The IaC Memory MCP Server is a persistent memory storage system for Infrastructure-as-Code (IaC) components that enables version tracking, relationship mapping, and resource management for Terraform and Ansible.
Key capabilities:
Terraform Management: Store and retrieve provider/resource information, track version history, check cross-version compatibility, and manage documentation
Ansible Management: Store and retrieve collection/module information, track version history, check cross-version compatibility, and manage documentation
Entity Management: Create, update, and delete infrastructure entities while tracking relationships and observations
Resource Organization: Hierarchical URI-based resource access with dynamic templates for standardized patterns
Advanced Features: Schema validation, temporal metadata tracking, automated relationship analysis, and search functionality
Integration: Designed to enhance Claude AI's capabilities across development and production environments
Enables interaction with Ansible collections and modules, supporting operations like retrieving collection information, listing modules, checking version compatibility, and adding or updating collection and module definitions with schema validation.
Uses SQLite as the persistent storage backend for Infrastructure-as-Code components, allowing configuration through the DATABASE_URL environment variable.
Provides tools for managing Terraform providers and resources, including retrieving provider information, listing resources, checking version compatibility, and adding or updating provider and resource definitions with schema validation.
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., "@IaC Memory MCP Server show me the latest version of the AWS Terraform provider"
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 that enhances Claude AI's capabilities by providing persistent memory storage for Infrastructure-as-Code (IaC) components, with a focus on version tracking and relationship mapping for Terraform and Ansible resources.
This was a personal project to determine the state of AI's ability if the person using it (me)
doesn't have subject matter expertise (lack of Python knowledge). Since it has become rather cost
prohibitive, I do not intend to develop or maintain this project further.
The IaC Memory MCP Server addresses the challenge of maintaining accurate, version-aware context for IaC components by providing:
Persistent storage and version tracking for IaC components
Hierarchical resource organization with URI-based access
Comprehensive relationship mapping between components
Version-specific documentation management
Schema validation and temporal metadata tracking
Automated relationship analysis and insights
Related MCP server: Claude Code Memory Server
The server implements a sophisticated resource management system with hierarchical URIs:
resources://<platform>/<category>/<name>Supported platforms:
terraform
ansible
iac (for general infrastructure entities)
Example URIs:
resources://terraform/providers/aws
resources://terraform/resources/aws/s3_bucket
resources://ansible/collections/community.aws
resources://ansible/modules/community.aws/s3_bucketThe server provides dynamic resource templates for standardized access patterns:
Terraform provider information: resources://terraform/providers/{provider_name}
Resource type details: resources://terraform/resources/{provider_name}/{resource_type}
Ansible collection data: resources://ansible/collections/{collection_name}
Module information: resources://ansible/modules/{collection_name}/{module_name}
The server implements four specialized prompts for IaC component discovery and analysis:
Purpose: Search for IaC resources
Arguments:
provider: Provider name
resource_type: Resource type
Returns: Information about specific resources for the given provider
Purpose: Analyze an entity and its relationships
Arguments:
entity_id: Entity ID
include_relationships: Include relationships
Returns: Detailed entity analysis including name, type, and observations
Purpose: Get information about a Terraform provider
Arguments:
provider_name: Name of the Terraform provider (required)
version: Specific version to query (optional)
Returns: Detailed provider information for the specified version
Purpose: Get information about an Ansible module
Arguments:
collection_name: Name of the Ansible collection (required)
module_name: Name of the module (required)
version: Specific version to query (optional)
Returns: Detailed module information for the specified version
The server implements comprehensive tooling for IaC component management:
get_terraform_provider_info: Retrieve detailed provider information including version and resources
list_provider_resources: List all resources available for a specific provider
get_terraform_resource_info: Get detailed information about a specific resource type
add_terraform_provider: Register new providers with versioning
add_terraform_resource: Add resource definitions with schemas
update_provider_version: Update provider versions with new documentation
get_ansible_collection_info: Get detailed information about an Ansible collection
list_ansible_collections: List all available Ansible collections
get_collection_version_history: View version history of a collection
get_ansible_module_info: Get detailed information about a specific module
list_collection_modules: List all modules in a collection
get_module_version_compatibility: Check version compatibility of modules
add_ansible_collection: Register new Ansible collections
add_ansible_module: Add new modules with validation and documentation
create_entity: Create new infrastructure entities
update_entity: Modify existing entity configurations
delete_entity: Remove entities with relationship cleanup
view_relationships: Analyze entity dependencies and relationships
The server supports configuration through environment variables:
DATABASE_URL: SQLite database location
MCP_DEBUG: Enable debug logging when set
MCP_TEST_MODE: Enable test mode for database resets
For development, create a .env file:
DATABASE_URL=sqlite:////path/to/db.sqlite
MCP_DEBUG=1
MCP_TEST_MODE=1"mcpServers": {
"iac-memory": {
"command": "uv",
"args": [
"--directory",
"/path/to/iac-memory-mcp-server",
"run",
"iac-memory-mcp-server"
]
"env": {
"DATABASE_URL": "sqlite:////home/herman/iac.db"
}
}
}"mcpServers": {
"iac-memory": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/AgentWong/iac-memory-mcp-server.git",
"python",
"-m",
"iac_memory_mcp_server"
],
"env": {
"DATABASE_URL": "sqlite:////home/herman/iac.db"
}
}
}# Install dependencies
uv sync
# Run tests
uv run pytest
# Development server with MCP Inspector
npx @modelcontextprotocol/inspector uv run iac-memory-mcp-serverThis project is licensed under the MIT License - see the LICENSE file for details.
Add a new Ansible collection to the memory store with version and documentation information
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Collection name | |
| version | Yes | Collection version | |
| source_url | Yes | Source repository URL | |
| doc_url | Yes | Documentation URL |
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 this is a write operation ('Add'), it doesn't specify whether this requires authentication, what happens if a collection already exists (overwrites? errors?), whether the operation is idempotent, or what the memory store's persistence characteristics are. For a mutation tool with zero annotation coverage, this is insufficient 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 a single, well-constructed sentence that efficiently communicates the core functionality. Every word earns its place: 'Add' (action), 'new Ansible collection' (resource), 'to the memory store' (destination), 'with version and documentation information' (scope). No wasted words or 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 4-parameter mutation tool with no annotations and no output schema, the description is minimally adequate but leaves significant gaps. It covers the basic purpose but lacks behavioral context (permissions, error conditions, idempotency) and doesn't explain what happens after the operation (what does 'added to memory store' mean practically?). The absence of output schema means the description should ideally hint at return values, which it doesn't.
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 mentions 'version and documentation information' which aligns with some parameters, but with 100% schema description coverage, all parameters are already documented in the schema. The description doesn't add meaningful semantic context beyond what's in the schema descriptions, such as format expectations for URLs or version strings. 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 action ('Add'), resource ('Ansible collection'), and destination ('to the memory store') with additional context about what information is included ('version and documentation information'). It distinguishes from siblings like 'add_ansible_module' by specifying the collection type, but doesn't explicitly contrast with other collection-related tools like 'update_collection_version' or 'get_ansible_collection_info'.
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 'update_collection_version', 'get_ansible_collection_info', and 'list_ansible_collections', there's no indication whether this is for initial creation versus updates, or how it relates to retrieval operations. The description only states what it does, not when it should be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add a new Ansible module definition with its schema and version information
| Name | Required | Description | Default |
|---|---|---|---|
| collection | Yes | Collection ID or name | |
| name | Yes | Module name | |
| module_type | Yes | Module type | |
| schema | Yes | Module schema | |
| version | Yes | Module version | |
| doc_url | Yes | Documentation URL |
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 adds a module definition but doesn't cover critical aspects like whether this is a write operation, what permissions are required, how conflicts are handled (e.g., if the module already exists), or what the response looks like. This is a significant gap for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 is front-loaded and wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of adding a module (a write operation with 6 required parameters), no annotations, and no output schema, the description is insufficient. It lacks details on behavior, error handling, or return values, leaving the agent with incomplete context for proper 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?
The schema description coverage is 100%, with all 6 parameters clearly documented in the input schema. The description mentions 'schema and version information' but doesn't add meaningful details beyond what the schema provides, such as explaining the relationships between parameters or their expected formats. 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 action ('Add') and resource ('new Ansible module definition with its schema and version information'), making the purpose evident. However, it doesn't explicitly differentiate this tool from sibling tools like 'add_ansible_collection' or 'create_entity', which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, context (e.g., when adding modules is appropriate), or comparisons to siblings like 'add_ansible_collection' or 'create_entity', leaving 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.
