NPMScan

Check an npm package for maintainer/ownership red flags

check_maintainer_changes

Read-only

Reconstructs a package's maintainer-change history straight from the npm packument — every published version carries the maintainers-list SNAPSHOT as it stood at that publish plus who actually ran npm publish (_npmUser), so diffing consecutive snapshots in publish-time order recovers exactly who was added or removed and when, with no extra API calls. Flags: (1) a maintainer added recently who then published a release shortly afterward on a package with real prior history — the account-takeover/hostile-handoff shape behind incidents like ua-parser-js, event-stream, and the 2025 chalk/debug ('qix') compromise; (2) a full, sudden replacement of the entire maintainer list; (3) a long-standing maintainer quietly dropped from the list; (4) a maintainer-list change that happened on npm's site AFTER the latest release — not yet tied to any published version, which is the more urgent case since it means access changed hands but nothing has shipped with it yet. Also cross-checks the declared GitHub repository: whether it still resolves to the same owner/name (a transfer/rename), whether it's reachable at all, and whether the latest npm release landed long after any real push activity there — repository.ownerLogin/ownerAvatarUrl name and show the CURRENT owning account (the new one after a transfer, not the one originally declared in package.json), with ownerAvatarUrl served from our own /api/github/avatar proxy rather than linking avatars.githubusercontent.com directly, both null whenever the repo check itself didn't reach GitHub. Use get_package/check_package_provenance first for the package's general health and publish-integrity signals; use this specifically for the 'who controls this package, and did that change recently' question. If this flags a newly added or fully turned-over maintainer, follow up with check_maintainer_blast_radius on that maintainer's username — it lists every other package the same account currently touches and flags a tight publish-time cluster across them, the 'did this compromise hit just one package or a dozen' question this tool can't answer on its own.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	Exact npm package name, e.g. "lodash" or "@scope/name"

Output Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`history`	Yes
`findings`	Yes
`riskTier`	Yes
`npmscanUrl`	Yes
`repository`	Yes
`totalScore`	Yes
`lookbackDays`	Yes
`currentMaintainers`	Yes

Schema Changelog

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

Changed3 schema fields changedSep 5, 2026

addedOutput schema / properties / repository / properties / ownerAvatarUrl
```
Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
```
addedOutput schema / properties / repository / properties / ownerLogin
```
Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
```

changedOutput schema / properties / repository / required

Previous value: -[
-  "checked",
-  "declaredRepository",
-  "currentFullName",
-  "transferred",
-  "archived",
-  "reachable",
-  "note"
-]New value: +[
+  "checked",
+  "declaredRepository",
+  "currentFullName",
+  "transferred",
+  "archived",
+  "reachable",
+  "ownerLogin",
+  "ownerAvatarUrl",
+  "note"
+]

AddedSep 1, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The description goes far beyond the readOnlyHint and destructiveHint annotations by revealing the internal method (diffing maintainer-list snapshots from the npm packument), the guarantee of no extra API calls, the exact red-flag heuristics, and the GitHub repository cross-checks including what the ownerAvatarUrl proxy does. It even discloses null behavior ('both null whenever the repo check itself didn't reach GitHub'). This is exemplary transparency for a read-only analysis tool.

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?

The description is long but information-dense; nearly every sentence adds a distinct fact or behavioral guarantee. It is front-loaded with the mechanism and flags before moving to GitHub checks and usage guidance. A minor grammar issue ('repository.ownerLogin/ownerAvatarUrl name and show the CURRENT owning account') and a somewhat long tail about avatar proxying prevent a perfect score, but overall the structure serves an agent well.

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?

Given the tool's complexity, the description covers the essential input, methodology, flags, output semantics, and follow-up workflow. The output schema exists and would provide the full field list, so the description need not enumerate every return value; it nonetheless clarifies candidate-specific fields like repository.ownerLogin and ownerAvatarUrl. No critical operational context is missing for correct invocation and interpretation.

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?

The input schema already documents the single 'name' parameter with a clear description and examples ('lodash' or '@scope/name'), so schema coverage is 100%. The tool description adds nothing beyond the tool's overall scope, which is acceptable because the parameter is trivial and fully documented in the schema. Baseline 3 is appropriate; no additional guidance is needed.

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 opens with a specific verb ('Reconstructs') and resource ('a package's maintainer-change history'), then enumerates four concrete flags that define the tool's unique value. It clearly distinguishes itself from siblings like get_maintainer_profile and check_package_provenance, and even names check_maintainer_blast_radius as a different follow-up tool. An agent can confidently know what this tool does and what it does not do.

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?

The description explicitly states when to use this tool: 'Use get_package/check_package_provenance first for the package's general health and publish-integrity signals; use this specifically for the who controls this package, and did that change recently question.' It also gives a concrete follow-up instruction to run check_maintainer_blast_radius when a specific flag condition is met. This is model usage guidance with both alternatives and exclusions.

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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