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container_update

Update resource limits on a running container without recreating it. Adjust memory, CPU, and restart policies immediately via cgroups.

Instructions

Update resource limits on a container without recreating it.

Changes take effect immediately on Linux (cgroups); not all fields are updatable on every platform. Common updates keys: mem_limit (bytes, e.g. 134217728 for 128 MB), memswap_limit (memory+swap in bytes; -1 = unlimited), cpu_shares (relative weight, default 1024), cpu_period / cpu_quota (microseconds for CFS throttling), cpuset_cpus (e.g. "0-1"), restart_policy (dict with Name such as "on-failure"/"always"/"unless-stopped" and optional MaximumRetryCount). To change image, env, or volumes the container must be recreated (container_remove + container_run).

args: id_or_name - Container id or name to update updates - Resource fields to update; see description for valid keys returns: dict - The container's full inspect payload after the update

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
updatesYes
id_or_nameYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate mutating but non-destructive behavior; the description adds valuable context such as immediate effect on Linux cgroups, cross-platform variability, and that the return is the full inspect payload. It does not enumerate which fields are platform-dependent or failure behavior, but the added context goes beyond the annotations.

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 well-structured and front-loaded: main purpose first, then caveats and alternatives, then key-value details, and finally args/returns. Every sentence contributes useful information, and the key list is compact yet detailed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description includes the return type and enough parameter detail for common use cases. It could be more complete by specifying which fields are platform-dependent or the behavior when an unsupported field is provided, but it covers the primary scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description fully compensates by explaining id_or_name as the container identifier and detailing the updates object with common keys, units, examples, and enum-like values for restart_policy. This is much more than the bare schema provides and enables correct invocation.

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 tool updates resource limits on an existing container without recreating it, which is a specific verb+resource combination. It also distinguishes itself from siblings by explicitly noting that image, env, or volume changes require container_remove + container_run.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit when-to-use context: apply resource limit changes in place. It also gives a clear when-not-to-use with named alternatives (container_remove + container_run) for image/env/volume changes, plus a platform caveat about updatable fields.

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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