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scout_sbom

Read-only

Generate a Software Bill of Materials (SBOM) for a Docker image. Supports SPDX, CycloneDX, JSON, and plain-text list formats, with optional platform specification.

Instructions

Generate a Software Bill of Materials (SBOM) for an image.

SBOMs can be large; captured stdout is subject to MAX_CLI_OUTPUT_BYTES and may be truncated for big images. If that's a concern, run docker scout sbom -o file.json … on the host and load the file separately.

args: image - Image reference format - SBOM format: "spdx" (default, SPDX JSON), "cyclonedx" (CycloneDX JSON), "json" (Scout's native JSON), "list" (plain-text package list) platform - Platform of the image to analyze returns: dict - {"format", "result", "raw": }. result is a parsed dict when format is "spdx"/"cyclonedx"/"json" and stdout parses cleanly; for "list" or a parse failure it's the raw text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
formatNospdx
platformNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, not contradicting. Description adds valuable behavioral details: stdout truncation warning, format behavior, return structure with parse success/failure handling. Adds context beyond annotations.

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?

Description is well-structured with an overview sentence followed by bullet-like argument details and return format. Some verbosity in the truncation explanation, but overall efficient.

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

Completeness5/5

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

No output schema exists; description fully compensates by explaining return dict structure and parse behavior. Covers truncation warning and alternative workflow, making the tool's behavior and output clear for an AI 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?

Schema has 0% coverage, so description carries full burden. It explains each parameter: 'image' as reference, 'format' with enumerated values, 'platform' as platform filter. Adds meaning beyond parameter names.

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?

Description clearly states the tool generates an SBOM for an image, which is distinct from sibling scout tools (compare, cves, quickview, recommendations). The verb 'generate' and resource 'SBOM for an image' are specific.

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?

Provides guidance on truncation issue and alternative to run command on host, but does not explicitly compare to other tools or state when to use SBOM over other scout commands. Usage context is partially covered.

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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