Docker MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
There is significant functional overlap between tools, particularly in monitoring and management areas. For example, 'docker_monitoring' and 'docker_monitoring_advanced' have unclear boundaries, and 'manage_containers' overlaps with 'create_container' and potentially 'docker_compose' operations. While descriptions provide some differentiation, agents may struggle to choose between these tools for common tasks.
Naming Consistency4/5
Most tools follow a consistent snake_case pattern with descriptive names, but there are notable deviations. 'docker_backup_migration' uses an underscore instead of a verb, and 'execute_docker_command' has a different structure than the majority. The naming is generally readable but lacks complete uniformity across all tools.
Tool Count4/5
With 14 tools, the count is reasonable for Docker management, covering a broad scope from containers to images, networks, volumes, and system operations. However, some tools feel redundant (e.g., two monitoring tools), suggesting the set could be more streamlined without losing functionality for the domain.
Completeness5/5
The tool set provides comprehensive coverage of Docker operations, including CRUD for containers, images, networks, and volumes, plus monitoring, registry interactions, remote connections, and system info. There are no obvious gaps; agents can perform end-to-end workflows from setup to maintenance and troubleshooting in this domain.
Average 2.9/5 across 14 of 14 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository is licensed under MIT License.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions operations like 'login/logout' and 'push/pull' but doesn't disclose authentication requirements, rate limits, side effects (e.g., data transfer), or error handling. For a multi-action tool with potential security implications, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (three comma-separated phrases) and front-loaded with all key operations. However, it's arguably too terse for a complex multi-action tool, missing explanatory context that could justify a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, multiple actions), lack of annotations, and no output schema, the description is insufficient. It doesn't explain return values, error conditions, or behavioral nuances (e.g., what 'login' actually does), 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 8 parameters. The description adds no parameter-specific information beyond implying that 'search', 'login/logout', and 'push/pull' correspond to the 'action' enum. This meets the baseline for high schema coverage but doesn't enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description lists multiple operations (search, login/logout, push/pull) but lacks specificity about what resources are involved (e.g., Docker Hub images, registry authentication). It distinguishes from siblings by focusing on registry operations rather than container/image management, but the purpose remains somewhat vague as it doesn't clearly state what the tool fundamentally does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'manage_images' or 'execute_docker_command'. The description merely enumerates actions without context about prerequisites, dependencies, or appropriate scenarios for each operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Manage Docker Compose services' implies mutation capabilities (e.g., 'up', 'down', 'restart'), but it doesn't specify permissions required, side effects, error handling, or output format. For a tool with multiple actions including potentially destructive ones, this lack of detail is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence ('Manage Docker Compose services'), which is front-loaded and wastes no words. However, this conciseness comes at the cost of detail, but for scoring this dimension alone, it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple actions with potential mutations), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, usage context, or output expectations, leaving significant gaps for an AI agent to understand how to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions (e.g., 'build' only applies to 'up'), constraints, or examples. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Manage Docker Compose services' states a general purpose but is vague about what 'manage' entails. It doesn't specify the specific actions available (up, down, logs, etc.) or distinguish it from sibling tools like 'docker_compose_advanced' or 'execute_docker_command'. The verb 'manage' is too broad for clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context for choosing specific actions, or how it differs from sibling tools like 'docker_compose_advanced' or 'execute_docker_command'. The description offers no usage context beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions executing commands but doesn't describe safety aspects (e.g., whether it can run destructive commands, requires specific permissions, has rate limits, or returns structured output). For a tool that likely interacts with Docker, this lack of behavioral context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly. Every word earns its place by conveying the core capability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Docker operations and the lack of annotations and output schema, the description is incomplete. It doesn't explain what happens after execution (e.g., success/failure handling, output format), nor does it address potential risks or dependencies. For a tool with no structured safety hints, more context is needed 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.