Add a new Terraform provider to the memory store with version and documentation information
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Provider name | |
| version | Yes | Provider version | |
| source_url | Yes | Source repository URL | |
| doc_url | Yes | Documentation URL |
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 an 'Add' operation (implying creation/mutation) but doesn't describe what happens on success/failure, whether duplicates are allowed, if the memory store is persistent, or any side effects. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every element ('Add a new Terraform provider', 'to the memory store', 'with version and documentation information') serves a clear purpose, making it appropriately sized and well-structured.
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 4-parameter mutation tool with no annotations and no output schema, the description is minimally adequate. It covers the basic purpose but lacks behavioral details (e.g., what 'memory store' means, success criteria, error handling) and doesn't explain return values. Given the complexity and missing structured data, it should provide more context to be truly complete.
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 mentions 'version and documentation information' which aligns with the 'version', 'source_url', and 'doc_url' parameters, but doesn't add meaning beyond what the schema already provides. With 100% schema description coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding beyond the schema's clear 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 ('Add a new Terraform provider') and the target ('to the memory store'), specifying the resource type (Terraform provider) and what information is included (version and documentation). It distinguishes from siblings like 'add_terraform_resource' by focusing on providers rather than resources, but doesn't explicitly contrast with 'create_entity' which might be a more generic alternative.
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 'add_terraform_provider' over 'create_entity' (which appears to be a generic creation tool) or 'update_provider_version', nor does it specify prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add a new Terraform resource definition with its schema and version information
| Name | Required | Description | Default |
|---|---|---|---|
| provider_id | No | Provider ID | |
| name | Yes | Resource name | |
| resource_type | Yes | Resource type | |
| schema | Yes | Resource schema | |
| version | Yes | Resource version | |
| doc_url | Yes | Documentation URL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is an 'Add' operation (implying creation/mutation) but doesn't disclose any behavioral traits: no information about permissions required, whether this is idempotent, what happens on conflicts, rate limits, or what the response looks like. For a mutation tool with zero annotation coverage, this leaves significant gaps.
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 states the core purpose without unnecessary words. It's appropriately sized for a tool with clear parameters documented elsewhere, though it could be more front-loaded with critical behavioral information given the lack of annotations.
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 mutation tool with 6 required parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't address key contextual questions: what happens when adding duplicates, what permissions are needed, what the return value contains, or how this interacts with sibling tools. The description provides only basic purpose without necessary operational 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 6 parameters. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, format expectations, or provide examples. 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 verb ('Add') and resource ('new Terraform resource definition'), specifying what gets added (schema and version information). It distinguishes from siblings like 'add_terraform_provider' by focusing on resources rather than providers, but doesn't explicitly contrast with other resource-related tools like 'update_resource_schema' or 'get_terraform_resource_info'.
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 about when to use this tool versus alternatives. There's no mention of prerequisites (e.g., whether a provider must exist first), when to choose this over 'update_resource_schema', or what happens if the resource already exists. The description only 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.
Create a new entity in the knowledge graph with optional initial observations
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Entity name | |
| type | Yes | Entity type | |
| observation | No | Initial observation |
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 this is a creation operation, it doesn't address important behavioral aspects like whether this requires specific permissions, what happens if an entity with the same name already exists, whether the operation is idempotent, or what the response looks like. For a mutation tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a tool with 3 parameters and gets straight to the point with no 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?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after creation, what errors might occur, how the entity integrates with the knowledge graph system, or what the tool returns. Given the complexity of entity creation in a knowledge graph context, more contextual information is needed.
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%, so all parameters are documented in the schema. The description adds minimal value beyond the schema by mentioning 'optional initial observations' which corresponds to the 'observation' parameter. However, it doesn't provide additional context about parameter relationships or usage patterns beyond what's already in the structured 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 ('create') and resource ('entity in the knowledge graph'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update_entity' or explain how it relates to other entity management tools like 'delete_entity' and 'view_relationships', 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 like 'update_entity' or 'delete_entity'. It mentions 'optional initial observations' but doesn't explain when this feature is appropriate or what prerequisites might be needed for creating entities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Remove an entity and its relationships from the knowledge graph
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Entity ID |
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 that relationships are also removed, which adds some context beyond a simple 'delete', but it doesn't cover critical aspects like whether the deletion is permanent, requires specific permissions, has side effects on related data, or what happens on success/failure. For a destructive operation with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to understand at a glance.
