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Glama

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations: it explains the composite fan-out to two services, partial failure handling, timing for bundlephobia's first measurement, and details of the return structure. No contradictions with annotations.

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 relatively long but each sentence provides necessary detail. It front-loads the main purpose and then adds specifics. It could be tightened slightly, but overall it is efficient for the 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?

Given the complexity (composite check, multiple data sources, partial failures, timing), the description is thorough. It covers purpose, usage, limitations, graceful degradation, and return fields. No output schema exists, but the description adequately describes what is returned.

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 100% with descriptions for both parameters. The description adds context: version defaults to latest, scoped packages accepted, and the tool is npm-only. This adds value beyond the schema descriptions.

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 clearly states the tool is a composite check for evaluating adding an npm package, covering license, advisories, version history, and bundle size. It distinguishes itself from sibling tools by specifying the npm ecosystem and mentioning alternatives for other registries.

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?

The description explicitly tells when to use it: when an agent asks about safety, popularity, or size of a package. It also mentions alternatives for non-npm packages (deps.dev:version). While it doesn't list explicit exclusions, it provides clear context.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; multiple Polymarket tools) and many serve unrelated domains, making it hard for an agent to distinguish which tool to use for a given task, especially given the server's holiday theme.

Naming Consistency3/5

Most tool names follow a lowercase_with_underscores pattern, but the prefixes vary (ask_pipeworx, pipeworx_*, polymarket_*, etc.) and some names are less descriptive (e.g., process, run, execute-like vague verbs are absent, but still the naming lacks a unified convention across the broad set.

Tool Count2/5

35 tools is excessive for a server named 'Openholidays'. The vast majority of tools (e.g., SEC filings, Polymarket, npm scanning) are unrelated to holidays, making the tool count feel bloated and unfocused.

Completeness3/5

For the holiday domain, the server includes necessary tools (list_countries, list_subdivisions, public_holidays, school_holidays) and is complete. However, the server's actual scope is far broader, and many unrelated tools are present, which dilutes the completeness for its stated purpose.