Machinepulse

Get Package Comparison

get_package_comparison

Read-onlyIdempotent

Compare npm/PyPI download activity for up to 20 packages — last 30 days: total, latest day and average (a longer list is cut and says so). Read-only aggregation of daily-collected observatory data; no side effects. Package download days may be missing (npm/PyPI reporting delay); missing days are null with notes, never fake zeros. Use when the user wants to compare package popularity side by side; for a single package's history use get_npm_trends or get_pypi_trends.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "packages": "<packages>"
    },
    "name": "get_package_comparison"
  }
}

Input Schema

Name	Required	Description	Default
`packages`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive, and the description still adds value beyond them: it is an aggregation over daily-collected observatory data, and missing download days are returned as null with notes rather than fake zeros. That data-quality caveat is exactly the kind of behavior an agent needs to interpret results correctly.

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?

Front-loaded with what it does and the time window, then caveats, then sibling routing; no filler. The heavy use of parenthetical asides makes it denser than it needs to be, but every sentence carries real 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?

An output schema exists, so return shapes need no explanation, yet the description still names the measured dimensions (total, latest day, average). Combined with the null-handling note and the cap, an agent can call this and interpret results without guessing.

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 0% for the single `packages` array, but the description compensates with the 20-item cap, the accepted ecosystems (npm/PyPI), and the truncation semantics. It does not specify whether scoped npm names or exact PyPI casing are expected, which is the remaining gap.

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 specific verb and resource ("Compare npm/PyPI download activity") plus scope (up to 20 packages, last 30 days) and the three metrics returned. It is immediately distinguishable from the single-package siblings get_npm_trends and get_pypi_trends.

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?

Explicit routing: "Use when the user wants to compare package popularity side by side; for a single package's history use get_npm_trends or get_pypi_trends." It also states the overflow behavior (a longer list is cut and says so), so the agent knows what happens past 20.

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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