It distinguishes from the sibling 'lock_workspace' by describing the opposite operation, and from 'force_unlock_workspace' by implying a standard vs forced approach.
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 this tool: 'after it was previously locked' and 'enables normal operation.' It distinguishes from 'force_unlock_workspace' by not mentioning forced alternatives, but doesn't explicitly state when to choose one over the other or list other alternatives like workspace creation or deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, which aligns with the 'create' action. The description adds valuable context beyond annotations by specifying the API endpoint (POST /organizations), mentioning it's a foundational setup step, and providing a reference to external documentation. However, it doesn't disclose potential side effects like rate limits or authentication requirements.
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, API endpoint, args, returns, see), but could be more front-loaded. The parameter list is comprehensive but lengthy, though each item earns its place by documenting parameters not covered in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with no output schema and 0% schema description coverage, the description does an excellent job explaining parameters and purpose. It provides API endpoint details and documentation references. The main gap is lack of information about return values beyond 'created organization details including ID and created timestamp' - more specifics would help.
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 detailed parameter information. It clearly explains the required 'name' and 'email' parameters, then comprehensively lists 12 optional parameters within 'params' with clear explanations of what each controls, 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 ('Create a new organization'), resource ('in Terraform Cloud'), and purpose ('allowing workspaces and teams to be created within it'). It distinguishes this tool from sibling tools like 'update_organization' by emphasizing it's the 'first step in setting up a new environment'.
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 this tool ('first step in setting up a new environment in Terraform Cloud'), but doesn't explicitly state when not to use it or mention specific alternatives like 'update_organization' for modifying existing organizations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false (indicating a write operation), which aligns with the 'Create' action. The description adds valuable behavioral context beyond annotations: it explains the purpose of projects ('container for workspaces'), mentions they can have settings and permissions, and provides the API endpoint. However, it doesn't disclose rate limits, authentication requirements, or error behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, API endpoint, args, returns, see). It's appropriately sized for a creation tool with multiple parameters. Some redundancy exists (e.g., auto_destroy_activity_duration appears twice), 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with 3 parameters, 0% schema coverage, no output schema, and minimal annotations, the description provides substantial context: purpose, parameter details, return value description, and API reference. It adequately compensates for the lack of structured documentation, though could benefit from more behavioral details like error handling.
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 carries the full burden of parameter documentation. It successfully explains all 3 parameters: 'organization' (name of organization), 'name' (name to give project), and 'params' with detailed sub-parameters including descriptions and examples like '14d' for auto_destroy_activity_duration. 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 project'), the resource ('in an organization'), and the platform context ('Terraform Cloud project'). It distinguishes from siblings like 'create_organization' or 'create_workspace' by specifying it creates a project as a container for workspaces, not other resource types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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 this tool: to create a Terraform Cloud project for organizing workspaces. It doesn't explicitly state when NOT to use it or name specific alternatives, but the context implies it's for project creation versus other creation tools like 'create_workspace' or 'create_organization'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the readOnlyHint=false annotation. It explains that the run 'queues in the workspace and executes based on the workspace's execution mode and settings,' describes the API endpoint, and provides a detailed returns section. However, it doesn't mention rate limits, authentication requirements, 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, usage, API endpoint, args, returns, reference). While comprehensive, some sentences could be more concise, and the detailed param list makes it longer than minimal.
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 complex mutation tool with no output schema, the description provides substantial context: purpose, usage, parameters, return values, and API reference. It covers the essential aspects but could benefit from more behavioral details about error handling or execution constraints.
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 comprehensive parameter documentation. It explains workspace_id format and details 14 specific params with clear explanations of their purposes, going far beyond what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a new Terraform run to trigger infrastructure changes, specifying it represents a single execution of plan and apply operations. It distinguishes from siblings by focusing on run creation rather than management operations like cancel_run or apply_run.
