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JavaScript

package_health_checker

Check npm, PyPI, and Crates.io package health: deprecation, last publish, license, weekly downloads, maintainers, GitHub stars, and a 0-100 score in one row per package.

Instructions

Package health checker for npm, PyPI and Crates.io — deprecation, last publish date, licence, weekly downloads, maintainers, GitHub stars and a 0-100 health score, one row per package. Billed to your own Apify account: ~$0.002 per result (Apify free-plan price, lower on paid plans).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packagesYesPackages — Enter the packages to check, one row is returned per package. Prefix the name with the registry, e.g. npm:react, pypi:requests, crates:serde. Bare names such as react or @scope/name use the default registry below, and full registry URLs work too, e.g. https://pypi.org/project/requests/. Example: ["react"].
enrichGithubNoEnrich with GitHub data — Keep this on to add GitHub stars, forks, open issues, the archived flag and the last push date whenever the package points at a GitHub repository. Turn it off to run faster and avoid GitHub rate limits.
defaultRegistryNoDefault registry — Select which registry a bare package name belongs to, e.g. npm for react. Entries that already carry a prefix (pypi:requests) or a registry URL ignore this setting. Options: npm = npm (JavaScript); pypi = PyPI (Python); crates = Crates.io (Rust).npm

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose real behavioral traits: billing to the caller's own Apify account at ~$0.002/result, one row returned per package, and that GitHub enrichment triggers rate limits. It stops short of stating auth requirements, run/async semantics, or failure behavior.

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?

Two sentences, front-loaded with the capability and then the cost caveat; every clause earns its place. The long metric list and the trailing 'one row per package' clause are slightly crammed but not wasteful.

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 3-parameter scraper with no output schema and no annotations, the description compensates by enumerating returned fields and the cost model. It leaves out execution semantics (async run, timing) that an Apify actor tool would benefit from disclosing.

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 description coverage is 100%, so the schema already documents all three parameters in detail (prefix syntax, defaultRegistry enum, enrichGithub trade-off). The description adds no parameter-level syntax or default beyond that, so the baseline 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?

States a concrete verb+resource ('Package health checker for npm, PyPI and Crates.io') and enumerates the exact signals returned (deprecation, last publish, licence, downloads, maintainers, stars, 0-100 score). The registry-level scope clearly separates it from the repo-level sibling github_repo_health.

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?

No explicit when-to-use statement, prerequisites, or named alternatives. The use case (assessing dependency health before adoption) is only implied by the list of returned metrics and the per-result pricing note.

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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