Parameters3/5
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 'command' documented as 'Natural language command or direct Docker command to execute'. The description adds no additional meaning beyond this, such as examples or constraints on command types. With high schema coverage, the baseline score of 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Execute Docker commands using natural language or direct commands', which provides a general purpose but lacks specificity. It mentions both natural language and direct commands but doesn't clarify what types of Docker commands are supported or how it differs from sibling tools like manage_containers or docker_compose. The purpose is vague rather than specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools available (e.g., create_container, manage_containers, docker_compose), the description doesn't specify scenarios where execute_docker_command is preferred, nor does it mention prerequisites or exclusions. This leaves the agent without clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Create and run' implies a write/mutation operation, but the description doesn't mention permissions required, whether containers persist after execution, error handling, or what happens if a container with the same name exists. For a complex 18-parameter mutation tool, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point. 'Create and run Docker containers with advanced options' contains no wasted words and immediately communicates the core functionality. It's appropriately sized for what it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 18 parameters, no annotations, and no output schema, the description is inadequate. It doesn't address behavioral aspects like permissions, side effects, or error conditions. While the schema covers parameters well, the description fails to provide the contextual understanding needed for safe and effective tool invocation in a Docker management ecosystem with multiple similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 18 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema - it doesn't explain parameter relationships, constraints, or provide examples beyond the schema's descriptions. The baseline of 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create and run') and resource ('Docker containers'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'manage_containers' or 'docker_compose', which likely have overlapping functionality. The phrase 'with advanced options' adds some specificity but doesn't clearly demarcate boundaries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools like 'manage_containers', 'docker_compose', and 'execute_docker_command', there's no indication of when this specific container creation tool is appropriate versus those other options. The agent receives no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions backup and migration but doesn't describe what 'backup' entails (e.g., creates files, requires storage space), whether operations are destructive, authentication needs, rate limits, or what happens during migration. This is inadequate for a tool with multiple action types.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that efficiently communicates the core functionality. Every word earns its place, and it's front-loaded with the main purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple action types, 5 parameters) and lack of both annotations and output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral details needed for safe operation, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds no additional parameter semantics beyond implying the tool handles containers, volumes, and projects, which aligns with the 'action' enum values. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as backing up and migrating Docker resources (containers, volumes, projects). It uses specific verbs ('backup', 'migration') and resources, but doesn't explicitly differentiate from sibling tools like 'manage_containers' or 'manage_volumes' that might handle similar operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when not to use it, or how it differs from sibling tools like 'manage_containers' or 'docker_compose' that might handle related backup or migration tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Get') but doesn't reveal if this is a read-only operation, requires specific permissions, has rate limits, or what the output format might be. This is inadequate for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 wasted words. It is 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'system information and statistics' entails, how results are returned, or any behavioral traits like safety or performance implications, which are crucial for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'type' parameter fully documented via enum values. The description adds no additional parameter semantics beyond implying retrieval of 'information and statistics', which aligns with the schema but doesn't provide extra context like default behaviors or usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('Docker system information and statistics'), making the purpose evident. However, it doesn't differentiate from sibling tools like 'docker_monitoring' or 'docker_monitoring_advanced', which might also retrieve system-related data, so it lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare to siblings such as 'docker_monitoring' for real-time stats or 'execute_docker_command' for custom queries, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It lists actions but doesn't explain what 'troubleshoot issues' entails, whether operations are read-only or have side effects (e.g., 'exec' might modify container state), or any constraints like permissions or rate limits. This is inadequate for a tool with multiple action types.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads key actions. However, it could be more structured by explicitly listing the 'action' enum values or grouping related functionalities, but it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, multiple actions) and lack of annotations and output schema, the description is insufficient. It doesn't cover behavioral aspects like side effects, error handling, or return formats, which are critical for an agent to use it correctly, especially with actions like 'exec' that may have security implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing clear documentation for all 7 parameters. The description adds no parameter-specific information beyond what's in the schema, such as clarifying how 'action' maps to the listed verbs or explaining parameter interactions. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('monitor', 'get logs', 'inspect resources', 'troubleshoot issues') and identifies the resource (containers). It distinguishes from some siblings like 'create_container' or 'manage_images' but doesn't explicitly differentiate from 'docker_monitoring_advanced', which appears to be a more specialized version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'docker_monitoring_advanced' or other sibling tools like 'execute_docker_command', leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'enhanced monitoring' but doesn't specify whether this requires special permissions, has rate limits, affects system performance, or what the output looks like. The description is too vague about actual behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (8 words) and front-loaded with the core purpose. Every word contributes to understanding the tool's enhanced capabilities compared to basic monitoring.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a monitoring tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'enhanced' means operationally, what format the monitoring data returns, or how the different actions differ in behavior and output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description mentions 'health checks, events, and detailed statistics' which loosely maps to some action enum values but doesn't add meaningful semantic context beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'enhanced monitoring' with specific capabilities (health checks, events, detailed statistics), which distinguishes it from the simpler 'docker_monitoring' sibling tool. However, it doesn't specify the exact verb or resource scope beyond 'monitoring'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the simpler 'docker_monitoring' sibling or other monitoring alternatives. It mentions capabilities but doesn't specify appropriate contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions connection and configuration actions but fails to describe critical traits: whether this tool mutates state (e.g., persistent configuration changes), requires authentication details beyond parameters, has side effects (e.g., network timeouts), or returns specific output formats. For a tool with multiple actions and remote operations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could benefit from slightly more detail given the tool's complexity. The structure is clear but minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, multiple actions, remote operations) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like error handling, output format, or security implications, leaving the agent under-informed for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 parameters (action, host, user, keyPath). The description adds no additional meaning beyond the schema—it doesn't explain parameter interactions (e.g., 'host' required for 'connect' but not 'status'), usage examples, or constraints. Baseline 3 is appropriate as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Connect to remote Docker hosts via SSH or configure Docker host.' It specifies the verb ('connect') and resource ('remote Docker hosts'), and mentions configuration as an alternative action. However, it doesn't explicitly differentiate from sibling tools like 'docker_compose' or 'execute_docker_command', which might also involve remote connections indirectly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., SSH setup), exclusions (e.g., not for local Docker), or compare to siblings like 'docker_compose' for orchestration. The lack of context leaves the agent guessing about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral context. It mentions actions but doesn't disclose permissions needed, side effects (e.g., data loss on remove), or error conditions. For a tool with destructive operations, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with zero wasted words. Front-loaded with the core purpose, though it could be more complete by including 'restart' from the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with multiple potentially destructive actions (stop, remove, restart), no annotations, and no output schema, the description is insufficient. It doesn't explain return values, error handling, or safety considerations, 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.