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 destructive nature, lack of annotations, and no output schema, the description is insufficient. It doesn't explain return values, error conditions, or the full behavioral impact (e.g., cascading effects). For a deletion tool in a knowledge graph context, more detail is needed to ensure safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'id' documented as 'Entity ID'. The description doesn't add any meaning beyond this, such as format examples or constraints, so it meets the baseline of 3 where 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 action ('Remove') and target ('entity and its relationships from the knowledge graph'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'update_entity' or 'create_entity' beyond the verb choice, so it doesn't reach the highest 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 like 'update_entity' or 'view_relationships', nor does it mention prerequisites or exclusions. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve comprehensive information about an Ansible collection
| Name | Required | Description | Default |
|---|---|---|---|
| collection_name | Yes | Name of the Ansible collection |
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 'retrieve' implies a read operation, it doesn't specify what 'comprehensive information' includes, whether there are rate limits, authentication requirements, or error conditions. This leaves significant behavioral aspects undocumented.
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 gets straight to the point without unnecessary words. While perfectly concise, it could be slightly improved with front-loaded key information about what makes this 'comprehensive' versus other retrieval tools.
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 read tool with no annotations and no output schema, the description is minimally adequate. It states what the tool does but leaves important context gaps about what 'comprehensive information' means and how this differs from sibling tools, making it incomplete for optimal agent understanding.
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 the single 'collection_name' parameter adequately. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score for high schema coverage situations.
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 ('Retrieve comprehensive information') and resource ('about an Ansible collection'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_ansible_module_info' or 'list_ansible_collections' beyond the resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'list_ansible_collections' (for listing) and 'get_ansible_module_info' (for module-specific details), there's no indication of when this comprehensive collection info tool is preferred over those options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve comprehensive information about an Ansible module including schema and documentation
| Name | Required | Description | Default |
|---|---|---|---|
| collection_name | Yes | Name of the Ansible collection | |
| module_name | Yes | Name of the module |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions retrieving 'comprehensive information' but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or error handling. The description is vague and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 is appropriately sized and front-loaded, though it could be slightly more structured by separating key aspects like schema vs. documentation retrieval.
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, no output schema, and a read-focused tool with 2 parameters, the description is incomplete. It lacks details on return values, error cases, or how the retrieved information is formatted, leaving gaps for the agent to understand the tool's full behavior and output.
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 parameter descriptions in the schema. The description adds no additional meaning beyond the schema's 'Retrieve comprehensive information about an Ansible module including schema and documentation', which mirrors the input schema 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 verb 'retrieve' and resource 'comprehensive information about an Ansible module including schema and documentation', making the purpose evident. It distinguishes from siblings like 'get_ansible_collection_info' by specifying modules rather than collections, though it doesn't explicitly contrast with 'get_module_version_compatibility' or 'update_module_version'.
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 'get_module_version_compatibility' or 'update_module_version'. The description implies usage for retrieving module details but lacks explicit context, prerequisites, or exclusions, leaving the agent to infer based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve version history for a specific Ansible collection
| Name | Required | Description | Default |
|---|---|---|---|
| collection_name | Yes | Name of the Ansible collection |
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 'Retrieve' suggests a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what the output format looks like. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 with zero wasted words. It's appropriately sized for a single-parameter tool and front-loads the essential information 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?
For a read-only tool with one fully documented parameter, the description adequately covers the basic purpose. However, with no annotations and no output schema, it should ideally provide more context about behavioral aspects (like authentication needs or return format) to be truly complete. The current description meets minimum viable standards 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%, so the schema already fully documents the single 'collection_name' parameter. The description doesn't add any additional meaning beyond what's in the schema (e.g., format examples, constraints, or relationship to other parameters). Baseline 3 is appropriate when the schema does all the parameter documentation work.
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 ('Retrieve version history') and target resource ('for a specific Ansible collection'), distinguishing it from siblings like 'get_ansible_collection_info' (general info) and 'update_collection_version' (modification). It uses precise terminology that matches the tool's domain 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 implies usage when version history is needed for an Ansible collection, but doesn't explicitly state when to choose this tool over alternatives like 'get_ansible_collection_info' or 'get_provider_version_history' (for Terraform). No guidance on prerequisites or exclusions is provided, leaving usage context somewhat ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check module compatibility across collection versions
| Name | Required | Description | Default |
|---|---|---|---|
| collection_name | Yes | Name of the Ansible collection | |
| module_name | Yes | Name of the module to check | |
| version | Yes | Target collection version to check compatibility against |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'checks' compatibility, implying a read-only operation, but doesn't clarify whether it's a simple lookup, requires network access, has rate limits, returns structured data, or what happens on errors. For a tool with three required parameters and no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 for a straightforward tool and front-loads the core functionality.