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 this tool: 'to deploy new infrastructure, apply configuration changes, or destroy resources.' It mentions the run queues in the workspace and executes based on workspace settings, but doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only indicate this is not read-only (readOnlyHint: false). The description adds valuable behavioral context beyond this: it specifies a prerequisite (workspace must be locked), describes the effect (sets as current state version), mentions the API endpoint, and references external documentation. No contradiction with annotations exists.
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, prerequisites, usage context, API endpoint, args, returns, see also). While comprehensive, some sentences could be more concise (e.g., the migration context sentence is somewhat lengthy). Overall, it's appropriately sized for a complex tool.
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 mutation tool with no output schema and 0% schema description coverage, the description provides excellent coverage: purpose, prerequisites, usage context, parameter details, return value description, and documentation references. The main gap is the lack of explicit error conditions or rate limit information, but it's otherwise very complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description carries the full burden of explaining parameters. It provides detailed explanations for all 4 parameters: workspace_id format, serial purpose, md5 purpose, and a comprehensive breakdown of optional params with their meanings and formats. This fully compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Create a state version'), target resource ('in a workspace'), and key effect ('sets it as the current state version'). It distinguishes this from sibling tools like 'get_state_version' or 'list_state_versions' by emphasizing creation rather than retrieval.
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 explicit context for when to use this tool ('most useful for migrating existing state from Terraform Community edition into a new HCP Terraform workspace') and mentions a prerequisite ('workspace must be locked by the user'). However, it doesn't explicitly state when NOT to use it or name specific alternative tools for similar operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide readOnlyHint=false, confirming this is a mutation. The description adds valuable behavioral context: it specifies the API endpoint (POST method), mentions sensitive value handling, and describes the return format. It doesn't cover rate limits, authentication needs, or error conditions, but provides solid operational context beyond annotations.
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?
Well-structured with clear sections (purpose, API endpoint, args, params, returns, reference). Most sentences earn their place by providing essential information. Slightly verbose with the 'See' reference line, but overall efficient for a complex creation tool.
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 mutation tool with no output schema and 0% schema description coverage, the description provides strong coverage: clear purpose, parameter details, return format, and API endpoint. Missing elements include error handling, authentication requirements, and rate limits, but it's substantially complete for core functionality.
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 carries full burden. It comprehensively explains all 4 parameters: workspace_id format, key purpose, category options, and details all params sub-fields with their purposes. The description provides complete parameter semantics that the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Create a new variable'), resource ('in a workspace'), and scope ('Terraform or environment variable'). It distinguishes from sibling tools like 'create_variable_in_variable_set' by specifying workspace context and from 'update_workspace_variable' by being a creation operation.
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 this tool (creating new workspace variables) and mentions key capabilities like marking variables as sensitive. However, it doesn't explicitly state when NOT to use it or name specific alternatives like 'create_variable_in_variable_set' for variable sets instead of workspaces.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (returns account information including specific fields), mentions the API endpoint, and notes the unique email visibility aspect. It doesn't cover potential errors, rate limits, or authentication requirements, but provides solid behavioral context for a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. Each sentence adds value: purpose, use cases, return format comparison, API endpoint, return content, and documentation reference. No wasted words while maintaining completeness.
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 parameterless read operation with no annotations and no output schema, the description provides excellent context. It explains what information is returned, compares it to similar API responses, and references documentation. The main gap is lack of explicit mention that this is a read-only operation, though that's implied by 'Get' and the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage. The description appropriately doesn't waste space discussing non-existent parameters. It focuses on what the tool returns rather than inputs, which is correct for a parameterless tool.
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 ('Get account details'), resource ('for a Terraform Cloud API token'), and scope ('currently authenticated user or service account'). It distinguishes itself from sibling tools by focusing on authentication/identity verification rather than resource management or run operations.
