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scout_sbom

Read-only

Generate a Software Bill of Materials (SBOM) for a Docker image in SPDX, CycloneDX, JSON, or list format. Specify image, platform, and format to retrieve component inventory.

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
Behavior5/5

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

Annotations indicate readOnlyHint=true, and the description adds critical behavioral info: SBOMs can be large and stdout may be truncated. It also details the return structure (dict with format, result, raw), going 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: a one-line purpose, a warning, a suggestion, and a clear args/returns section. Every sentence adds value, no fluff.

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?

Despite no output schema and simple parameters, the description covers all essential aspects: purpose, parameter semantics, return format, and a behavioral caveat. It is complete for an agent to use correctly.

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?

Input schema coverage is 0%, but the description compensates fully by explaining each parameter: image (image reference), format (with allowed values: spdx, cyclonedx, json, list), and platform. This adds meaning that the schema lacks.

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 'Generate a Software Bill of Materials (SBOM) for an image.' This is a specific verb and resource, and it distinguishes the tool from scout_compare, scout_cves, etc., by focusing on SBOM generation.

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 warns about potential truncation for large SBOMs and suggests using the command line with '-o file.json' if needed. While it doesn't compare to other tools, it provides a clear when-to-use guideline for the tool itself.

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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