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 has three required parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., compatibility status, error messages, or structured data), nor does it cover behavioral aspects like error handling or performance characteristics, leaving the agent with significant uncertainty.
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 all three parameters clearly documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema (e.g., it doesn't explain format constraints, example values, or relationships between parameters). 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 as 'Check module compatibility across collection versions', which specifies the verb ('check'), resource ('module compatibility'), and scope ('across collection versions'). However, it doesn't explicitly differentiate from its sibling 'get_resource_version_compatibility', which appears to serve a similar function for Terraform resources rather than Ansible modules.
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, context, or exclusions, nor does it reference sibling tools like 'get_resource_version_compatibility' or 'get_collection_version_history' that might be relevant for related queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve version history for a specific Terraform provider
| Name | Required | Description | Default |
|---|---|---|---|
| provider_name | Yes | Name of the Terraform provider |
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 'Retrieve' but does not specify whether this is a read-only operation, if it requires authentication, what the return format is (e.g., list of versions with timestamps), or any rate limits. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 any unnecessary words. It is front-loaded and wastes no space, making it easy to understand at a glance.
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 one parameter and no output schema, the description is minimally adequate but lacks depth. It does not explain what the version history includes (e.g., version numbers, release dates, changelogs) or how the data is structured, which could be important for an agent to interpret results correctly. Given the simplicity, it meets basic needs but could be more informative.
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 the parameter 'provider_name' clearly documented. The description does not add any extra meaning beyond what the schema provides, such as examples or constraints on the provider name format. Given the high schema coverage, a 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 verb 'Retrieve' and the resource 'version history for a specific Terraform provider', making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_terraform_provider_info' or 'get_collection_version_history', which might retrieve different aspects of provider data.
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 such as 'get_terraform_provider_info' or 'get_collection_version_history'. It lacks context about prerequisites, exclusions, or specific scenarios where this tool is preferred over others, leaving usage decisions unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check resource compatibility across provider versions
| Name | Required | Description | Default |
|---|---|---|---|
| provider_name | Yes | Name of the Terraform provider | |
| resource_name | Yes | Name of the resource to check | |
| version | Yes | Target provider version to check compatibility against |
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 what the tool does but doesn't describe how it behaves: no information on output format (e.g., compatibility matrix, boolean result), error handling (e.g., if provider/resource not found), or side effects (likely none, but not confirmed). For a tool with 3 required parameters and no output schema, this leaves the agent guessing about critical operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 with zero redundancy. It's appropriately front-loaded and wastes no words, making it easy for an agent to parse quickly. Every part of the sentence contributes essential information about the tool's function.
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 (3 required parameters, no output schema, no annotations), the description is insufficiently complete. It doesn't explain what 'compatibility' means in practice (e.g., backward/forward compatibility, schema changes), what the output contains, or how to interpret results. With siblings that might provide related information, the description should do more to help the agent understand when and how to use this specific tool 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%, with all parameters well-documented in the schema (provider_name, resource_name, version). The description adds no additional parameter semantics beyond what's in the schema - it doesn't clarify format expectations (e.g., version syntax like '1.2.3'), dependencies between parameters, or examples. Given the high schema coverage, the baseline score of 3 is appropriate, but the description doesn't enhance 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's purpose: 'Check resource compatibility across provider versions' - a specific verb ('check') with clear objects ('resource compatibility', 'provider versions'). It distinguishes from most siblings (e.g., get_terraform_resource_info, get_provider_version_history) by focusing on compatibility checking rather than information retrieval or history. However, it doesn't explicitly differentiate from get_module_version_compatibility, which has a similar pattern for Ansible modules.
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., whether the provider/resource must exist in the system), nor does it specify use cases (e.g., planning upgrades, troubleshooting). With siblings like get_terraform_resource_info and get_provider_version_history that might overlap in context, the lack of explicit differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve comprehensive information about a Terraform provider
| Name | Required | Description | Default |
|---|---|---|---|
| provider_name | Yes | Name of the Terraform provider |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it 'retrieves' information, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'comprehensive information' entails. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence earns its place by specifying the action and resource 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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'comprehensive information' includes, how results are formatted, or any behavioral context, which is inadequate for a tool that likely returns complex data about Terraform providers.
