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docker_run

Run Docker containers with configurable options like ports, volumes, environment variables, and resource limits to execute applications in isolated environments.

Instructions

Run a Docker container

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesDocker image to run
nameNoContainer name
commandNoCommand to run in container
argsNoCommand arguments
portsNoPort mappings (e.g., ["8080:80", "3000:3000"])
volumesNoVolume mounts (e.g., ["/host/path:/container/path"])
envNoEnvironment variables as key-value pairs
detachNoRun container in background
removeNoRemove container when it exits
interactiveNoKeep STDIN open
ttyNoAllocate a pseudo-TTY
networkNoNetwork to connect container to
working_dirNoWorking directory inside container
userNoUsername or UID (format: <name|uid>[:<group|gid>])
memoryNoMemory limit (e.g., "512m", "2g")
cpusNoCPU limit (e.g., "0.5", "2")
restartNoRestart policy (no, on-failure, always, unless-stopped)
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. 'Run a Docker container' implies execution and potential side effects, but it doesn't mention safety considerations, permissions required, whether it's interactive or background by default, or how errors are handled. For a tool with 17 parameters and no annotations, 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 ('Run a Docker container') that front-loads the core action without unnecessary words. It's appropriately sized for its purpose, with zero wasted verbiage.

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 (17 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain what happens when the tool runs (e.g., container lifecycle, output format, error behavior), leaving significant gaps for the agent to navigate a potentially destructive operation.

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 each parameter well-documented in the schema itself (e.g., 'Docker image to run' for 'image'). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high 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 'Run a Docker container' clearly states the verb ('Run') and resource ('Docker container'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'docker_build' or 'docker_compose', which would require explicit comparison to achieve 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. With multiple Docker-related siblings (e.g., docker_build, docker_compose, docker_containers), there's no indication of appropriate contexts, prerequisites, or exclusions, leaving the agent to infer usage.

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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