The Ansible MCP Server enables AI assistants to manage infrastructure as code with the following capabilities:
Ansible Operations:
Run playbooks with customizable parameters (inventory, extra vars, tags, limits)
List inventory hosts and groups
Check playbook syntax
Preview playbook tasks
Execute ad-hoc commands
Encrypt/decrypt with Ansible Vault
Create dynamic AWS inventory
AWS Management:
EC2 instances (list, create, start, stop, terminate)
S3 buckets and objects
VPC networks
CloudFormation stacks
IAM roles and policies
RDS database instances
Route53 DNS records and zones
Elastic Load Balancers
Lambda functions
Terraform Support:
Execute commands (init, plan, apply, destroy, output)
LocalStack Integration:
Test AWS operations locally without real credentials
Allows AI assistants to execute Ansible playbooks, view and manage inventory, validate playbook syntax, and preview tasks that would be executed by a playbook.
Serves as the runtime environment for the MCP server, allowing the Ansible integration to operate.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Ansible MCP Server check the syntax of my webserver playbook"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server for Infrastructure as Code operations. This server allows AI assistants to interact with Ansible and Terraform, execute playbooks and Terraform plans, manage cloud resources, and perform other infrastructure operations directly.
(Project previously known as mcp-ansible)
All code in demos generated using Claude 3.7 Sonnet (via OpenRouter), Cline, and SysOperator
AWS LAMP Stack - All Ansible code to deploy example LAMP stack in AWS
AWS Terraform LAMP - Terraform and Ansible code to reply a LAMP stack
Related MCP server: AAP MCP Server
Run Ansible Playbooks: Execute Ansible playbooks with support for parameters like inventory, extra vars, tags, and limits
List Inventory: View hosts and groups from an Ansible inventory file
Check Syntax: Validate Ansible playbook syntax without execution
List Tasks: Preview tasks that would be executed by a playbook
Access Default Inventory: Access the default Ansible inventory file via resource API
AWS Integration: Manage AWS resources (EC2, S3, VPC, CloudFormation, etc.)
Terraform Support: Execute Terraform commands (init, plan, apply, destroy, output, etc.)
tflocal Integration: Test Terraform configurations with LocalStack for local cloud development
LocalStack Support: Test AWS operations locally using LocalStack without real AWS credentials
Node.js 18 or higher
npm or yarn
Ansible installed and in PATH
@modelcontextprotocol/sdk (installed automatically)
For AWS operations: AWS CLI and valid credentials
For LocalStack: LocalStack installed and running, awslocal CLI
git clone https://github.com/tarnover/mcp-sysoperator.git
cd mcp-sysoperatornpm installnpm run buildAdd the Ansible MCP server to your MCP settings configuration file.
For VSCode with Claude extension:
Edit the file at ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
For Claude Desktop app:
macOS: Edit ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: Edit %APPDATA%\Claude\claude_desktop_config.json
Linux: Edit ~/.config/Claude/claude_desktop_config.json
Add the following to the mcpServers section:
{
"mcpServers": {
"sysoperator": {
"command": "node",
"args": ["/absolute/path/to/mcp-sysoperator/build/index.js"],
"env": {}
}
}
}Make sure to replace /absolute/path/to/mcp-sysoperator with the actual path to your installation.
Once installed and configured, the MCP server provides the following tools to the AI assistant:
<use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>run_playbook</tool_name>
<arguments>
{
"playbook": "/path/to/your/playbook.yml",
"inventory": "/path/to/inventory.ini",
"extraVars": {
"var1": "value1",
"var2": "value2"
},
"tags": "setup,configure",
"limit": "webservers"
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>list_inventory</tool_name>
<arguments>
{
"inventory": "/path/to/inventory.ini"
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>check_syntax</tool_name>
<arguments>
{
"playbook": "/path/to/your/playbook.yml"
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>list_tasks</tool_name>
<arguments>
{
"playbook": "/path/to/your/playbook.yml"
}
</arguments>
</use_mcp_tool><access_mcp_resource>
<server_name>sysoperator</server_name>
<uri>sysoperator://inventory/default</uri>
</access_mcp_resource><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>aws_s3</tool_name>
<arguments>
{
"action": "list_buckets",
"region": "us-east-1"
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>terraform</tool_name>
<arguments>
{
"action": "init",
"workingDir": "/path/to/terraform/project"
}
</arguments>
</use_mcp_tool>
<use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>terraform</tool_name>
<arguments>
{
"action": "plan",
"workingDir": "/path/to/terraform/project",
"vars": {
"instance_type": "t2.micro",
"region": "us-west-2"
}
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>terraform</tool_name>
<arguments>
{
"action": "apply",
"workingDir": "/path/to/terraform/project",
"autoApprove": true,
"vars": {
"instance_type": "t2.micro",
"region": "us-west-2"
}
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>sysoperator</server_name>
<tool_name>terraform</tool_name>
<arguments>
{
"action": "apply",
"workingDir": "/path/to/terraform/project",
"useLocalstack": true,
"autoApprove": true,
"vars": {
"instance_type": "t2.micro",
"region": "us-west-2"
}
}
</arguments>
</use_mcp_tool>This project includes integration with LocalStack for testing AWS operations locally without real AWS credentials. The LocalStack integration allows you to:
Test Ansible playbooks that use AWS services locally
Develop and test AWS operations without incurring AWS costs
Run tests without requiring real AWS credentials
Validate your infrastructure code before deploying to real AWS
See the LocalStack README for detailed instructions on using the LocalStack integration.