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 this tool: 'useful for verifying identity, retrieving email address, and checking authentication status.' It doesn't explicitly mention when NOT to use it or name specific alternatives, but the purpose is sufficiently distinct from sibling tools that primarily manage resources, runs, or variables.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a retrieval operation (implied read-only), specifies the API endpoint and HTTP method (GET), mentions automatic redirect following, and outlines the return content (JSON with resource changes, metadata, actions). This covers most behavioral aspects, though it lacks details on error handling or rate limits.
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 a clear purpose statement, followed by detailed sections (Args, Returns, See) that add value without redundancy. Each sentence earns its place by providing essential information like API endpoint, parameter details, and return format, with no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is largely complete: it covers purpose, usage, parameter semantics, and behavioral traits. However, it lacks explicit mention of prerequisites (e.g., authentication) or error cases, and the absence of an output schema means the return structure is only vaguely described as 'complete JSON formatted plan'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates well by explaining the single parameter 'plan_id' in the Args section, including its purpose and format ('plan-xxxxxxxx'). This adds meaningful semantics beyond the bare schema, though it could benefit from more context on where to obtain the plan_id or validation rules.
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 ('Retrieve the JSON execution plan') and resource ('plan's execution details'), distinguishing it from siblings like get_plan_details or get_plan_logs by focusing on the JSON representation of planned resource changes. It explicitly mentions the machine-readable format and planned actions, making the purpose distinct and well-defined.
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 usage by specifying that it retrieves JSON output for a plan's execution details, implying it should be used when machine-readable plan data is needed. However, it does not explicitly state when not to use it or name alternatives (e.g., get_plan_details for non-JSON format), leaving some guidance gaps compared to explicit sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well at disclosing key behavioral traits. It explicitly states the tool is for retrieval (not mutation), mentions pagination behavior, filtering capabilities, and provides the API endpoint. It doesn't cover rate limits, authentication needs, or error handling, but gives substantial operational context beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, API endpoint, Args, Returns, See). While slightly longer than minimal, every sentence earns its place by providing essential information. The front-loaded purpose statement is clear, and the parameter explanations are necessary given the poor schema coverage.
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 tool with 8 parameters, 0% schema description coverage, no annotations, and no output schema, the description provides substantial context. It covers purpose, parameters, pagination behavior, filtering options, and return format. The main gap is lack of output structure details, but given the complexity and poor structured data support, it's quite comprehensive.
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 for 8 parameters, the description provides excellent compensation by explaining all parameters in the 'Args' section with clear semantics, defaults, constraints, and usage examples. It adds significant meaning beyond what the bare schema provides, including parameter purposes, default values, maximums, and format details like comma-separated lists.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verb ('List', 'Retrieves') and resource ('projects in an organization', 'all projects in a Terraform Cloud organization'). It distinguishes from siblings by focusing specifically on listing projects rather than creating, updating, or managing them, which are covered by other tools like create_project, update_project, and get_project_details.
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 this tool: to retrieve a paginated list of projects with optional filtering. It doesn't explicitly state when NOT to use it or name specific alternatives, but the context of sibling tools (like get_project_details for single project details) implies differentiation. The mention of filtering capabilities helps guide usage decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, indicating this is a mutation operation. The description adds valuable behavioral context beyond annotations: it specifies this is a DELETE operation with an empty 204 response, describes the effect on variable availability, and references external documentation. No contradiction with annotations exists.
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, API endpoint, args, returns, reference). Each sentence adds value, though the API endpoint detail might be more technical than necessary for an agent. The information is front-loaded with the core purpose first.
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 mutation tool with 2 parameters, 0% schema coverage, and no output schema, the description provides comprehensive coverage: purpose, parameters with formats, API method, response format, and documentation reference. The only minor gap is not explicitly mentioning authentication or error cases, but it's otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by documenting both parameters with their purposes and formats. It explains varset_id identifies the variable set to unassign, and project_ids lists the target projects, including specific ID format examples that aren't in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Remove a variable set from one or more projects') and the resource affected ('variable set assignment'). It distinguishes from sibling tools like 'assign_variable_set_to_projects' by specifying the opposite operation, and from 'unassign_variable_set_from_workspaces' by targeting projects instead of workspaces.
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 this tool: when you need to remove a variable set assignment from projects, making variables unavailable in those projects' workspaces. It doesn't explicitly state when NOT to use it or name specific alternatives, but the context is sufficient for differentiation from similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, indicating this is a mutation tool. The description adds valuable behavioral context beyond annotations: it specifies that only specified attributes are updated (partial update behavior), mentions the API endpoint (PATCH /projects/{project_id}), and describes the return value. It doesn't contradict annotations, and adds useful implementation details that help the agent understand 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 well-structured with clear sections (purpose, behavior, args, returns, see). It's appropriately sized at 9 sentences, with the core information front-loaded. The 'Args' and 'Returns' sections could be slightly more concise, but overall it's efficient with minimal 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 mutation tool with 2 parameters, 0% schema coverage, no output schema, and readOnlyHint=false annotation, the description provides strong coverage: clear purpose, behavioral context, full parameter documentation, and return value explanation. It lacks explicit error handling or permission requirements, but given the context signals, it's mostly complete. The 'See' reference adds helpful documentation linkage.
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 carries full burden for parameter documentation. It provides excellent parameter semantics: clearly documents both parameters (project_id and params), explains the format for project_id ('prj-xxxxxxxx'), lists the four updatable fields within params with examples for auto_destroy_activity_duration, and explains that params is optional. This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update'), resource ('an existing project'), and scope ('Terraform Cloud project'). It distinguishes from siblings like 'create_project' by specifying it's for existing projects, and from 'update_organization' or 'update_workspace' by focusing on projects. The purpose is specific and well-differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('Modifies the settings of a Terraform Cloud project') and mentions it's for updating existing projects, which distinguishes it from 'create_project'. However, it doesn't explicitly state when NOT to use it or mention alternatives like 'update_workspace' or 'update_organization' for other resources. The guidance is clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false (mutation), which the description confirms with 'Modifies'. The description adds valuable behavioral context: it specifies that only specified attributes are updated (partial update behavior), mentions the API endpoint format, and notes that unspecified attributes remain unchanged. This goes beyond the annotation's basic mutation hint.
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, behavior, API endpoint, args, returns, see). It's appropriately sized but includes some redundancy (e.g., repeating 'New' for each param) and the 'See' reference could be more concise. Most sentences earn their place by adding value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no output schema and 0% schema coverage, the description provides strong context: clear purpose, behavioral details (partial updates), full parameter semantics, and return value description. It lacks explicit error handling or permission requirements, but covers most essential aspects given the 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?
With 0% schema description coverage, the description fully compensates by detailing all 3 parameters: varset_id and var_id with their ID formats, and params with a comprehensive list of 6 sub-parameters (key, value, description, category, hcl, sensitive) including constraints like 'terraform variables only' for hcl. This adds complete semantic 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 ('Update an existing variable in a variable set') and distinguishes it from sibling tools like 'create_variable_in_variable_set' and 'update_workspace_variable' by specifying it modifies existing variables within variable sets. It provides both verb ('Modifies') and resource ('existing variable within a variable set').
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 when to use this tool (to modify existing variables) and distinguishes it from creation tools, but doesn't explicitly state when not to use it or mention specific alternatives among siblings like 'update_workspace_variable' for workspace-specific updates. The context is clear but lacks explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, confirming this is a mutation. The description adds valuable behavioral context beyond annotations: it specifies the tool works during 'planning or applying phases,' attempts 'cleanly terminate the run by sending an interrupt signal,' and mentions the API endpoint. No contradiction with annotations.
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?
