NPMScan

Analyze an npm package install script

analyze_install_script

Read-only

Statically scans a package's preinstall/install/postinstall/prepare lifecycle scripts AND the file(s) they reference — fetched directly from the published tarball, not just the command string in package.json — against npmscan's documented red-flags rubric (/docs/red-flags): child_process use, network calls, access to sensitive paths/env (.ssh, .aws, .npmrc, *TOKEN/*KEY), obfuscation, remote binaries hosted off trusted CDNs, writes to HOME, Discord/Telegram/Pastebin exfil endpoints, eval on decoded strings, chmod+exec of downloaded binaries, and CI-metadata telemetry — plus a possibleTyposquatOf name check. Returns a weighted totalScore and riskTier ('none'/'low'/'moderate'/'high'/'critical'). This is a heuristic static scan, not proof of malice or a guarantee of safety: it doesn't execute any code, can't see behavior gated on runtime conditions, and does NOT check maintainer/ownership history (a separate red-flags signal this tool doesn't cover). Use get_package/get_package_version first for the raw script listing; use this when you need to know what an install script actually does, not just that one exists.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	Exact npm package name, e.g. "lodash" or "@scope/name"
`version`	No	Exact version to analyze; omit to use the latest published version

Output Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`version`	Yes
`findings`	Yes
`riskTier`	Yes
`scanNote`	Yes
`npmscanUrl`	Yes
`totalScore`	Yes
`filesScanned`	Yes
`lifecycleScripts`	Yes
`hasLifecycleScripts`	Yes
`possibleTyposquatOf`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

AddedSep 1, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds substantial behavioral context: it is a heuristic static scan, does not execute code, cannot see runtime-gated behavior, and is not proof of safety. This goes beyond the annotation baseline and manages expectations well.

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 long but every clause carries information: scope, rubric, output, limitations, and usage guidance. It is front-loaded with the core scan scope before diving into rubric details, and the length is justified by the tool's complexity.

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 an output schema present and a description that names the return fields (totalScore, riskTier), defines limitations, lists exclusions, and provides usage ordering, nothing needed for correct invocation or interpretation 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 coverage is 100% with clear descriptions for both name and version. The description adds little parameter-specific meaning beyond confirming it fetches from the published tarball, but since the schema already documents the parameters fully, baseline 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?

States a specific verb ('statically scans') and resource (npm package lifecycle scripts plus referenced files fetched from the tarball), and enumerates the rubric categories. It clearly differentiates from sibling tools by specifying what it analyzes and what it returns (totalScore, riskTier).

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?

Explicitly instructs to use get_package/get_package_version first for raw script listings and defines when this tool is needed ('when you need to know what an install script actually does'). It also states what it does not cover (maintainer/ownership history), helping an agent avoid misusing it.

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

A4.4/5.0

Disambiguation4/5

Most tools have clearly distinct scopes, such as flat vs. transitive vulnerability checks and per-package vs. GitHub-repo audits. The main ambiguity is that several tools all ultimately report OSV/NVD findings or perform install-script risk checks, though the descriptions do draw clear boundaries and include cross-references to steer selection.

Naming Consistency5/5

Every tool follows a consistent lowercase snake_case verb_noun pattern, e.g. analyze_install_script, check_maintainer_changes, prioritize_remediation. The naming is predictable and makes the action and target of each tool immediately clear.

Tool Count3/5

At 22 tools, the surface is at the heavy end of the rubric and pushes beyond the typical 3-15 well-scoped range. The tools are individually purposeful and broad in coverage, but the count is high enough that an agent faces a large decision space and several workflows that overlap or compose in complex ways.

Completeness5/5

The set covers the full npm supply-chain assessment lifecycle: discovery, metadata lookup, vulnerability scanning, transitive dependency analysis, license checks, install-script analysis, maintainer and provenance checks, SBOM generation, dependency diffs, upgrade simulation, remediation prioritization, and alternative suggestion. There are no obvious dead ends or major missing operations for the stated domain.

Resources

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