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Security Fetch Package Vulnerabilities

security_fetch_package_vulnerabilities
Read-onlyIdempotent

Fetch all known CVEs for an open source package version or a batch of packages. Read-only. No side effects. Idempotent. Single-package mode: package (e.g. requests), version (e.g. 2.28.0), ecosystem (PyPI/npm/Maven/Go/Cargo/NuGet/RubyGems). package_name is accepted as an alias for package. Batch mode: packages array of {name, version, ecosystem} objects — max 50 per call. If packages array is provided and non-empty, batch mode is used and package/version/ecosystem are ignored. Batch returns {results: [...], partial: bool, failed_count: int}. Each result has vuln_count and vulnerabilities list. Returns CVE ID, severity, CVSS score, affected range, and fixed version. Use security_fetch_cve_detail for full detail by CVE ID. Use security_audit_sbom_vulnerabilities for SBOM files. Verified source: Google OSV.dev. 1-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_fetch_package_vulnerabilities", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageNoPackage name e.g. requests. Required in single-package mode.
versionNoPackage version e.g. 2.28.0. Required in single-package mode.
packagesNoBatch list of {name, version, ecosystem} objects. Max 50.
ecosystemNoPackage ecosystem: npm, pypi, cargo, go, maven, nuget. Required.
package_nameNoAlias for `package`. Accepted for consistency with other DataNexus tools.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / package_name
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Alias for `package`. Accepted for consistency with other DataNexus tools."
      +}
  2. Changed1 schema field changed
    • removedInput schema / properties / package_name
      Removed value: -{
      -  "anyOf": [
      -    {
      -      "type": "string"
      -    },
      -    {
      -      "type": "null"
      -    }
      -  ],
      -  "default": null,
      -  "description": "Alias for `package`. Accepted for consistency with other DataNexus tools."
      -}
  3. Changed1 schema field changed
    • addedInput schema / properties / package_name
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Alias for `package`. Accepted for consistency with other DataNexus tools."
      +}
  4. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the annotations, the description discloses the 1-hour cache, the verified OSV.dev source, batch partial/failed_count semantics, and the fact that batch mode ignores package/version/ecosystem. This adds meaningful behavioral context without contradicting the read-only, idempotent 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 longer than average but well-organized, front-loading the core purpose and then structuring details by mode, return shape, and alternatives. Some phrases like 'Read-only. No side effects. Idempotent.' restate annotations, and the closing report_feedback boilerplate adds length without aiding tool selection.

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?

For a dual-mode tool with five optional parameters and a rich result shape, the description covers mode selection, per-mode parameters, batch limits, return fields, data source, caching, and sibling tools. An agent has all essential information needed to call it correctly.

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%, so the baseline is 3, but the description adds important semantics: mode-dependent precedence, the 50-item batch cap, and the package_name alias. It also gives concrete examples and includes RubyGems, which the schema's ecosystem property text does not list.

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 opens with a specific action and object: 'Fetch all known CVEs for an open source package version or a batch of packages.' It also explicitly names sibling tools for adjacent use cases, distinguishing this tool from security_fetch_cve_detail and security_audit_sbom_vulnerabilities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

The description clearly defines single-package and batch modes and the condition that selects batch mode: a non-empty packages array. It also directs the agent to security_fetch_cve_detail for full CVE detail and security_audit_sbom_vulnerabilities for SBOM files, giving explicit routing 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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