Well-structured with purpose, usage guidelines, behavioral details, parameters, returns, and reference. Most sentences are necessary, though the API endpoint line could be considered extraneous for an AI agent. Slightly verbose but efficiently organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description details return values: 'Run status update with canceled state, timestamp of cancellation, and any provided comment.' Given the tool's complexity (mutation with behavioral nuances) and lack of output schema, this provides good completeness, though could mention error cases.
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 carries full burden. It clearly explains both parameters: 'run_id' as 'The ID of the run to cancel' with format example, and 'comment' as 'optional explanation for why the run was canceled.' This compensates well for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Cancel a run') and specifies the target state ('currently planning or applying'). It distinguishes from sibling tools like 'force_cancel_run' by emphasizing 'gracefully stops' and 'cleanly terminate,' indicating a non-forced approach.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool: 'when you need to stop a run that's taking too long, consuming too many resources, or needs to be stopped for any reason.' It implicitly distinguishes from 'force_cancel_run' by not mentioning forceful termination, providing clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false (non-read-only), which aligns with the destructive action described. The description adds valuable behavioral context beyond annotations: it explains that the action 'removes the run from the queue and unlocks the workspace for new runs,' discloses it's a POST API call, and mentions the return format. No contradiction with annotations.
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. However, it includes some redundant information like the API endpoint and 'See:' reference, which could be trimmed for better conciseness without losing essential guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive action, 2 parameters, no output schema), the description is quite complete: it covers purpose, usage, parameters, behavior, and return values. The main gap is lack of explicit error handling or prerequisites, but it provides sufficient context for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining both parameters: 'run_id' is described as 'The ID of the run to discard' with format details, and 'comment' as 'An optional explanation for why the run was discarded.' This adds clear 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 ('discard a run that is paused waiting for confirmation') and distinguishes it from siblings like 'cancel_run' and 'force_cancel_run' by specifying it's for runs that are paused and waiting for confirmation, without applying changes. It explicitly mentions the resource ('run') and the verb ('discard').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('typically used when the plan shows undesired changes or after reviewing and rejecting a plan') and what it does ('Cancels a run without applying its changes'). It distinguishes from alternatives by specifying it's for 'paused waiting for confirmation' runs, unlike 'cancel_run' which might apply to other run states.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond the readOnlyHint=false annotation. It explains that this action 'bypasses the graceful shutdown process and forces the workspace to be unlocked,' which are critical behavioral traits not captured in annotations. However, it doesn't mention potential side effects like data loss or system instability.
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?
Well-structured with purpose upfront, usage guidance, API endpoint reference, parameter details, return description, and documentation link. Every sentence adds value, though the API endpoint line could be considered redundant for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no output schema, the description provides good coverage: purpose, usage context, behavioral impact, parameter semantics, and return format. It lacks explicit error conditions or permissions required, but the 'last resort' warning and workspace unlock details offer sufficient context for safe 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?