Quick start:
# Install LocalStack and awslocal CLI
pip install localstack awscli-local
# Start LocalStack
localstack start
# Run the sample playbook
node localstack/run_sample_playbook.mjsmcp-sysoperator/
├── src/
│ ├── index.ts # Main entry point
│ └── ansible-mcp-server/ # Will be renamed in filesystem in future updates
│ ├── index.ts # MCP SysOperator server implementation
│ ├── common/ # Common utilities and types
│ │ ├── errors.ts # Error definitions
│ │ ├── types.ts # Type and schema definitions
│ │ ├── utils.ts # Utility functions
│ │ └── version.ts # Version information
│ └── operations/ # Operation handlers
│ ├── ad_hoc.ts # Ansible ad-hoc commands
│ ├── aws.ts # AWS operations
│ ├── inventory.ts # Ansible inventory operations
│ ├── playbooks.ts # Ansible playbook operations
│ ├── terraform.ts # Terraform operations
│ └── vault.ts # Ansible vault operations
├── localstack/ # LocalStack integration
│ ├── README.md # LocalStack documentation
│ ├── sample_playbook.yml # Sample playbook for LocalStack
│ ├── inventory.ini # Sample inventory for LocalStack
│ ├── run_sample_playbook.mjs # Script to run sample playbook
│ └── utils.localstack.ts # Modified utils for LocalStack
├── package.json # Project configuration and dependencies
├── tsconfig.json # TypeScript configuration
└── README.md # DocumentationTo add new capabilities to the MCP server:
Modify src/ansible-mcp-server/index.ts (future: src/sysoperator/index.ts)
Add your new tool in the setupToolHandlers method
Implement a handler function for your tool in the appropriate operations file
Add the schema definition in common/types.ts
Rebuild with npm run build
SysOperator is currently in active development and undergoing extensive testing. It is not recommended for use in production environments at this time. The software may experience breaking changes, incomplete features, or unexpected behavior.
Use at your own risk.
MIT License - See LICENSE for details
Manage AWS CloudFormation stacks
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| capabilities | No | ||
| parameters | No | ||
| region | Yes | ||
| stackName | No | ||
| tags | No | ||
| templateBody | No | ||
| templateUrl | No |
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. 'Manage' implies both read and write operations, but there's no information about permissions required, whether operations are destructive, rate limits, error handling, or what 'manage' actually does behaviorally. The description doesn't explain what happens during create/update/delete actions or any 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary elaboration. While this conciseness comes at the cost of completeness, the structure itself is optimal for its length.
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 tool with 8 parameters, 0% schema coverage, no annotations, and no output schema, the description is severely incomplete. It doesn't provide enough information for an agent to understand what the tool actually does, how to use it properly, or what to expect from it. The three-word description is inadequate given the tool's complexity and lack of supporting documentation.
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 0% schema description coverage for 8 parameters, the description provides no parameter semantics whatsoever. It doesn't explain what 'action' values mean, what 'capabilities' are for, how 'parameters' and 'tags' should be structured, or the relationship between 'templateBody' and 'templateUrl'. The description fails to compensate for the complete lack of schema documentation.
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 'Manage AWS CloudFormation stacks' states the general purpose (verb+resource) but is vague about what 'manage' entails. It doesn't distinguish this tool from its many AWS siblings (like aws_ec2, aws_s3) beyond mentioning CloudFormation specifically. The description is functional but lacks specificity about the scope of management 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?
