Skip to main content
Glama

Package provenance

package_provenance
Read-onlyIdempotent

Who publishes this package, and is it a typosquat? Live npm or PyPI lookup: first-publish date and age, release count, latest version, maintainers/author, linked repo, plus a typosquat check against popular package names. Use when an agent is about to install or recommend an unfamiliar dependency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYespackage name, e.g. express or requests
ecosystemYesnpm or pypi

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: this is a live network lookup (freshness/latency implication) and it enumerates the fields returned, including a typosquat heuristic. It does not mention failure modes for unknown packages.

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 the two questions an agent actually has, then the data returned, then the usage condition. Dense but every clause carries information; the interrogative opener is slightly less efficient than a declarative verb phrase.

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?

With no output schema, the description compensates by enumerating the returned fields (first-publish date/age, release count, latest version, maintainers, linked repo, typosquat result) and the scenario that warrants a call. Nothing an agent needs to decide or invoke is missing.

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% with only two parameters, so the schema already documents name and the npm/pypi enum. The description reinforces the ecosystem scope but adds no syntax, format, or edge-case detail beyond it; 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 specific verb and resource (publishers of a package, typosquat status) plus the exact lookup source (live npm or PyPI). It is clearly distinguishable from the sibling domain_provenance because it names the artifact type it operates on.

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?

"Use when an agent is about to install or recommend an unfamiliar dependency" gives a concrete triggering condition. There are no explicit exclusions or alternatives named, but the context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources