Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'list, get, and trigger deployments' implies read and write operations, the description doesn't disclose critical behavioral traits such as authentication requirements, rate limits, whether 'trigger' is destructive or reversible, or what happens on success/failure. For a multi-action tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place by specifying the three actions. However, it could be slightly more structured by explicitly separating the actions or adding minimal context, but it's appropriately concise for its content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, 3 distinct actions including a write operation 'trigger'), no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like side effects, error handling, or return formats, leaving the agent with insufficient context to use the tool effectively beyond basic parameter passing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all six parameters thoroughly with descriptions and enum values. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain relationships between parameters like how 'uuid' and 'deployment_uuid' differ). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Application deployment management - list, get, and trigger deployments' clearly states the tool's purpose as managing deployments with three specific actions, but it doesn't distinguish this tool from its many siblings (like coolify_application_lifecycle or coolify_service_lifecycle) that might also handle deployment-related tasks. The description is accurate but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With 17 sibling tools including several that might overlap with deployment management (e.g., coolify_application_lifecycle, coolify_service_lifecycle), the agent receives no help in selecting this specific tool over others. The description merely states what the tool does, not when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While it indicates the tool performs CRUD operations, it lacks critical information about permissions needed, whether operations are destructive, rate limits, error handling, or what happens to existing variables during bulk updates. For a multi-action tool with mutation capabilities, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured as a single phrase listing the four actions. It's front-loaded with the core purpose and avoids unnecessary elaboration. However, it could be slightly more structured by separating actions with clearer formatting.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex multi-action tool with 6 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain return values, error conditions, or the relationship between actions and parameters. The agent must rely entirely on the schema for operational details, which is insufficient for safe tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, providing complete parameter documentation. The description adds minimal value beyond the schema by listing the four action types, but doesn't explain parameter interactions, dependencies, or provide usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Application environment variables management' with specific verbs (list, create, bulk update, delete) and resource (environment variables). It distinguishes from siblings like coolify_service_envs by specifying 'application' scope, but doesn't explicitly contrast with other environment-related tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like coolify_service_envs or other application management tools. It lists actions but offers no context about appropriate use cases, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the actions but doesn't describe effects (e.g., whether stop is graceful, if restart preserves state), permissions required, error conditions, or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality ('Application lifecycle management') and lists the specific actions. There is zero waste or redundancy, making it highly concise and well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (mutation operations with no annotations and no output schema), the description is incomplete. It lacks information on behavioral traits, error handling, return values, and usage context. While the schema covers parameters well, the overall description fails to provide sufficient context for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear descriptions for both parameters (action with enum values and UUID as required). The description adds no additional parameter semantics beyond what the schema provides, such as UUID format or action-specific behaviors. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 ('start, stop, and restart applications') and identifies the resource ('applications'). It distinguishes from siblings like 'coolify_application_deployments' or 'coolify_service_lifecycle' by focusing on lifecycle operations rather than deployments or service management. However, it doesn't explicitly differentiate from 'coolify_service_lifecycle' which might have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., application must exist), exclusions (e.g., cannot be used for databases), or compare to siblings like 'coolify_service_lifecycle' or 'coolify_database_lifecycle'. Usage is implied by the action names but lacks explicit context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'CRUD operations' implies both read and write capabilities, it doesn't specify authentication requirements, rate limits, side effects (e.g., whether deletions are permanent), or error handling. For a tool with 74 parameters and complex operations, this is a significant gap in behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—a single sentence that efficiently summarizes the tool's scope. It's front-loaded with the core purpose and wastes no words. Every part of the sentence earns its place by clarifying the action types and resource scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the high complexity (74 parameters, multiple action types, no annotations, no output schema), the description is insufficiently complete. It doesn't explain return values, error conditions, or how different actions interact with parameters. For such a multifaceted tool, more contextual information is needed to guide proper usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 74 parameters thoroughly with descriptions and enums. The description adds no parameter-specific information beyond what's in the schema, but since the schema does the heavy