No guidance is provided on when to use this tool versus alternatives. There's no mention of when to choose CloudFormation over sibling tools like terraform or run_playbook, nor any context about prerequisites or typical use cases. The description offers no usage boundaries or comparison with other infrastructure-as-code options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Create AWS dynamic inventory
| Name | Required | Description | Default |
|---|---|---|---|
| compose | No | ||
| filters | No | ||
| hostnames | No | ||
| keyed_groups | No | ||
| region | Yes |
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. 'Create' implies a write/mutation operation, but the description provides no information about authentication requirements, rate limits, side effects, what happens if inventory already exists, or what the tool actually produces. No behavioral traits beyond the basic 'create' action are disclosed.
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 at just three words. While this represents under-specification rather than ideal conciseness, within the scoring framework for this dimension, it's front-loaded with the core action and wastes no words. Every word earns its place, even if more content is needed.
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 (5 parameters with nested objects, no annotations, no output schema), the description is completely inadequate. A 'create' operation with multiple complex parameters requires explanation of what's being created, how parameters interact, what authentication is needed, and what the result looks like. The three-word description provides none of this necessary 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?
With 0% schema description coverage for 5 parameters (region, compose, filters, hostnames, keyed_groups), the description provides no parameter information whatsoever. The schema shows complex nested objects and arrays, but the description doesn't explain what these parameters mean, how they interact, or what values are expected. The description fails to compensate for the complete lack of schema documentation.
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 states the tool 'Create AWS dynamic inventory' which provides a basic verb+resource combination. However, it's vague about what 'dynamic inventory' specifically means in this context and doesn't differentiate from sibling tools like 'list_inventory' or 'aws_ec2' which might have related functionality. The purpose is understandable but lacks specificity about what type of inventory or what makes it 'dynamic'.
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 multiple AWS-related sibling tools (aws_ec2, aws_cloudformation, etc.) and inventory-related tools (list_inventory), there's no indication of when this specific dynamic inventory creation tool is appropriate versus other inventory or AWS management tools. No context, prerequisites, or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS EC2 instances (list, create, start, stop, terminate)
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| count | No | ||
| filters | No | ||
| imageId | No | ||
| instanceIds | No | ||
| instanceType | No | ||
| keyName | No | ||
| region | Yes | ||
| securityGroups | No | ||
| tags | No | ||
| terminationProtection | No | ||
| userData | No | ||
| waitForCompletion | No |
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 but offers minimal information. It lists actions but doesn't describe permissions needed, cost implications, destructive nature of operations like terminate, or response formats. For a tool with 13 parameters and no annotation coverage, this is a significant gap in transparency about 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 extremely concise with a single, efficient sentence that lists all key actions. It's front-loaded with the core purpose and wastes no words. Every element (manage, AWS EC2 instances, action list) earns its place without redundancy.
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 (13 parameters, multiple actions including destructive ones like terminate, no annotations, no output schema), the description is incomplete. It doesn't address critical context like authentication requirements, error handling, or what information is returned. For a multi-action cloud management tool, this minimal description leaves too many gaps for 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 0%, meaning none of the 13 parameters have descriptions in the schema. The tool description provides no information about parameters beyond implying some actions (like create) might use parameters like imageId or instanceType. It doesn't explain what parameters are needed for which actions, their formats, or constraints, failing to compensate for the complete lack of schema documentation.
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 managing AWS EC2 instances with specific verbs (list, create, start, stop, terminate). It distinguishes from sibling tools by focusing on EC2 instances rather than other AWS services like S3 or Lambda, though it doesn't explicitly contrast with them. The description goes beyond tautology by specifying the resource (AWS EC2 instances) and actions.
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, context for choosing between actions, or comparisons with sibling tools like aws_cloudformation or terraform that might also manage infrastructure. Usage is implied through the listed actions but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS Elastic Load Balancers
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| healthCheck | No | ||
| lbType | No | application | |
| listeners | No | ||
| name | No | ||
| region | Yes | ||
| scheme | No | ||
| securityGroups | No | ||
| subnets | No | ||
| tags | No | ||
| targetGroups | No |
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. 'Manage' implies mutation capabilities (create/delete) and read operations (list), but it doesn't disclose critical behavioral traits such as authentication requirements, rate limits, destructive effects of 'delete', or response formats. For a tool with 11 parameters and no 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 extremely concise with a single sentence, 'Manage AWS Elastic Load Balancers', which is front-loaded and wastes no words. It efficiently states the tool's scope without unnecessary elaboration, earning a high score for brevity and clarity in structure.
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 (11 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't provide enough context for an AI agent to understand how to invoke the tool correctly, such as explaining parameter dependencies, action-specific requirements, or expected outcomes. For a multi-action tool with significant input complexity, this is inadequate.
