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pull-image

Pull an image into a local machine's cache to prepare it for use, without transferring to remote targets. Specify the machine and image name to make it available locally.

Instructions

Pull an image into a running machine's local cache. Local only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesMachine name
imageYes
targetNoWhich fleet to talk to. local is smolvm serve on this host; cloud is smol cloud at SMOL_CLOUD_URL.local

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
osYes
sizeYes
digestYes
referenceYes
layerCountYes
architectureYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
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 and the 'local only' scope, but it does not disclose side effects (e.g., whether existing cache entries are overwritten), network requirements, authentication needs, or failure modes. For a pull operation this is a notable 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 sentence that is concise and front-loads the core action. It avoids unnecessary detail, though it could have included a bit more behavioral context without sacrificing brevity. It is appropriately sized for a simple pull operation.

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 moderate complexity (3 parameters, an enum, and an output schema) and the complete absence of annotations, the description is too sparse. It does not explain return values, error conditions, or the distinction between local and cloud behavior beyond the one-word 'Local only'. An agent would have to rely on the schema and runtime feedback to understand the full behavior.

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

Parameters2/5

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

The input schema describes 'name' and 'target' but leaves 'image' undocumented. The description adds no parameter-level detail beyond what the schema already provides, and it fails to compensate for the missing 'image' description. With only 67% schema coverage, the description should have clarified the image parameter but did not.

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 states a clear verb ('pull') and resource ('image') with a destination ('into a running machine's local cache'). It also adds a scoping note ('Local only') that distinguishes it from potential cloud operations. However, since no sibling tool performs pulling, the differentiation is implicit rather than explicit.

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 minimal context about when to use this tool: it implies it is for pulling into a running machine's local cache. There is no explicit guidance on when not to use it or mention of alternatives, even though the target parameter distinguishes local vs cloud. The agent is left to infer that this is the only tool for image pulling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.