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Rank a project's package vulnerabilities

package_vulns
Read-onlyIdempotent

Identify vulnerable package versions and prioritize fixes by severity, using KEV, EPSS, and CVSS to determine the smallest upgrade that resolves all.

Instructions

Checks up to 50 package versions (npm, PyPI, Go, Maven, crates.io, RubyGems, NuGet, Packagist, Pub, Hex) against OSV and ranks each package by its worst vulnerability (act_now, high, medium, low), with the smallest upgrade that fixes them all and each vulnerability's KEV, EPSS and CVSS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packagesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countsYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already convey read-only, idempotent, open-world, non-destructive behavior, so the description adds meaningful operational context: it queries OSV, supports up to 50 versions, uses specific severity labels, and includes upgrade and metric data. This goes beyond what annotations alone tell the agent.

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?

One dense sentence with no filler: it front-loads the core action, then packs in the limit, ecosystems, data source, ranking output, upgrade recommendation, and supporting metrics. Every clause contributes useful information.

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?

The tool has one parameter, a rich output schema, and strong annotations. The description supplies the remaining operational context: input limits, supported ecosystems, severity taxonomy, upgrade behavior, and metric fields. No critical detail needed to call it correctly is missing.

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 description coverage is 0%, so the description must compensate, and it does: it explains that the packages input should contain up to 50 package versions, lists possible ecosystems, and states what will be produced for each. It does not restate required fields like name, version, and ecosystem, but those are already clear in the schema.

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 names a specific action and resource: it 'Checks up to 50 package versions' against OSV and 'ranks each package by its worst vulnerability' with severity categories. It also names the supported ecosystems, which clearly separates it from sibling tools like recent_exploited or vuln_details.

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 clearly implies when to use the tool: when the user supplies package versions and wants vulnerability severity, upgrade paths, and KEV/EPSS/CVSS details. It does not explicitly state when not to use it or name alternative sibling tools, so it stops short of a 5.

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