Docker MCP Server

by Swartdraak

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific Docker resources and actions. For example, create_container and run_container are well-differentiated by their descriptions, with run_container explicitly noted as the preferred method for starting containers. There is no ambiguity or overlap in functionality across the tool set.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as list_containers, create_container, and stop_container. This predictable naming convention makes it easy for agents to understand and select the appropriate tools without confusion.
Tool Count5/5
With 12 tools, the server is well-scoped for managing Docker containers, images, networks, and volumes. Each tool earns its place by covering essential operations like creation, listing, starting, stopping, and removal, without being overly sparse or bloated.
Completeness4/5
The tool set provides strong coverage for core Docker operations, including CRUD for containers and listing for other resources. Minor gaps exist, such as no tools for creating or removing networks/volumes, but agents can still perform most workflows effectively with the available tools.
Average 3/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Get logs' implies a read-only operation, but it doesn't specify critical behaviors such as whether this requires specific permissions, if it streams logs in real-time, potential rate limits, or what happens if the container doesn't exist. The description is too minimal for a tool with potential operational impact.
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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward tool, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of container operations and the lack of annotations and output schema, the description is insufficient. It doesn't cover what the logs contain, how they're formatted, error conditions, or behavioral nuances like streaming. For a tool that interacts with system resources, this leaves significant gaps in 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 already documents all parameters (containerId, tail, follow) with clear descriptions. The description adds no additional meaning beyond what's in the schema, such as explaining log format or interaction 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get logs from a container' clearly states the verb ('Get') and resource ('logs from a container'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'inspect_container' or specify what type of logs (e.g., stdout/stderr, application vs. system), which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., the container must be running or exist), nor does it differentiate from sibling tools like 'inspect_container' that might provide related information. This lack of contextual guidance leaves the agent to infer usage scenarios.
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 but offers minimal information. It states this is a creation operation but doesn't mention whether it requires specific permissions, what happens if a container with the same name exists, whether the container starts automatically, or what the typical response format might be. For a complex mutation tool with 8 parameters, this is inadequate 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 extremely concise at just 4 words, front-loading the essential purpose without any wasted words. While this brevity comes at the cost of completeness, as a standalone statement it's efficiently structured.
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 container creation tool with 8 parameters, no annotations, no output schema, and multiple sibling tools, the description is severely incomplete. It doesn't address behavioral aspects, usage context, or provide any guidance beyond the basic purpose, leaving significant gaps for an agent trying to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter information beyond what's already in the schema, which has 100% coverage with detailed descriptions for all 8 parameters. The baseline score of 3 reflects that the schema does the heavy lifting, though the description could have provided higher-level context about how parameters relate or typical usage patterns.
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 'Create a new Docker container' clearly states the verb ('create') and resource ('Docker container'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'run_container', which appears to serve a similar function, leaving some ambiguity about when to use one versus the other.
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 like 'run_container' or other container management tools. There's no mention of prerequisites, typical use cases, or constraints that would help an agent select this tool appropriately from among the 11 sibling tools available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a 'Get' operation, implying read-only behavior, but doesn't confirm if it's safe, whether it requires specific permissions, what format the detailed information returns, or if there are rate limits. The description adds minimal behavioral context beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the core purpose immediately.
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 no annotations and no output schema, the description is incomplete for a tool that presumably returns detailed container information. It doesn't explain what 'detailed information' includes (e.g., status, configuration, resources) or the response format, leaving significant gaps for the agent to understand the tool's 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?
The input schema has 100% description coverage, with the single parameter 'containerId' documented as 'Container ID or name'. The description adds no additional parameter semantics beyond what's in the schema, 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.
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 ('detailed information about a container'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_containers' or 'container_logs' which also provide information about containers, missing an opportunity for clearer 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 specify that this is for detailed metadata rather than logs (container_logs) or a summary list (list_containers), nor does it mention prerequisites like needing a container ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'List all Docker containers' but doesn't disclose behavioral traits such as output format, pagination, permissions required, rate limits, or whether it's a read-only operation. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 address behavioral aspects like output format or operational context, which are crucial for a tool that interacts with system resources like Docker containers. More detail is needed to compensate for the missing structured data.