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 0%, meaning none of the 11 parameters have descriptions in the schema. The tool description adds no meaning beyond the schema—it doesn't explain what parameters like 'healthCheck', 'listeners', or 'targetGroups' are for, their formats, or how they relate to actions. With low coverage and no compensation in the description, this falls short of the baseline.
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 'Manage AWS Elastic Load Balancers' states the resource (AWS Elastic Load Balancers) and a general verb ('Manage'), but it's vague about what specific operations are included. It doesn't distinguish from sibling tools like aws_ec2 or aws_vpc, which also manage AWS resources. The purpose is clear at a high level but lacks specificity about the CRUD operations available.
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, context for choosing between 'list', 'create', or 'delete' actions, or how it differs from other AWS tools in the sibling list. Without such guidance, users must infer usage from the input schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS IAM roles and policies
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| assumeRolePolicyDocument | No | ||
| managedPolicies | No | ||
| name | No | ||
| path | No | ||
| policyDocument | No | ||
| policyName | No | ||
| region | Yes | ||
| roleName | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Manage' implies both read and write operations, but it doesn't specify permissions required, rate limits, side effects (e.g., deletions), or response formats. For a tool with 9 parameters and no 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 with no wasted words. It's appropriately sized and front-loaded, making it easy to scan. Every word contributes to the core message, though the message itself is under-specified.
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 (9 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain parameters, return values, or behavioral traits. For a multi-action tool handling sensitive IAM operations, this minimal description leaves critical gaps in understanding how to use it 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 0%, so the description must compensate for undocumented parameters. It mentions 'roles and policies' but doesn't explain any of the 9 parameters (e.g., action, region, name). The description adds no meaningful semantics beyond what's inferred from the tool name, failing to address the coverage gap.
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 'Manage AWS IAM roles and policies' states a general purpose but lacks specificity. It mentions the resource (AWS IAM roles and policies) and a vague verb ('manage'), but doesn't distinguish from sibling AWS tools or specify what management operations are available. This is better than a tautology but remains vague about the exact 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 sibling tools like aws_cloudformation or aws_lambda, nor does it specify prerequisites, exclusions, or appropriate contexts for IAM management. Usage is implied only by the tool name and description, with no explicit instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS Lambda functions
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| description | No | ||
| environment | No | ||
| functionCode | No | ||
| handler | No | ||
| memorySize | No | ||
| name | No | ||
| payload | No | ||
| region | Yes | ||
| role | No | ||
| runtime | No | ||
| s3Bucket | No | ||
| s3Key | No | ||
| tags | No | ||
| timeout | No | ||
| zipFile | No |
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 but offers minimal information. 'Manage' implies mutation capabilities, but it doesn't specify authentication requirements, rate limits, error handling, or side effects. The description fails to disclose critical behavioral traits like whether operations are idempotent, what permissions are needed, or how errors are returned.
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 at just three words, which is appropriate for its length. However, this conciseness comes at the cost of being under-specified for such a complex tool with 16 parameters. While front-loaded, it lacks the necessary detail that would justify its brevity for a multi-action management tool.
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 tool with 16 parameters, 0% schema description coverage, no annotations, no output schema, and multiple possible actions, the description is completely inadequate. It provides no information about return values, error conditions, authentication requirements, or how different actions behave. The agent would struggle to use this tool correctly without extensive 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 0%, meaning none of the 16 parameters have descriptions in the schema. The tool description provides no parameter information whatsoever - it doesn't mention the 'action' parameter with its enum values, required 'region', or any of the other 14 parameters. This leaves the agent completely dependent on parameter names alone to guess functionality.
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 'Manage AWS Lambda functions' states a general purpose but is vague about what management entails. It distinguishes from sibling tools by specifying AWS Lambda, but doesn't clarify the specific actions available (list, create, update, delete, invoke) which are only visible in the schema. The description lacks the specificity needed for an agent to understand the tool's exact capabilities.
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 doesn't mention prerequisites, appropriate contexts, or compare it to sibling AWS tools like aws_cloudformation or terraform. An agent must infer usage solely from the tool name and parameter schema without any contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS RDS database instances
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| allocatedStorage | No | ||
| backupRetentionPeriod | No | ||
| dbEngine | No | ||
| dbInstanceClass | No | ||
| dbInstanceIdentifier | No | ||
| dbSubnetGroupName | No | ||
| masterPassword | No | ||
| masterUsername | No | ||
| multiAZ | No | ||
| region | Yes | ||
| skipFinalSnapshot | No | ||
| tags | No | ||
| vpcSecurityGroupIds | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. 'Manage' implies mutation capabilities, but it doesn't disclose critical traits like authentication requirements, potential costs of create/delete actions, rate limits, or that actions like 'delete' might be irreversible. It lacks context on what 'manage' entails operationally.
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 with no wasted words. It's appropriately sized for a high-level summary, though it lacks detail. The structure is front-loaded with the core purpose.
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 tool with 14 parameters, no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain the tool's scope, parameter meanings, behavioral expectations, or output format, leaving significant gaps for an AI agent to understand and use the tool correctly.
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 description provides no parameter information, while the schema has 14 parameters with 0% description coverage. Parameters like 'action', 'region', 'dbInstanceIdentifier', and 'masterPassword' are undocumented in both schema and description, leaving their purposes and formats unclear. The description fails to compensate for the schema's lack of documentation.
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 'Manage AWS RDS database instances' states the general purpose (managing RDS instances) but is vague about what 'manage' entails. It doesn't specify the specific actions available (list, create, delete, start, stop) or distinguish this tool from sibling AWS tools like aws_ec2 or aws_s3 beyond mentioning RDS.
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 doesn't mention prerequisites (e.g., AWS credentials), compare to sibling tools (e.g., aws_cloudformation for infrastructure as code), or specify appropriate contexts for different actions like 'create' versus 'list'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS Route53 DNS records and zones
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| comment | No | ||
| recordName | No | ||
| recordState | No | ||
| recordTtl | No | ||
| recordType | No | ||
| recordValue | No | ||
| region | Yes | ||
| zoneId | No | ||
| zoneName | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool 'manages' DNS records and zones, implying both read and write operations, but doesn't specify permissions required, rate limits, whether deletions are permanent, or what the response format looks like. This is inadequate for a tool with multiple mutation actions like create and delete.
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 at just 7 words, front-loading the core purpose with zero wasted words. Every element ('Manage AWS Route53 DNS records and zones') directly communicates essential information without redundancy.
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 tool with 10 parameters, multiple mutation actions, no annotations, and no output schema, the description is severely incomplete. It doesn't address authentication requirements, error conditions, return formats, or the scope of operations. The agent would struggle to use this tool effectively based solely on this description.
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 0% schema description coverage for 10 parameters, the description provides no information about parameters beyond what's implied by the tool name. It doesn't explain what 'action' values do, what 'recordState' means, or how parameters interact. The description fails to compensate for the complete lack of schema documentation.
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 managing AWS Route53 DNS records and zones, providing specific verbs (manage) and resources (DNS records and zones). However, it doesn't differentiate this tool from its sibling AWS tools (like aws_ec2, aws_s3) beyond the Route53 service focus, which is why it doesn't reach 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 doesn't mention when to choose aws_route53 over other AWS tools or non-AWS DNS management options, nor does it specify any prerequisites or contextual constraints for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS S3 buckets and objects
| Name | Required | Description | Default |
|---|---|---|---|
| acl | No | ||
| action | Yes | ||
| bucket | No | ||
| contentType | No | ||
| localPath | No | ||
| metadata | No | ||
| objectKey | No | ||
| region | Yes | ||
| tags | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Manage' implies both read and write operations, but it doesn't specify destructive actions (e.g., delete_bucket), authentication requirements, rate limits, error handling, or response formats. For a multi-action tool with potential mutations, this lack of detail is inadequate and fails to inform the agent about critical 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single phrase, 'Manage AWS S3 buckets and objects', which is front-loaded and wastes no words. It efficiently states the domain and high-level purpose without unnecessary elaboration, 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 high complexity (9 parameters, multiple actions including mutations, no annotations, no output schema), the description is severely incomplete. It doesn't cover behavioral aspects, parameter meanings, usage contexts, or return values. For a tool that handles diverse S3 operations, this minimal description fails to provide the necessary context for an agent to use it 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 0%, meaning no parameters are documented in the schema. The description adds no parameter semantics beyond the tool name—it doesn't explain what 'action', 'bucket', 'objectKey', or other parameters mean, their relationships, or how they map to S3 operations. With 9 parameters and zero coverage, the description fails to compensate, leaving parameters largely unexplained.