With 0% schema description coverage, the description compensates well by explaining both parameters: run_id format ('run-xxxxxxxx') and comment purpose ('optional explanation for why the run was force canceled'). It adds meaningful context beyond the bare schema, though it could specify comment length or content constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('forcefully cancel a run immediately') and distinguishes it from the sibling 'cancel_run' tool by explaining it's for when normal cancellation fails. It specifies the resource (run) and the forceful nature of the operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('as a last resort when a run is stuck and not responding to regular cancellation') and provides clear exclusion criteria (bypasses graceful shutdown). It references the alternative 'cancel_run' implicitly by contrasting with 'normal cancel request'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, indicating a write operation. The description adds valuable behavioral context beyond this: it discloses that the tool cancels other queued runs, unlocks the workspace, and prioritizes a specific run. However, it lacks details on permissions, rate limits, or error handling, which would be helpful for a destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with key information in the first sentence, followed by usage guidelines and technical details. It avoids redundancy, but the inclusion of API endpoint and 'See:' reference could be trimmed for conciseness, as they don't directly aid the AI agent in tool selection.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation with workspace implications) and lack of output schema, the description is mostly complete: it explains the action, usage, parameters, and return value. However, it could better address potential side effects or error scenarios to fully guide the 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 and 1 parameter, the description compensates by explaining the 'run_id' parameter's purpose ('The ID of the run to execute') and format ('format: "run-xxxxxxxx"'), adding meaning not in the schema. It doesn't cover edge cases or validation rules, but this is sufficient for a single 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 ('forcefully execute a run by canceling all prior runs') and the resource ('run'), distinguishing it from siblings like 'cancel_run', 'force_cancel_run', and 'apply_run'. It explicitly mentions the UI equivalent ('Run this plan now'), providing concrete context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('when a run is stuck in the pending queue but needs immediate execution due to urgency or priority over other queued runs'), distinguishing it from alternatives. It also implies when not to use it (e.g., for normal execution without force), though alternatives are not named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a read operation ('Retrieve'), mentions that redirects are automatically followed, specifies admin-level access requirements, and notes the machine-readable JSON output format. This covers safety, authentication, and response behavior adequately for a retrieval 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, starting with the core purpose. Each sentence adds value: explaining the output format, specifying the API endpoint, detailing parameters and returns, and noting access requirements. There is no wasted text, and the information is organized logically for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (1 parameter, no output schema, no annotations), the description is largely complete. It covers purpose, usage, parameters, returns, and behavioral notes like access requirements. However, it lacks details on error handling or response structure specifics, which could be useful for a tool returning JSON data, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that assessment_result_id is 'The ID of the assessment result to retrieve JSON output for' and specifies the required format ('asmtres-xxxxxxxx'), providing crucial context not present in the schema. This fully compensates 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 ('Retrieve the JSON execution plan') and resource ('from an assessment result'), distinguishing it from sibling tools like get_assessment_result_details or get_assessment_log_output by focusing on the JSON output format. It uses precise terminology like 'machine-readable format of the planned resource changes' to clarify the purpose.
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 this tool: to obtain JSON-formatted plan details from an assessment result. It mentions admin-level access requirements and notes that organization tokens cannot be used, which helps guide usage. However, it does not explicitly state when to choose this over alternatives like get_assessment_result_details or get_plan_json_output, missing explicit sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, consistent with the 'update' action. The description adds valuable behavioral context beyond annotations by explaining the partial update behavior ('Only specified attributes will be updated'), specifying the API endpoint, and noting that sensitive values can be updated. It does not mention authentication needs or rate limits, but provides useful 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, behavioral details, parameter breakdown, and return information. It is appropriately sized but includes a 'See' reference that, while helpful, slightly reduces conciseness. Most sentences earn their place by adding value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the mutation nature (annotations show readOnlyHint=false), 3 parameters with no schema descriptions, and no output schema, the description is highly complete. It covers purpose, usage behavior, all parameters with semantics, return values, and provides a documentation reference, leaving no significant gaps for tool invocation.
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 detailing all 3 parameters: workspace_id and variable_id (with format examples), and params (listing all 6 sub-parameters with clear explanations). This adds significant meaning beyond the bare schema, making parameter usage unambiguous.