lifting, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs CRUD operations (list, create, update, get, delete) on applications, which is a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'coolify_application_lifecycle' or 'coolify_application_deployments' that might handle related application operations, so it doesn't fully distinguish from alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus the many sibling tools listed. There's no mention of prerequisites, alternative tools for specific scenarios, or contextual limitations. The agent must infer usage solely from the tool name and description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the actions (start, stop, restart) but doesn't cover critical aspects like required permissions, side effects (e.g., downtime during stop/restart), error handling, or response format. For a lifecycle management tool with potential destructive operations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded, using a single sentence that efficiently lists all actions and the resource. Every word earns its place, with no redundant or vague language, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of lifecycle management (potentially destructive operations) and the lack of annotations and output schema, the description is incomplete. It doesn't address safety considerations, expected outcomes, or error scenarios, which are crucial for an agent to use this tool correctly in a production environment.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, clearly documenting both parameters (action with enum values and uuid as required). The description adds no additional parameter semantics beyond what's in the schema, such as format details for UUID or action-specific behaviors. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 (start, stop, restart) and resource (databases), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'coolify_application_lifecycle' or 'coolify_service_lifecycle', which likely manage different resource types but share similar lifecycle operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, dependencies, or comparisons to sibling tools (e.g., 'coolify_databases' for listing databases or 'coolify_application_lifecycle' for applications), leaving the agent to infer usage context from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral disclosure. It states the operations but doesn't describe side effects (e.g., delete is irreversible), authentication needs, rate limits, error handling, or response formats. For a multi-action tool with destructive operations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It wastes no words but could be more structured by separating operations or adding brief context. For a multi-action tool, it's appropriately concise though slightly dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (10 parameters, multiple actions including destructive ones), no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects, error cases, or return values. For a CRUD tool with delete/update operations, more context is needed to use it safely and effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, providing detailed parameter documentation. The description adds no additional parameter semantics beyond the schema's action list. It doesn't explain dependencies between parameters (e.g., uuid required for specific actions) or provide usage examples. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'Database CRUD operations' with specific verbs (list, create, get, update, delete) and the resource (databases). It distinguishes from siblings like coolify_database_types or coolify_database_lifecycle by focusing on core database management rather than types or lifecycle states. However, it doesn't explicitly differentiate from all siblings (e.g., coolify_applications also manages resources).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing server/project UUIDs from other tools), when to choose list vs get, or how it relates to siblings like coolify_database_lifecycle for state changes. Usage is implied through the action parameter but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 creation tool but doesn't mention permission requirements, whether it's idempotent, what happens on failure, or typical response format. For a tool with 19 parameters and no output schema, this leaves significant behavioral gaps for the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It wastes no words but could potentially benefit from slightly more context given the tool's complexity. Every word earns its place, though it might be too concise for a tool with 19 parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex creation tool with 19 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what happens after creation, error conditions, or how this tool relates to the broader database management context provided by sibling tools. The agent would struggle to use this effectively without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 19 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'type-specific parameters' and listing the four database types, but doesn't provide additional context about parameter relationships or usage patterns. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Specific database type creation - create PostgreSQL, MySQL, MongoDB, and Redis databases with type-specific parameters.' It specifies the verb ('create') and resources (four database types), but doesn't explicitly differentiate from sibling tools like 'coolify_databases' or 'coolify_database_lifecycle' which might handle other database operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, dependencies, or compare it to sibling tools like 'coolify_databases' (which might list databases) or 'coolify_database_lifecycle' (which might manage existing databases). The agent must infer usage from the name and description alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool is for 'get application logs' but doesn't describe what 'get' entails—e.g., whether it returns real-time or historical logs, if there are rate limits, authentication requirements, or pagination behavior. The mention of 'monitoring' in the description is vague and adds little actionable context, leaving significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two phrases ('Application logs and monitoring' and 'get application logs'), which are front-loaded and to the point. However, 'Application logs and monitoring' is somewhat redundant with 'get application logs', and the monitoring aspect isn't elaborated, slightly reducing efficiency. Overall, it avoids unnecessary verbosity but could be more streamlined.