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 parameter 'provider_name' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, so it meets the baseline for high schema coverage without compensating value.
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 ('Retrieve comprehensive information') and resource ('about a Terraform provider'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_terraform_resource_info' or 'get_provider_version_history', which limits its 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. With siblings like 'get_provider_version_history' and 'list_terraform_providers' available, there's no indication of context, prerequisites, or exclusions for this specific retrieval tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve comprehensive information about a Terraform resource including schema and documentation
| Name | Required | Description | Default |
|---|---|---|---|
| provider_name | Yes | Name of the Terraform provider | |
| resource_name | Yes | Name of the resource |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'retrieves' information, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or details the output format. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 purpose from scope details.
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 2 parameters with full schema coverage but no annotations and no output schema, the description is minimally adequate. It covers the 'what' but lacks behavioral context like authentication needs or return format. For a read tool with simple inputs, it meets basic needs but leaves room for improvement in completeness.
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 both parameters ('provider_name' and 'resource_name') well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. 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 verb 'retrieve' and the resource 'Terraform resource information', specifying it includes 'schema and documentation'. It distinguishes from sibling tools like 'get_erraform_provider_info' by focusing on resources rather than providers, though it doesn't explicitly contrast with other resource-related tools like 'list_provider_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 when to choose this over sibling tools like 'get_resource_version_compatibility' or 'list_provider_resources', nor does it specify prerequisites or exclusions. Usage is implied 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.
List all cached Ansible collections with basic metadata
| Name | Required | Description | Default |
|---|---|---|---|
| filter_criteria | No | Optional filtering criteria |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation with basic metadata, implying it's read-only and non-destructive, but doesn't cover aspects like pagination, rate limits, authentication needs, or what 'cached' entails (e.g., freshness of data). This leaves significant gaps for a tool with potential complexity.
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 ('List all cached Ansible collections with basic metadata'). There's no wasted verbiage, and it directly communicates the essential information 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 lack of annotations and output schema, the description is incomplete for a list tool. It doesn't explain what 'basic metadata' includes, the format of the returned data, or any behavioral traits like error handling. For a tool that might return complex data structures, this leaves the agent with insufficient context 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?
The schema description coverage is 100%, with the single parameter 'filter_criteria' and its nested 'name_pattern' property well-documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.
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 'cached Ansible collections' with 'basic metadata', providing a specific purpose. However, it doesn't explicitly differentiate from sibling tools like 'get_ansible_collection_info' or 'get_collection_version_history', which might offer more detailed or historical information about collections.
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 'get_ansible_collection_info' for detailed info or 'list_provider_resources' for other resource types, leaving the agent to infer usage based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all resources associated with a specific Terraform provider
| Name | Required | Description | Default |
|---|---|---|---|
| provider_name | Yes | Name of the Terraform provider | |
| filter_criteria | No | Optional filtering criteria |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'List all resources' but does not describe key behaviors such as pagination, rate limits, authentication requirements, or what 'all resources' entails (e.g., if it includes deprecated ones). This leaves significant gaps for a tool with potential complexity.
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 is front-loaded and earns its place by clearly conveying the core functionality, making it highly concise and well-structured.
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 and no output schema, the description is incomplete for a tool that lists resources. It lacks details on behavioral traits (e.g., pagination, error handling), output format, or usage context, which are critical for an agent to invoke it correctly in a Terraform management 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 schema description coverage is 100%, with clear descriptions for both parameters (provider_name and filter_criteria with type_pattern). The description does not add any additional meaning beyond what the schema provides, such as examples or usage context for the filter_criteria, so it meets the baseline score.
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 ('List all resources') and the target ('associated with a specific Terraform provider'), providing a specific verb+resource combination. However, it does not explicitly differentiate from sibling tools like 'list_terraform_providers' or 'get_terraform_resource_info', which reduces it from 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 does not mention sibling tools like 'list_terraform_providers' for listing providers instead of resources, or 'get_terraform_resource_info' for detailed info on a specific resource, leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all cached Terraform providers with basic metadata
| Name | Required | Description | Default |
|---|---|---|---|
| filter_criteria | No | Optional filtering criteria |
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 'cached' providers and 'basic metadata', but fails to specify what 'cached' means (e.g., local vs. remote), the format of the list (e.g., paginated, sorted), or any limitations (e.g., rate limits, authentication needs). This leaves significant gaps for a tool that likely interacts with a system state.