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 'Manage AWS S3 buckets and objects' states the general domain (AWS S3) and high-level purpose (manage), but it's vague about what specific actions are available. It doesn't specify verbs like list, create, delete, upload, or download, which are revealed in the action parameter enum. It distinguishes from siblings by mentioning S3 specifically, but lacks precision about the tool's functional 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. It doesn't mention prerequisites (e.g., AWS credentials), differentiate from other AWS tools (e.g., aws_ec2 for compute), or specify contexts like file operations versus bucket management. Usage is implied only by the tool name, with no explicit when/when-not statements or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage AWS VPC networks
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| cidrBlock | No | ||
| dnsHostnames | No | ||
| dnsSupport | No | ||
| name | No | ||
| region | Yes | ||
| subnets | No | ||
| tags | No | ||
| vpcId | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Manage' implies both read and write operations, but the description doesn't disclose behavioral traits like authentication requirements, rate limits, destructive consequences of delete actions, or what happens when creating VPCs with specific configurations. The description is too generic to provide meaningful 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 at just three words. It's front-loaded with the essential information (verb and resource) with zero wasted words. While under-specified, it's structurally efficient.
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 tool with 9 parameters, nested objects, no output schema, and no annotations, the description is inadequate. It doesn't explain the tool's scope, behavior, parameter usage, or expected outcomes. The agent would struggle to use this tool correctly without significant trial and error or external knowledge.
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 0% schema description coverage for 9 parameters, the description provides no parameter information beyond what's in the schema. It doesn't explain what 'action' values do, what 'cidrBlock' represents, how 'subnets' array should be structured, or any parameter relationships. The description fails to compensate for the complete lack of schema descriptions.
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 'Manage AWS VPC networks' states a general purpose (verb+resource) but is vague about what management entails. It doesn't specify the CRUD operations available or distinguish this from sibling AWS tools like aws_ec2 or aws_cloudformation that might also manage network-related 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 on when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or exclusions. With many sibling AWS tools, there's no indication of when aws_vpc is the right choice versus other infrastructure management tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check syntax of an Ansible playbook without executing it
| Name | Required | Description | Default |
|---|---|---|---|
| playbook | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states this is a non-execution check, which is valuable behavioral context. However, it doesn't mention error handling, output format, or any limitations like maximum playbook size or supported Ansible versions.
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 with zero wasted words. It's front-loaded with the core purpose and includes the critical constraint. Every word earns its place in this concise formulation.
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 no annotations and no output schema, the description provides adequate basic context about purpose and behavior. However, it lacks details about what the check actually validates, what output to expect, or any error conditions - gaps that become more significant given the absence of structured documentation.
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 0% schema description coverage and only one parameter, the description implies the parameter is an Ansible playbook content string, which adds meaningful context beyond the bare schema. However, it doesn't specify format expectations (YAML string, file path, etc.) or validation details.
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 specific action ('Check syntax') and resource ('Ansible playbook'), with the important constraint 'without executing it' that distinguishes it from execution tools. It's precise and unambiguous about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context - checking syntax before execution - but doesn't explicitly state when to use this tool versus alternatives like 'run_playbook' or other sibling tools. It provides clear context but lacks explicit guidance on alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List Ansible inventory hosts and groups
| Name | Required | Description | Default |
|---|---|---|---|
| inventory | No |
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 'List' implies a read-only operation, the description doesn't specify whether this requires specific permissions, what format the output takes (structured data vs plain text), whether it supports pagination, or how it handles errors. For a 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 extremely concise at just 6 words, front-loading the essential information with zero wasted words. Every word earns its place by specifying the action ('List'), domain ('Ansible inventory'), and targets ('hosts and groups').
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 lack of annotations, 0% schema description coverage, no output schema, and the presence of potentially overlapping sibling tools, the description is insufficiently complete. It doesn't explain the tool's relationship to other inventory-related tools, provide parameter guidance, or describe what the output looks like, leaving too many contextual gaps for effective tool selection and 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?
The schema has 0% description coverage for its single parameter 'inventory', and the tool description provides no information about what this parameter represents, what values it accepts, or whether it's required. With low schema coverage and no parameter explanation in the description, users must guess what 'inventory' means in this context.
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 verb ('List') and resource ('Ansible inventory hosts and groups'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling inventory tools like 'aws_dynamic_inventory' or explain what distinguishes 'list_inventory' from other listing operations in the Ansible context.
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 sibling tools like 'aws_dynamic_inventory' and 'aws_ec2' that might also provide inventory-related functionality, there's no indication of when this specific Ansible inventory tool is appropriate versus AWS-specific inventory tools or other operations like 'list_tasks'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all tasks that would be executed by a playbook
| Name | Required | Description | Default |
|---|---|---|---|
| playbook | Yes |
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 lists tasks but doesn't disclose behavioral traits like whether it's a read-only operation, what format the output takes, if there are rate limits, or if it requires specific permissions. The description is minimal and lacks essential context for safe and effective use.