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 'all' parameter fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, so 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all Docker containers'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_images' or 'list_networks' beyond the resource name, missing explicit 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, context for listing containers, or compare to related tools like 'inspect_container' for detailed views, leaving usage decisions to inference.
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. 'List Docker images' implies a read-only operation, but it doesn't specify whether this requires specific permissions, how results are formatted (e.g., JSON, table), if there's pagination, or what happens on errors. For a tool with zero annotation coverage, this leaves critical behavioral traits undocumented.
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 at just three words ('List Docker images'), with zero wasted language. It's front-loaded and directly states the core functionality without unnecessary elaboration, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 for effective tool use. It doesn't explain what the tool returns (e.g., image IDs, tags, sizes), how results are structured, or any behavioral nuances. For a listing tool in a Docker context with multiple similar siblings, more context is needed to distinguish it and guide proper 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 single parameter 'all' fully documented in the schema itself ('Show all images (default hides intermediate)'). The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List Docker images' clearly states the verb ('List') and resource ('Docker images'), making the tool's purpose immediately understandable. However, it doesn't differentiate this from sibling tools like 'list_containers', 'list_networks', or 'list_volumes', which all follow the same 'list [resource]' pattern without specifying what distinguishes listing images from listing other 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 (e.g., Docker daemon running), compare it to similar tools like 'inspect_container' for detailed views, or explain why one might list images instead of containers. With multiple sibling listing tools, this lack of differentiation leaves 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'pull' implies a network operation that fetches data, the description doesn't mention authentication needs (e.g., for private registries), rate limits, whether it overwrites existing images, what happens on failure, or the expected output format. This leaves significant gaps for a tool that interacts with external registries.
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 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 the essential function.
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 (network-dependent, potential authentication, side effects) and the lack of annotations and output schema, the description is insufficient. It doesn't explain what 'pull' entails behaviorally (e.g., downloads layers, updates local cache), success/failure conditions, or output details, leaving the agent with incomplete context for reliable 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%, with the single parameter 'image' well-documented in the schema as 'Image name with optional tag (e.g., 'nginx:latest')'. The description adds no additional parameter information 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('pull') and resource ('Docker image from a registry'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_images' or 'run_container' which might also involve Docker images, leaving some ambiguity about when this specific pull operation is needed versus other image-related 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. With siblings like 'list_images' (to check existing images), 'run_container' (which might pull images automatically), and 'create_container' (which might require images), there's no indication of prerequisites, typical workflows, or when pulling is necessary versus optional.
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. 'Remove' implies a destructive operation, but the description doesn't clarify that this permanently deletes the container, what happens to running containers (hinted at by force parameter but not explained), or whether removal is irreversible. For a destructive tool with zero annotation coverage, this is inadequate behavioral transparency.
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 any unnecessary words. It's perfectly front-loaded and every word earns its place. This is an excellent example of conciseness for a simple tool.
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 this is a destructive operation with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'remove' entails (permanent deletion), what happens to associated resources, potential side effects, or what the tool returns. For a 3-parameter tool that performs irreversible changes, more contextual information is needed.
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 fully documents all three parameters (containerId, force, volumes) with their types, descriptions, and defaults. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Remove a Docker container' clearly states the action (remove) and resource (Docker container), making the purpose immediately understandable. It distinguishes from siblings like stop_container (which stops but doesn't remove) and list_containers (which only lists). However, it doesn't explicitly mention that this is a destructive deletion operation versus other container management actions.
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., container must be stopped unless force=true), when to choose remove_container over stop_container, or what happens to associated resources. With multiple sibling tools for container management, this lack of comparative guidance 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.
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 ('Stop') but doesn't clarify critical details: whether this is a graceful stop versus force kill, what happens to container resources after stopping, if it requires specific permissions, or what the response looks like (e.g., success/failure indicators). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It front-loads the core action and target, making it highly efficient and easy to parse. Every word earns its place by conveying essential purpose without redundancy.
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 a mutation tool (stopping a container) with no annotations and no output schema, the description is incomplete. It lacks behavioral details (e.g., side effects, error handling) and usage context, which are crucial for an agent to invoke this tool correctly and safely. The high schema coverage doesn't compensate for these gaps in operational guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what the input schema already provides. Since schema description coverage is 100%, with clear documentation for both 'containerId' and 'timeout', the baseline score of 3 is appropriate. The description doesn't compensate with additional context like format examples or usage tips.