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 action ('List all cached Terraform providers') and adds necessary context ('with basic metadata') without redundancy. Every word earns its place, making it highly concise and well-structured.
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 and no output schema, the description is incomplete for a tool that likely returns a list of providers. It specifies the resource and scope but omits details on return format (e.g., structure of 'basic metadata'), error handling, or system dependencies. This is adequate as a minimum but has clear gaps in contextual information.
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 the optional 'filter_criteria' parameter and its 'name_pattern' sub-property. The description does not add any parameter details beyond what the schema provides, such as examples of regex patterns or filtering behavior, meeting 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 verb ('List') and resource ('all cached Terraform providers'), specifying the scope ('all cached') and output ('with basic metadata'). It distinguishes from siblings like 'get_terraform_provider_info' by indicating a list operation rather than detailed info retrieval, though it doesn't explicitly contrast with 'list_provider_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 like 'get_terraform_provider_info' for detailed metadata or 'list_provider_resources' for related resources. The description implies usage for listing providers but lacks explicit context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Update an existing Ansible collection's version information and documentation links
| Name | Required | Description | Default |
|---|---|---|---|
| collection_id | Yes | Collection ID | |
| new_version | Yes | New version | |
| new_source_url | No | New source URL | |
| new_doc_url | No | New documentation URL |
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 'Update an existing Ansible collection's version information and documentation links', implying a mutation operation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or what happens to existing data not mentioned. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 front-loaded with the core action and resource, 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 a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't address behavioral traits, error handling, or return values, leaving the agent with incomplete information to use the tool effectively in a real-world 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%, meaning all parameters are documented in the schema. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain format constraints, examples, or relationships between parameters). According to the rules, with high schema coverage, the baseline is 3 even without param info in the description.
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 ('Update') and the resource ('an existing Ansible collection's version information and documentation links'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'update_entity' or 'update_module_version', which could handle similar updates in different contexts.
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 'update_entity' or 'update_module_version'. It mentions updating 'an existing Ansible collection', but lacks context on prerequisites, exclusions, or specific scenarios where this tool is preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Update an existing entity's properties and add new observations
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Entity ID | |
| name | No | New name | |
| type | No | New type | |
| observation | No | New observation |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action ('update' and 'add') without disclosing behavioral traits like permission requirements, whether updates are reversible, how conflicts are handled, or what the response includes. This is inadequate for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('update an existing entity's properties and add new observations') with zero wasted words. Every part 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?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover error conditions, response format, or important behavioral aspects like idempotency or side effects, leaving significant gaps for agent understanding.
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 parameters. The description adds no additional meaning beyond what's in the schema, such as explaining how 'observation' relates to 'properties' or format details. 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 verb ('update') and resource ('existing entity'), and specifies what gets updated ('properties') and added ('new observations'). However, it doesn't explicitly differentiate from sibling tools like 'create_entity' or 'delete_entity' beyond the 'existing' qualifier.
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 'create_entity' for new entities or 'view_relationships' for related operations. It mentions 'existing entity' but doesn't clarify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Update an existing Ansible module's schema and related information
| Name | Required | Description | Default |
|---|---|---|---|
| module_id | Yes | Module ID | |
| new_schema | Yes | New schema | |
| new_version | No | New version | |
| new_doc_url | No | New documentation URL |
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 updating schema and related information but doesn't specify whether this is a destructive operation, what happens to existing data, or if there are rate limits or authentication requirements. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 front-loaded and earns its place by clearly conveying the core action, making it highly concise and well-structured.
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 updating a module (a mutation operation) with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like side effects, error handling, or return values, leaving significant gaps for an AI agent to understand the tool's full 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 input schema already documents all parameters. The description doesn't add any additional meaning beyond what the schema provides, such as explaining the format of 'new_schema' or how 'new_version' interacts with existing versions. Baseline 3 is appropriate when the schema handles parameter 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 ('Update') and resource ('existing Ansible module's schema and related information'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'update_entity' or 'update_collection_version', which could handle similar updates in different contexts.