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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand quickly. Every word earns its place.
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 listing tasks (which may involve parsing playbooks) and the lack of annotations, output schema, and poor schema coverage, the description is incomplete. It doesn't explain what 'tasks' entail, how they're formatted, or any dependencies, leaving significant gaps for an AI agent to use the tool correctly.
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 1 parameter with 0% description coverage, so the schema provides no semantic information. The description mentions 'playbook' but doesn't explain what this parameter represents, such as a playbook name or file path, or provide examples. It adds minimal value beyond the schema's structure.
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 verb ('List') and resource ('tasks'), specifying that these are tasks 'executed by a playbook'. It distinguishes from siblings like 'run_playbook' or 'run_ad_hoc' by focusing on listing rather than execution. However, it doesn't explicitly differentiate from 'list_inventory', which might list 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a valid playbook name, or compare it to siblings like 'check_syntax' for validation or 'run_playbook' for execution. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run an Ansible ad-hoc command against specified hosts
| Name | Required | Description | Default |
|---|---|---|---|
| args | No | ||
| become | No | ||
| extra_vars | No | ||
| inventory | No | ||
| module | No | shell | |
| pattern | Yes |
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 running commands against hosts, implying execution and potential system changes, but fails to detail critical aspects like permissions needed, side effects, error handling, or output format, leaving significant gaps for a tool with 6 parameters.
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 with no wasted words, making it highly concise and front-loaded. Every part contributes directly to stating the tool's function, though this brevity comes at the cost of detail.
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, no output schema, no annotations), the description is incomplete. It doesn't cover parameter meanings, behavioral traits, or usage context, making it inadequate for an agent to reliably invoke this tool without additional guesswork or external knowledge.
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 0%, so the description must compensate for undocumented parameters. It only vaguely references 'specified hosts' (hinting at 'pattern' or 'inventory'), but doesn't explain any of the 6 parameters (e.g., 'args', 'become', 'extra_vars'), their purposes, or how they interact, failing to add meaningful semantic value beyond the bare 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 verb ('Run') and resource ('Ansible ad-hoc command against specified hosts'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'run_playbook' or 'list_tasks', which are related Ansible operations, so it misses full sibling distinction.
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 'run_playbook' for playbooks or 'list_tasks' for task listing. It lacks context on prerequisites, exclusions, or specific scenarios, offering only a basic statement of function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run an Ansible playbook
| Name | Required | Description | Default |
|---|---|---|---|
| extraVars | No | ||
| inventory | No | ||
| limit | No | ||
| playbook | Yes | ||
| tags | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action without detailing execution behavior, such as whether it's synchronous/asynchronous, error handling, or output format. This is inadequate for a tool that likely performs complex 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 extremely concise with a single sentence, 'Run an Ansible playbook', which is front-loaded and wastes no words. It efficiently communicates the core purpose without unnecessary elaboration.
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 running Ansible playbooks, 5 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on execution behavior, parameter usage, and expected outcomes, making it insufficient for effective tool 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 0%, so the description must compensate by explaining parameters. It adds no meaning beyond the schema, failing to clarify what parameters like 'extraVars', 'inventory', or 'limit' do or how they affect playbook execution, leaving significant gaps.
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 states the tool's purpose as 'Run an Ansible playbook', which clearly indicates the action (run) and resource (Ansible playbook). However, it doesn't distinguish this tool from its sibling 'run_ad_hoc', which also performs Ansible operations, making the purpose somewhat vague in context.
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 sibling tools like 'run_ad_hoc' or 'check_syntax', nor does it specify contexts or prerequisites for running playbooks, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Execute Terraform commands (init, plan, apply, destroy, validate, output, etc.)
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| autoApprove | No | ||
| backendConfig | No | ||
| lockTimeout | No | ||
| refresh | No | ||
| state | No | ||
| target | No | ||
| useLocalstack | No | ||
| varFiles | No | ||
| vars | No | ||
| workingDir | Yes | ||
| workspace | No |
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 'Execute Terraform commands' which implies mutation capabilities (apply, destroy), but doesn't warn about destructive operations, authentication requirements, state management implications, or error handling. For a tool with potentially destructive actions like 'destroy', 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 extremely concise - a single sentence that efficiently communicates the core functionality. It's front-loaded with the main purpose and includes helpful examples. Every word earns its place with no redundancy.
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 tool with 12 parameters, no annotations, no output schema, and 0% schema description coverage, the description is severely incomplete. It doesn't address Terraform's state management, authentication, destructive operations, or parameter usage. The agent would struggle to use this tool correctly without significant external knowledge.