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 ('Stop') and target ('a running Docker container'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'remove_container' or 'start_container', but the verb 'Stop' is specific enough to imply halting execution rather than deletion or initiation.
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., the container must be running), exclusions (e.g., not for stopped containers), or comparisons to siblings like 'remove_container' for deletion or 'start_container' for restarting. This leaves the agent to infer usage from context 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 the full burden of behavioral disclosure. 'List Docker networks' implies a read-only operation, but it doesn't specify what information is returned (e.g., network names, IDs, types), whether there are rate limits, authentication requirements, or how results are formatted (e.g., JSON, plain text). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words ('List Docker networks'), which is front-loaded and wastes no space. For a simple tool with no parameters, this is appropriately sized and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavior, usage context, or output format. Without annotations or output schema, the agent must infer these aspects, making this description incomplete for optimal use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it meets the baseline expectation. No points are deducted since there are no parameters to document.
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 'List Docker networks' clearly states the verb ('List') and resource ('Docker networks'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_containers' or 'list_images' beyond the resource name, which keeps 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.
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. There are multiple list-related siblings (list_containers, list_images, list_volumes), but the description doesn't explain when to choose networks over those or mention any prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It implies a read-only operation (listing) but doesn't cover critical aspects like permissions required, rate limits, output format (e.g., JSON list), or error conditions (e.g., Docker not installed). 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 extremely concise ('List Docker volumes')—a single phrase with no wasted words. It's front-loaded with the core action and resource, making it easy to parse. This efficiency is ideal for a simple listing tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally complete. It identifies the resource but lacks context about behavior, output, or integration with siblings. For a basic read operation, it's adequate but leaves gaps in usage and transparency that could hinder an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage (empty schema), so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, but it also doesn't imply any hidden parameters or constraints. Baseline 4 is given for zero-parameter tools where the schema fully covers the absence of inputs.
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 'List Docker volumes' clearly states the verb ('List') and resource ('Docker volumes'), making the purpose immediately understandable. It distinguishes from siblings like 'list_containers' and 'list_images' by specifying volumes. However, it lacks specificity about scope (e.g., all volumes vs. filtered), preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., Docker daemon running), compare to other listing tools (e.g., 'list_containers'), or specify use cases (e.g., checking available storage). This leaves the agent with minimal context for decision-making.
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 mentions the tool creates and starts containers, it lacks critical information about permissions needed, whether this is a destructive operation (e.g., if a container with the same name exists), resource implications, error handling, or what happens on failure. For a complex container management tool, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just two sentences that are front-loaded and zero waste. Every word earns its place by stating the action and providing usage guidance 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 complexity (8 parameters with nested objects), no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, error conditions, side effects, or behavioral nuances needed for a container execution tool. The description should provide more context about the operation's 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%, so the schema already documents all 8 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for any gaps.
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 ('run a container') and specifies it involves both creation and starting, which distinguishes it from siblings like 'create_container' and 'start_container'. However, it doesn't explicitly contrast with these specific alternatives, missing full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating this is the 'preferred method for starting containers', which implies when to use it over alternatives like 'create_container' followed by 'start_container'. However, it doesn't explicitly mention when NOT to use it or detail specific scenarios where other tools might be better.
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 'Start' implies a state-changing operation, it doesn't describe permissions needed, whether this affects container data, error conditions (e.g., if container doesn't exist), or what happens on success. For a mutation tool with zero annotation coverage, 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and uses precise technical language appropriate for Docker operations.
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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after starting (does it return container status? success confirmation?), error conditions, or behavioral nuances. Given the complexity of container operations and lack of structured metadata, more context is needed.
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%, with the single parameter 'containerId' well-documented in the schema as 'Container ID or name'. The description doesn't add any parameter details beyond what the schema provides, so 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Start') and resource ('a stopped Docker container'), using precise technical terminology. It distinguishes from siblings like 'stop_container', 'run_container', and 'create_container' by focusing exclusively on restarting already-existing 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 context by specifying 'a stopped Docker container', suggesting it should only be used on containers that are currently stopped. However, it doesn't explicitly state when NOT to use it (e.g., for running containers or creating new ones) or name specific alternatives like 'run_container' for starting new containers.
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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