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Package Info (deps.dev)

depsdev.insights.package
Read-onlyIdempotent

Access package metadata from Google deps.dev across six ecosystems—npm, PyPI, Go, Maven, Cargo, NuGet—including all versions and default version, providing a unified cross-ecosystem view beyond individual registry APIs.

Instructions

Get package metadata from Google deps.dev — all versions, default version, ecosystem. Covers npm, PyPI, Go, Maven, Cargo, NuGet (50M+ package versions). Complements npm/PyPI registries with cross-ecosystem unified view.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
systemYesPackage ecosystem: npm, pypi, go, maven, cargo, or nuget
packageYesPackage name (e.g. express, requests, gin-gonic/gin, log4j-core)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior4/5

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

Annotations (readOnlyHint, idempotentHint) already indicate safety; the description adds scale (50M+ versions) and data scope (versions, default version, ecosystem). No contradictions. Could mention rate limits or pagination, but acceptable.

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?

Two concise sentences: first declares core purpose, second adds ecosystem coverage and positioning. No filler, every sentence earns its place.

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 output schema exists, the description adequately covers input and high-level output. It could specify output shape more precisely, but the combination of annotations and schema makes it sufficient for an agent to decide.

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 descriptions (system enum, package examples) cover 100% of parameters. The description only reinforces what the schema provides, adding no new parameter meaning. Baseline score of 3 applies.

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 tool retrieves package metadata (all versions, default version, ecosystem) from deps.dev. It specifies supported ecosystems and positions the tool as a cross-ecosystem complement to individual registries, distinguishing it from siblings like depsdev.insights.advisories.

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 implies usage for cross-ecosystem package lookup and contrasts with npm/PyPI registries, but does not explicitly state when not to use or name specific alternatives. Still, the context is clear enough for an agent to differentiate.

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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