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 'update_entity' or 'update_collection_version'. The description lacks context about prerequisites, such as whether the module must exist or if specific permissions are needed, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Update an existing Terraform provider's version information and documentation links
| Name | Required | Description | Default |
|---|---|---|---|
| provider_name | Yes | Name of the provider | |
| new_version | Yes | New version | |
| new_source_url | No | New source URL | |
| new_doc_url | No | New documentation URL |
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 an update operation, implying mutation, but doesn't mention permission requirements, whether changes are reversible, potential side effects, or error conditions. 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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place in conveying essential information.
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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like authentication needs, error handling, or what the tool returns. Given the complexity of updating provider versions and the lack of structured metadata, the description should provide more context to guide 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%, so the input schema fully documents all four parameters. The description adds no additional parameter semantics beyond what's already in the schema (e.g., format expectations, constraints, or examples). The baseline score of 3 reflects adequate but minimal value added by the description over the structured 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 action ('Update') and resource ('existing Terraform provider's version information and documentation links'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'update_entity' or 'update_collection_version', which could handle similar update operations on 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 like 'update_entity' or 'add_terraform_provider'. It doesn't mention prerequisites (e.g., the provider must already exist), exclusions, or contextual constraints, leaving the agent to infer usage 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.
Update an existing Terraform resource's schema and related information
| Name | Required | Description | Default |
|---|---|---|---|
| resource_id | Yes | Resource ID | |
| new_schema | Yes | New schema | |
| new_version | No | New version | |
| new_doc_url | No | New documentation URL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a mutation ('Update') but doesn't disclose critical traits like required permissions, whether changes are reversible, potential side effects, or rate limits. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's 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?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., permissions, side effects), usage context, and doesn't compensate for the absence of structured safety or output information.
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 four parameters. The description adds no additional meaning beyond what the schema provides (e.g., no examples, format details, or constraints). 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 action ('Update') and target ('an existing Terraform resource's schema and related information'), providing specific verb+resource. However, it doesn't explicitly differentiate from sibling tools like 'update_entity' or 'update_provider_version', which could handle similar updates in different contexts.
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 an existing resource), exclusions, or compare it to siblings like 'update_entity' or 'update_provider_version' that might handle related updates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve all relationships and observations for a specific entity
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | Yes | Entity ID |
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 'Retrieve', implying a read-only operation, but does not disclose behavioral traits like permissions needed, rate limits, pagination, or what 'observations' entail. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's function without unnecessary words. It is front-loaded and efficient, earning its place by conveying the core purpose concisely.
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, no output schema, and a single parameter with full schema coverage, the description is incomplete. It lacks details on return values, error handling, or behavioral context, making it insufficient for an agent to fully understand the tool's operation and outcomes.
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 the parameter 'entity_id' documented as 'Entity ID'. The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline is 3, as the schema handles the parameter 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 ('Retrieve') and the target ('all relationships and observations for a specific entity'), making the purpose understandable. However, it does not differentiate this tool from potential siblings like 'get_entity' or 'list_relationships', which might offer similar functionality, preventing a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or compare it to sibling tools such as 'get_entity' or 'list_relationships', leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Most tools have distinct purposes targeting specific IaC components (Ansible vs. Terraform) and operations (add/get/list/update). However, there is some potential overlap between 'create_entity' and the various 'add_' tools, as both involve storing information, though 'create_entity' seems more generic for a knowledge graph. The descriptions help clarify boundaries, but an agent might need to infer when to use 'create_entity' versus the specific 'add_' tools.
Tool names follow a highly consistent verb_noun pattern throughout, with clear and predictable conventions. All tools use snake_case, and verbs like 'add', 'get', 'list', 'update', 'delete', and 'view' are applied consistently across similar resource types (e.g., 'add_ansible_collection', 'get_ansible_collection_info', 'list_ansible_collections'). This makes the tool set easy to navigate and understand.
With 23 tools, the count is on the higher side for an MCP server, bordering on heavy. While the server covers both Ansible and Terraform domains comprehensively, the number of tools might feel overwhelming or lead to redundancy (e.g., separate tools for version history and compatibility checks). A more streamlined set could improve usability without losing functionality, placing it in the borderline range.
The tool surface provides complete CRUD/lifecycle coverage for both Ansible and Terraform components, including adding, retrieving, listing, updating, and deleting entities. It also handles version management, compatibility checks, and relationship viewing for a knowledge graph. No obvious gaps exist; agents can perform all expected operations for managing IaC metadata and entities without dead ends.
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