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package-intel-mcp

package_dependencies

List the direct dependencies of a specific package version (defaults to latest), via deps.dev. Lets an agent understand what a package pulls in before adding it. Ecosystems: npm, pypi, cargo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesExact package name as published in that registry, e.g. express for npm, requests for pypi, serde for cargo.
versionNoOptional; defaults to the latest/default version
ecosystemYesPackage registry to look in. One of: npm, pypi, cargo.

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It usefully discloses that the tool queries deps.dev, that it is a read-only listing operation, and that version defaults to the latest. It does not discuss potential network dependencies or rate limits, but the non-mutating nature is clear from 'List'.

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 three tight sentences with no filler. The core action is front-loaded, the default-version behavior is included, and the supported ecosystems are listed compactly.

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?

For a simple read-only dependency listing tool, the description provides the necessary purpose, data source, ecosystem scope, and default version behavior. There is no output schema, but the return value is strongly implied by the stated purpose and tool name.

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 all three parameters already described in the input schema. The description adds minimal extra semantic value beyond restating the ecosystem choices and the default-version behavior, so the baseline score of 3 is appropriate.

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 verb and resource: 'List the direct dependencies of a specific package version.' It also distinguishes itself from sibling tools by focusing on direct dependencies and naming the supported ecosystems, so an agent can separate it from package_info or package_versions.

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 phrase 'Lets an agent understand what a package pulls in before adding it' gives clear contextual guidance for when to use the tool. However, it does not explicitly mention when not to use it or compare it with alternatives such as package_health or package_info.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct aspect of package intelligence: dependencies, download statistics, health, metadata, search, and version history. There is no overlap in purpose, and the descriptions clearly differentiate what each tool returns.

Naming Consistency5/5

All tools follow the consistent pattern 'package_' plus a descriptive noun (dependencies, downloads, health, info, search, versions). The naming is uniform, snake_case, and immediately conveys each tool's function.

Tool Count5/5

Six tools is well within the ideal 3–15 range and matches the server's single focus on package evaluation. Each tool covers a necessary facet without redundancy or bloat.

Completeness5/5

The tool surface covers the full lifecycle of package evaluation: discovering packages via search, inspecting metadata, checking version history, assessing popularity, and performing a composite health check including security advisories. No obvious gaps exist for the stated purpose.