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 ('Update an existing workspace variable') and resource ('workspace variable'), distinguishing it from sibling tools like 'create_workspace_variable' (for creation) and 'list_workspace_variables' (for listing). It precisely defines the operation 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage by specifying it updates existing variables and that only specified attributes are changed, implying it should be used for modifications rather than creation. However, it does not explicitly state when not to use it or name alternatives like 'create_workspace_variable' for new variables.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, indicating a write operation, which aligns with the description's 'apply' and 'executes' language. The description adds valuable context beyond annotations: it specifies the tool applies to runs in a specific state ('paused waiting for confirmation after a plan'), mentions the API endpoint, and notes it returns updated status information, enhancing behavioral understanding without contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by usage guidelines, API details, parameter explanations, return info, and a reference. Each sentence adds value without redundancy, and the structure is logical and efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a write operation with state dependencies), no output schema, and 0% schema description coverage, the description is largely complete. It covers purpose, usage, parameters, returns, and API endpoint. However, it could mention error cases or prerequisites more explicitly, leaving minor 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 carries the burden. It adds meaning for both parameters: 'run_id' is explained as 'The ID of the run to apply' with format details, and 'comment' as 'An optional comment explaining the reason for applying the run'. This compensates well for the lack of schema descriptions, though it doesn't detail all possible constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Apply a run'), the resource ('a run that is paused waiting for confirmation after a plan'), and distinguishes it from siblings like 'cancel_run' or 'force_execute_run' by specifying it's for runs in a paused post-plan state. It uses precise verbs like 'confirms and executes the apply phase'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool: 'Use this when you've reviewed the plan output and want to apply the proposed changes to your infrastructure.' It also implies when not to use it (e.g., for runs not in a paused post-plan state) and distinguishes from alternatives like 'cancel_run' or 'force_execute_run' by context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it specifies admin-level access requirements, token restrictions, and that redirects are automatically followed. However, it doesn't mention rate limits, error conditions, or response format details beyond 'JSON schema file'.
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 API endpoint details, parameter explanation, return value, and important notes. Every sentence earns its place, with no redundant information or unnecessary elaboration.
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 read operation with no annotations and no output schema, the description provides comprehensive context about purpose, usage, authentication requirements, and parameter details. The only minor gap is lack of explicit information about the structure of the returned JSON schema file.
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 one parameter, the description adds significant value by explaining the parameter's purpose ('The ID of the assessment result to retrieve schema for') and providing format details ('format: "asmtres-xxxxxxxx"'). This fully compensates 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 ('Retrieve the JSON schema file') and resource ('from an assessment result'), distinguishing it from sibling tools like 'get_assessment_json_output' or 'get_assessment_result_details'. It provides a precise verb+resource combination with explicit scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('Retrieve the JSON schema file from an assessment result') and includes a critical 'Note' section specifying when NOT to use it ('cannot be accessed with organization tokens'). It also references alternative documentation ('See: docs/tools/assessment_results.md') for further context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations only indicate readOnlyHint=false, leaving behavioral details unspecified. The description adds valuable context beyond annotations: it explains the tool's effect (prevents queuing runs), clarifies what is unaffected (current plans/applies), mentions the API endpoint, and notes the return format. However, it lacks details on permissions, rate limits, or error conditions, which would be helpful 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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by context, API details, parameter explanations, and return information. Every sentence adds value without redundancy, and the structure is clear with labeled sections (Args, Returns, See).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (mutation with 2 parameters) and lack of output schema, the description is mostly complete: it covers purpose, usage, parameters, and return format. However, it could improve by mentioning authentication requirements, error handling, or linking to sibling tools like 'unlock_workspace' for better contextual awareness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining both parameters: 'workspace_id' (ID format: 'ws-xxxxxxxx') and 'reason' (optional reason for locking). This adds meaningful semantics beyond the bare schema, though it doesn't detail constraints like length limits or validation rules for the reason 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 ('Lock a workspace') and resource ('workspace'), distinguishing it from sibling tools like 'unlock_workspace' and 'force_unlock_workspace'. It explains the effect ('prevent runs from being queued') and provides context about what is not affected ('currently running plans or applies'), making the purpose highly specific and well-differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('useful when you want to prevent changes to infrastructure while performing maintenance or making manual adjustments') and distinguishes it from alternatives by noting what it does not affect. It provides clear context for usage without exclusions, helping the agent understand appropriate scenarios for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false (implying a mutation), which aligns with the description's 'Move' action. The description adds valuable behavioral context beyond annotations: it specifies permission requirements, mentions the API endpoint, and notes the return behavior ('Empty response with HTTP 204 status code if successful'). This provides practical implementation details that annotations don't cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and efficiently front-loaded with the core purpose. Each sentence adds value: purpose statement, permission context, API endpoint, parameter details, return behavior, and documentation reference. There is no wasted text, and information is logically organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with 2 parameters, 0% schema coverage, no output schema, and annotations only covering readOnlyHint, the description provides excellent completeness. It explains the tool's purpose, usage context, behavioral details (permissions, API, response), parameter semantics, and points to further documentation, covering all essential aspects for effective use.