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 0% schema description coverage for 12 parameters, the description provides no information about any parameters. It doesn't explain what 'action' does, what 'workingDir' represents, or the purpose of other parameters like 'autoApprove', 'backendConfig', or 'target'. The description fails to compensate for the complete lack of schema documentation.
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 verb ('Execute') and resource ('Terraform commands') with specific examples of commands (init, plan, apply, etc.). It distinguishes from sibling tools by focusing on Terraform rather than AWS or other infrastructure tools, though it doesn't explicitly differentiate from all siblings.
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 like AWS CloudFormation or other infrastructure-as-code approaches. The description only lists what commands can be executed without context about appropriate use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Decrypt a string encrypted with Ansible Vault
| Name | Required | Description | Default |
|---|---|---|---|
| string | Yes | ||
| vault_id | No | ||
| vault_password_file | No |
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 action ('decrypt') but doesn't describe what happens on success (e.g., returns plaintext), failure modes, authentication needs (implied by vault parameters), or side effects. This is inadequate for a tool with parameters and 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 with zero waste, front-loading the core purpose. It's appropriately sized for a straightforward tool, making every word count without unnecessary elaboration.
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 no annotations, 0% schema coverage, no output schema, and three parameters, the description is incomplete. It doesn't cover parameter meanings, return values, or behavioral details, leaving significant gaps for a decryption tool that likely involves security-sensitive operations.
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 0%, so the description must compensate for undocumented parameters. It mentions 'encrypted with Ansible Vault' for the 'string' parameter but doesn't explain 'vault_id' or 'vault_password_file', leaving two of three parameters without semantic context. The description adds minimal value beyond 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 verb ('decrypt') and resource ('a string encrypted with Ansible Vault'), providing a specific purpose. However, it doesn't explicitly distinguish from its sibling 'vault_encrypt_string' beyond the obvious encryption/decryption distinction, missing nuanced 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?
No guidance is provided on when to use this tool versus alternatives or in what context. The description lacks any mention of prerequisites, such as having an encrypted string from Ansible Vault, or exclusions, leaving usage entirely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Encrypt a string using Ansible Vault
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| string | Yes | ||
| vault_id | No | ||
| vault_password_file | No |
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 'encrypt' implies a write/mutation operation, the description doesn't disclose important behavioral traits: whether this requires specific permissions, what happens to the original unencrypted string, whether the encryption is reversible only via the sibling tool, what format the output takes, or any rate limits. It mentions the technology (Ansible Vault) but not how it 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 extremely concise at just 6 words, with zero wasted language. Every word earns its place: 'Encrypt' specifies the action, 'a string' specifies the target, and 'using Ansible Vault' specifies the technology. It's perfectly front-loaded with the core purpose.
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 a 4-parameter tool with no annotations, 0% schema description coverage, and no output schema, the description is inadequate. For an encryption tool that presumably produces important output, the description should explain what the tool returns, what the parameters mean, and any behavioral constraints. The current description leaves too many unanswered questions for effective tool selection and 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?
With 0% schema description coverage and 4 parameters (only 1 required), the description provides no information about any parameters. It doesn't explain what 'name', 'vault_id', or 'vault_password_file' mean, nor does it clarify the semantics of the required 'string' parameter. The description fails to compensate for the complete lack of schema documentation.
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 action ('encrypt') and target resource ('a string using Ansible Vault'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'vault_decrypt_string' beyond the obvious encryption vs. decryption difference, nor does it explain what makes this tool unique among other encryption-related tools that might exist.
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 (like needing Ansible Vault configured), when encryption is appropriate, or what scenarios warrant using this specific tool over other encryption methods. The sibling tool 'vault_decrypt_string' is clearly related, but no explicit comparison is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Most tools are clearly distinct by AWS service or Ansible function, with minimal overlap. However, aws_ec2's broad scope (list, create, start, stop, terminate) could be confused with more specific AWS tools, and terraform seems out of place in an Ansible-focused server, creating some ambiguity.
Tools follow a consistent snake_case pattern throughout, with clear verb_noun structures (e.g., run_playbook, list_inventory). The main deviation is the terraform tool, which lacks a verb prefix, slightly breaking the pattern.
With 18 tools, the count is borderline high for an Ansible server, especially since it includes AWS-specific tools that might be better scoped separately. It feels slightly heavy, but still manageable given the domain coverage.
The toolset covers core Ansible operations (syntax checking, inventory, tasks, ad-hoc commands, playbooks, vault) and extensive AWS management, but lacks tools for other cloud providers or non-AWS infrastructure, which could be gaps for broader automation needs.
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