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Marketplace Trust Check

marketplace_check
Read-onlyIdempotent

Check package trust before installation by querying npm or PyPI registries and cross-referencing threat intelligence for CVEs and download stats.

Instructions

Pre-install trust check for an MCP server package.

    Queries the package registry (npm or PyPI) for metadata and
    cross-references against the agent-bom MCP threat intelligence registry.
    Returns trust signals including download count, CVE status, and
    registry verification.

    Args:
        package: Package name to check.
        ecosystem: 'npm' or 'pypi'. Defaults to 'npm'.

    Returns:
        JSON with name, version, ecosystem, cve_count, download_count,
        registry_verified, and trust_signals.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesPackage name, e.g. 'express', 'langchain'.
ecosystemNoPackage ecosystem: 'npm' or 'pypi'.npm

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds behavioral context: querying registries, cross-referencing threat intel, and returning trust signals. It does not contradict annotations and provides additional detail about the process, though it omits potential rate limits or error handling.

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 front-loaded with a one-line summary followed by structured paragraphs. Every sentence serves a purpose: defining the action, explaining the method, listing arguments, and summarizing return values. No unnecessary words or repetition.

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 simple two-parameter tool and the presence of an output schema (described in the docstring), the description covers the core functionality, data sources, and return fields. It could be more complete by mentioning error behavior or edge cases (e.g., package not found), but for a straightforward check tool, it is nearly complete.

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

Parameters3/5

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

Schema coverage is 100%, with clear descriptions for both parameters. The description repeats 'Package name' and 'Package ecosystem' but adds examples ('express', 'langchain') and default behavior. This adds marginal value beyond the schema, which already documents the parameters thoroughly.

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 'Pre-install trust check for an MCP server package' and specifies it queries npm or PyPI registries and cross-references against a threat intelligence registry. The verb 'check' and resource 'trust of package' are precise, and it distinguishes from sibling tools like registry_lookup or verify by focusing on pre-install trust.

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 indicates usage before installation ('Pre-install trust check') and the supported registries (npm, PyPI). However, it does not explicitly state when not to use this tool or mention alternatives (e.g., registry_lookup for direct metadata, policy_check for policy evaluation). The context is clear but lacks exclusion guidance.

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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