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 explaining both parameters: 'project_id: The ID of the destination project (format: "prj-xxxxxxxx")' and 'workspace_ids: List of workspace IDs to move (format: ["ws-xxxxxxxx", ...])'. It provides format examples and clarifies their roles, adding substantial 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 ('Move workspaces into a project') with the exact resources involved ('workspaces', 'project'). It distinguishes this tool from siblings like 'create_workspace', 'update_workspace', or 'list_workspaces' by focusing on relocation rather than creation, modification, or listing.
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 this tool ('Moves one or more workspaces into a project') and mentions a prerequisite ('The user must have permission to move workspaces on both source and destination projects'). However, it does not explicitly state when NOT to use it or name specific alternative tools for related operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that this is a retrieval operation ('Retrieves comprehensive information'), specifies the API endpoint method (GET), and notes the lack of a listing endpoint. However, it doesn't mention potential errors, rate limits, or authentication requirements.
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?
Well-structured with clear sections (description, API endpoint, Args, Returns, Note, See). Each sentence adds value: the purpose statement, parameter details, return information, important usage note, and documentation reference. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter retrieval tool with no output schema, the description is quite complete. It explains the parameter, return values, and crucial context about how to obtain the ID. The main gap is the lack of output schema, but the description compensates by listing what's returned. Slightly reduced because it doesn't detail the full structure of return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides the parameter name ('cost_estimate_id'), explains its purpose ('The ID of the cost estimate to retrieve details for'), and specifies the required format ('format: "ce-xxxxxxxx"'), adding crucial semantic information 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 ('Get details for a specific cost estimate') and resource ('cost estimate'), distinguishing it from siblings like 'get_run_details' or 'get_organization_details' by focusing on cost estimates. It specifies retrieving comprehensive information including status, resource counts, and cost estimations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided on when to use this tool: 'There is no endpoint to list cost estimates. You can find the ID for a cost estimate in the `relationships.cost-estimate` property of a run object.' This clearly indicates the prerequisite and alternative approach for obtaining the required ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations only indicate it's not read-only (readOnlyHint: false), but the description adds substantial behavioral context: it discloses the dangerous nature of the operation with warnings, explains typical scenarios for use, specifies admin privilege requirements, and mentions the API endpoint. This goes well beyond what annotations provide.
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, usage context, warnings, API endpoint, args, returns, reference). While slightly verbose, every sentence adds value—no fluff. The warning section is appropriately emphasized for a dangerous operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation with risks), the description is highly complete: it covers purpose, usage guidelines, behavioral risks, parameter details, and return information. With no output schema, it helpfully describes the return value. It addresses all critical aspects for safe and correct 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?
With 0% schema description coverage for the single parameter, the description compensates by explaining that 'workspace_id' is 'The ID of the workspace to force unlock' and provides the format 'ws-xxxxxxxx'. This adds meaningful context beyond the bare schema, though it doesn't detail validation rules or examples beyond the format hint.
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 ('force unlock') and resource ('workspace'), distinguishing it from siblings like 'unlock_workspace' by emphasizing the forceful nature. It explicitly mentions it's for when normal unlock isn't possible, providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('when a run has orphaned a lock or when the user who locked the workspace is unavailable'), when not to use it ('dangerous if the workspace is legitimately locked for active operations'), and mentions the alternative 'normal unlock process' implicitly. It also specifies prerequisites ('requires admin privileges').
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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