Parameters3/5
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 parameters. The description adds no additional meaning about parameters beyond implying the tool handles multiple actions, which is already clear from the schema's enum. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool manages Docker containers with specific verbs (list, start, stop, remove), though it omits 'restart' which appears in the schema. It distinguishes from siblings like create_container and manage_images by focusing on lifecycle operations rather than creation or image management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like docker_compose or execute_docker_command. The description lists actions but doesn't provide context for choosing between this multi-action tool and more specialized siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It lists actions but doesn't describe their effects (e.g., 'remove' deletes images, 'build' creates new ones), permissions required, side effects, or error conditions. This is inadequate for a multi-action mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one phrase) and front-loaded with all essential information. Every word earns its place, making it efficient for quick scanning without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-action tool with no annotations and no output schema, the description is incomplete. It doesn't explain what each action does behaviorally, what the tool returns, or how errors are handled. This leaves significant gaps for an 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no parameter-specific semantics beyond implying the 'action' parameter's values, which are already in the enum. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool manages Docker images and enumerates the specific actions (list, pull, remove, build), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like manage_containers or manage_volumes, which handle different Docker resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for choosing between actions, or how it relates to sibling tools like manage_containers or docker_compose, leaving the agent with no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it lists action types, it doesn't describe what each action does, what permissions are required, whether operations are destructive, what happens on failure, or what the output looks like. For a multi-action tool with mutation capabilities, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single parenthetical list of actions that efficiently communicates scope. Every word earns its place, and the structure is front-loaded with the core purpose followed by specific capabilities.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-action tool with mutation capabilities (create, remove, connect, disconnect) and no annotations or output schema, the description is incomplete. It doesn't explain behavioral implications, error conditions, or what users can expect from different actions. The tool has significant complexity that isn't addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, dependencies, or usage patterns. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool manages Docker networks and lists specific actions (list, create, remove, inspect, connect, disconnect). It provides a specific verb ('manage') and resource ('Docker networks'), but doesn't explicitly differentiate from sibling tools like manage_containers or manage_volumes beyond the network focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose manage_networks over execute_docker_command for network operations, or how it relates to docker_compose tools. No context about prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only lists actions without behavioral details. It doesn't disclose permissions needed, whether operations are destructive, what happens during 'prune' (mentioned in schema but not description), or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with zero wasted words. Every word earns its place by specifying the resource (Docker volumes) and available actions in a clear, front-loaded manner.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-action mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'prune' does (though in schema), doesn't describe return values, and provides minimal behavioral context for operations that could be destructive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add meaningful parameter semantics beyond what's in the schema, maintaining the baseline score for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as managing Docker volumes with specific actions (list, create, remove, inspect). It distinguishes from siblings by focusing on volumes rather than containers, images, or networks, but doesn't explicitly differentiate from all volume-related alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. While it's clear this is for volume management, there's no mention of when to choose this over other Docker tools or when specific actions are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'plan+apply workflow' which hints at a two-step process, but fails to describe critical behaviors: what 'plan' does (e.g., preview changes), what 'apply' entails (e.g., actual deployment), side effects, error handling, or authentication needs. For a tool with actions like 'destroy' that could be destructive, this lack of transparency is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Manage Docker projects') and key differentiator ('plan+apply workflow'). There is zero wasted text, making it easy for an agent to parse quickly while still conveying essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters including enums, actions like 'destroy', no output schema, and no annotations), the description is inadequate. It doesn't explain the workflow details, return values, error conditions, or how parameters interact (e.g., 'containers' being required for 'plan'). For an 'advanced' tool with potential destructive operations, more context is needed to ensure safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing good documentation for all parameters. The description adds minimal value beyond the schema—it mentions 'natural language' which might relate to the 'containers' parameter, but doesn't clarify syntax or examples. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Manage Docker projects with natural language using plan+apply workflow', which specifies the verb ('manage'), resource ('Docker projects'), and approach ('plan+apply workflow'). It distinguishes from simpler sibling 'docker_compose' by emphasizing 'advanced' capabilities, though it doesn't explicitly contrast with all siblings like 'execute_docker_command' or 'manage_containers'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the mention of 'plan+apply workflow', suggesting this tool is for structured Docker project management rather than ad-hoc operations. However, it provides no explicit guidance on when to use this versus alternatives like 'docker_compose', 'execute_docker_command', or 'manage_containers', leaving the agent to infer based on the 'advanced' and 'workflow' cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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