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a logging tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the logs contain (e.g., format, timestamps), how to interpret them, or any limitations (e.g., log retention periods). With siblings like coolify_application_lifecycle that might overlap, more context is needed to ensure the agent can use this tool effectively without confusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for each parameter (action, uuid, lines). The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions (e.g., how lines affects output) or provide examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract from the schema's clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'get application logs', which is a specific verb+resource combination. It distinguishes this tool from siblings like coolify_application_deployments or coolify_application_lifecycle by focusing on logs rather than deployments or lifecycle management. However, it doesn't explicitly differentiate from all siblings (e.g., monitoring aspect isn't clarified versus other tools).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, such as needing an application UUID from another tool like coolify_applications, or specify scenarios where logs are needed (e.g., debugging vs. monitoring). With siblings like coolify_application_lifecycle that might involve logs, the lack of explicit usage context leaves the agent guessing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the four operations (list, create, get, delete), it doesn't explain important behavioral aspects like: what permissions are needed for each action, whether deletions are permanent or reversible, if there are rate limits, what the response format looks like, or any side effects of these operations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise - a single sentence that efficiently communicates the core functionality. It's front-loaded with the main purpose. However, it could be slightly more structured by separating the different action types more clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the relationships between parameters (e.g., which parameters are needed for which actions beyond what the schema indicates), doesn't describe return values or error conditions, and doesn't provide context about how this fits within the broader Coolify ecosystem relative to sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the schema already documents all four parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it just lists the four action types without explaining parameter dependencies or usage patterns. The baseline of 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Project environment management - list, create, get, and delete project environments', which is a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling tools like 'coolify_application_envs' or 'coolify_service_envs', which might handle similar environment operations for different resource types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There are multiple sibling tools with 'envs' in their names (coolify_application_envs, coolify_service_envs), but the description doesn't explain whether this tool is for project-level environments specifically or how it differs from those other environment tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 CRUD operations but lacks behavioral details: it doesn't specify permissions needed, whether deletions are irreversible, rate limits, or what the output looks like (e.g., format of listed projects). This is inadequate for a mutation-heavy 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose (CRUD operations on projects) and enumerates the five actions. Every word earns its place with zero waste, making it easy to scan and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It covers the basic actions but misses critical context: behavioral traits (e.g., destructive effects of delete), usage scenarios, and output expectations. This leaves significant gaps for an agent to operate safely and effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 6 parameters. The description adds no parameter-specific information beyond the high-level action list, which is already covered in the schema's enum description. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'CRUD operations' on 'projects', specifying the five actions (list, create, get, update, delete). It distinguishes the resource (projects) and verbs, but doesn't explicitly differentiate from sibling tools like 'coolify_applications' or 'coolify_servers' that might handle similar operations on different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description lists actions but doesn't indicate context, prerequisites, or exclusions. For example, it doesn't clarify if this is the primary tool for project management or if siblings like 'coolify_project_environments' should be used for specific aspects.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 lists actions but doesn't describe critical traits like authentication requirements, rate limits, side effects (e.g., deletion permanence), or response formats. For a multi-action tool with potential mutations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more structured by separating actions or adding brief context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, multiple actions including mutations) and lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects, error handling, or return values, leaving the agent under-informed for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with each parameter well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify dependencies between parameters). Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Security keys management - list, create, get, update, and delete security keys', which is a specific verb+resource combination. However, it doesn't differentiate this tool from its siblings (like coolify_servers or coolify_services) beyond the security keys domain, missing explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 lists actions but doesn't specify prerequisites, contexts, or exclusions (e.g., when to use this over other security or management tools). This leaves the agent without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 operations like 'validate server connection' and 'list domains/resources', but doesn't describe what these actions entail—e.g., whether validation is a lightweight ping or a full audit, if listing returns all data or is paginated, or if there are rate limits or authentication requirements. For a tool with multiple actions and no annotations, this leaves significant gaps in understanding behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, stating the tool's purpose in a single sentence with three bullet-like actions. There's no wasted text, and it efficiently communicates the scope. However, it could be slightly more structured by explicitly separating the actions or adding brief context, but it remains appropriately sized for its content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple actions, no output schema, no annotations), the description is incomplete. It lacks details on what each action returns, error conditions, or behavioral traits like whether operations are read-only or have side effects. Without annotations or output schema, the description should compensate more by explaining expected outputs or usage constraints, which it doesn't do adequately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear descriptions for both parameters: 'action' with enum values and 'uuid' as required. The description adds minimal value beyond the schema by naming the actions (validate, domains, resources), but doesn't provide additional context like what 'validate' checks or what 'resources' includes. With high schema coverage, the baseline is 3, as the description doesn't significantly enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs server operations and resources with three specific actions: validate server connection, list domains, and list resources. It provides a verb+resource combination that distinguishes it from siblings like coolify_servers (likely listing servers) or coolify_system (broader system operations). However, it doesn't explicitly differentiate from all siblings, such as coolify_logs which might also involve server resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a valid server UUID from another tool like coolify_servers, or clarify when to choose this over siblings like coolify_servers for server-level operations versus coolify_applications for application-level tasks. Usage is implied through action names but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 CRUD operations but doesn't specify authentication requirements, rate limits, side effects (e.g., what happens when deleting a server), or response formats. For a tool with 10 parameters and multiple actions including destructive ones like 'delete,' this leaves significant gaps in understanding how the tool behaves in practice.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—a single sentence that efficiently lists all five actions. It's front-loaded with the core purpose and wastes no words. Every part of the description earns its place by clearly communicating the scope of operations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (10 parameters, multiple actions including destructive ones), lack of annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like authentication, error handling, or what the tool returns. For a CRUD tool with 'delete' action and no structured safety hints, more context is needed to ensure safe and correct usage by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with each parameter well-documented in the schema itself (e.g., action enum values, required conditions for uuid). The description adds no additional parameter semantics beyond stating it handles CRUD operations, which is already implied by the action parameter. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't enhance understanding of parameter usage beyond what's in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'Server CRUD operations - list, create, get, update, and delete servers,' which is a specific verb+resource combination. It distinguishes itself from sibling tools like 'coolify_application_deployments' or 'coolify_projects' by focusing specifically on servers rather than applications, databases, or projects. However, it doesn't explicitly differentiate from 'coolify_server_management' which might have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, when to choose specific actions (like 'list' vs 'get'), or how it relates to sibling tools such as 'coolify_server_management' or other server-related operations. The agent must infer usage solely from the action parameter description in the schema.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While it lists the available actions, it doesn't describe important behavioral traits: what permissions are required, whether operations are destructive (delete action), how changes affect running services, rate limits, or error conditions. For a multi-action tool with destructive operations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in a single sentence that lists all available actions. It's front-loaded with the core purpose and wastes no words. However, it could be slightly more structured by grouping related actions or indicating which are read vs write operations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex multi-action tool with 11 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the tool's scope (service vs application), doesn't provide behavioral context for destructive operations, and offers no guidance on action selection. The agent would struggle to use this tool correctly without trial and error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 11 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, dependencies between action and other parameters, or provide usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Service environment variables management' with specific verbs (list, create, update, bulk update, delete) and resource (environment variables). It distinguishes from sibling tools like 'coolify_application_envs' by specifying 'service' rather than 'application' environment variables, though it doesn't explicitly mention this distinction in the description text itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or when to choose specific actions (like bulk_update vs individual updates). There's no comparison to sibling tools like 'coolify_application_envs' that might handle similar functionality for different resource types.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the actions (start, stop, restart) but doesn't cover critical aspects like required permissions, side effects (e.g., downtime for stop/restart), error handling, or response format. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Service lifecycle management') and lists the specific actions. Every word earns its place with zero waste, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (managing service states, which implies mutations) and lack of annotations or output schema, the description is incomplete. It doesn't address behavioral traits like safety, permissions, or response details, leaving the agent with insufficient context to use it effectively beyond basic parameter input.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for both parameters (action with enum values and uuid as required). The description adds no additional parameter semantics beyond what's in the schema, such as explaining UUID format or action nuances. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Service lifecycle management - start, stop, and restart services', which specifies the verb (manage lifecycle) and resource (services) with concrete actions. However, it doesn't differentiate from sibling tools like 'coolify_application_lifecycle' or 'coolify_database_lifecycle', which likely manage similar lifecycle operations for different resource types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, distinguish it from sibling tools (e.g., 'coolify_application_lifecycle'), or specify contexts like which services are eligible. Usage is implied by the action names but lacks explicit when/when-not instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 CRUD operations but doesn't disclose behavioral traits like authentication requirements, rate limits, side effects, or what happens during deletion. For a multi-action tool with destructive operations, this leaves significant gaps in understanding how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality. It wastes no words but could be slightly more structured by separating the different action types for better readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex multi-action tool with 10 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain return values, error conditions, or behavioral implications of different actions. The agent must rely entirely on the input schema without guidance on how to interpret results or handle different operation types.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the schema already documents all 10 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, provide examples, or clarify edge cases. The baseline of 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'Service CRUD operations' with specific verbs (list, create, get, update, delete) and resource (services). It distinguishes from siblings like coolify_servers or coolify_projects by focusing on services, but doesn't explicitly differentiate from other service-related tools like coolify_service_lifecycle.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With 16 sibling tools including service-specific ones like coolify_service_lifecycle and coolify_service_envs, the description offers no context about use cases, prerequisites, or relationships to other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 'operations' but doesn't disclose whether these are read-only queries or potentially disruptive actions, what permissions are required, rate limits, or what format the information returns. For a system management tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise - a single sentence that efficiently communicates the core functionality. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for a tool with one parameter and clear scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with 100% schema coverage but no annotations or output schema, the description provides adequate but minimal context. It covers what the tool does but lacks behavioral details (permissions, side effects) and doesn't explain what information each action returns. Given the simplicity of the tool, this is minimally viable but has clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'action' fully documented in the schema with enum values and descriptions. The description mentions the three operations (health, version, info) but adds no additional semantic context beyond what the schema already provides. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'System management operations' with specific functions listed (health check, version, system information). It distinguishes from siblings by focusing on system-level operations rather than application/database/project management. However, it doesn't explicitly contrast with 'coolify_server_management' which might have overlapping scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'coolify_server_management' that might handle similar system operations, there's no indication of scope boundaries or prerequisites. The description only lists what the tool does, not when it's appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 actions but doesn't describe behavioral traits such as required permissions, rate limits, response formats, or whether operations are read-only or mutative. For a tool with multiple actions, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that lists all key actions without unnecessary words. It's front-loaded with the main purpose ('Complete team management') and structured clearly. However, it could be slightly more polished by using bullet points or clearer formatting for the actions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple actions), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects, usage context, or return values, leaving gaps that could hinder an AI agent's ability to use the tool effectively in a broader context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with clear descriptions for both parameters (action and team_id). The description doesn't add any additional semantic context beyond what's in the schema, such as examples or edge cases. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Complete team management' and enumerates four specific actions (list teams, get current team, get team details, list team members), providing a comprehensive overview. However, it doesn't explicitly differentiate this team management tool from sibling tools like coolify_projects or coolify_servers, 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.

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 lists actions but doesn't specify prerequisites, contexts, or comparisons to sibling tools (e.g., when to use coolify_teams vs. coolify_projects for related data). This lack of usage context limits its effectiveness for an AI agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.