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msaad00

agent-bom

by msaad00
OverviewSchemaRelated ServersScoreDiscussions
Python

Generate SBOM

generate_sbom
Read-onlyIdempotent

Generate a standards-compliant SBOM for AI agent setups by discovering agent configs and MCP server dependencies, outputting in CycloneDX or SPDX format.

Instructions

Generate a Software Bill of Materials (SBOM) for your AI agent setup.

    Discovers AI agents and MCP servers, extracts all package dependencies,
    and generates a standards-compliant SBOM.

    Args:
        format: SBOM format — "cyclonedx" (CycloneDX 1.6) or "spdx" (SPDX 3.0).
        config_path: Path to a specific MCP config directory.
                     If not provided, auto-discovers all local agent configs.

    Returns:
        JSON string containing the SBOM in the requested format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoSBOM format: 'cyclonedx' (CycloneDX 1.6) or 'spdx' (SPDX 3.0).cyclonedx
config_pathNoPath to MCP client config directory. Auto-discovers all if omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds behavioral context about discovering agents and servers, extracting dependencies, and generating a standards-compliant SBOM, going 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.

Conciseness4/5

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

The description is well-structured with clear sections for Args and Returns, and front-loaded purpose. It could be slightly more concise, 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?

Given the tool's low complexity (2 optional params, no enums), output schema presence, and annotations covering safety, the description is complete enough for an agent to use effectively.

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 coverage is 100%, but the description adds value by explaining that config_path auto-discovers if omitted, which is not fully conveyed by the schema alone.

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 verb 'generate', the resource 'Software Bill of Materials (SBOM)', and the context 'for your AI agent setup'. This is specific and distinguishes the tool from siblings, none of which focus 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 Guidelines3/5

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

The description implies usage via the parameter docs (e.g., 'If not provided, auto-discovers all local agent configs') but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria.

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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