Skip to main content
Glama

Openaire

by io.github.pipeworx-io

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. Added

TDQS

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint false), the description adds important behavioral details: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed will list timeouts. No contradiction 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 well-structured: it starts with the composite nature, then usage guidance, then ecosystem scope, and ends with failure behavior and return fields. Every sentence adds value; no redundancy.

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?

Without an output schema, the description fully explains the return value structure, including specific fields like is_latest, license, advisory_count, bundle sizes, and alternative versions. It also covers failure behavior, making it complete for the tool's complexity (two params, composite logic).

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% and both parameters have descriptions. The description adds nuance: scoped packages accepted for 'package', and 'version' defaults to latest when omitted. This adds value beyond the schema, though the schema is already strong.

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 verb 'scan' and the resource 'dependency' (npm package). It says 'Composite should I add this npm package check' and specifies the fan-out to deps.dev and bundlephobia, distinguishing it from sibling tools that likely focus on broader or different topics.

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 usage guidance: 'Use whenever an agent asks is X safe / popular / small or what does adding lodash cost me.' It also states limitations: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly.' This tells the agent when to use this tool and when alternatives apply.

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

All Openaire toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation2/5

Several tools have heavily overlapping or explicitly duplicate purposes: ask_pipeworx_beta is described as currently identical to ask_pipeworx, while ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language queries to similar lookup pipelines. The Polymarket tools also blur together (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk), and scan_competitor_ai_presence is just a wrapper around ai_visibility_check.

Naming Consistency3/5

There are readable verb-led names like search_publications, get_project, resolve_entity, and validate_claim, but the set mixes conventions with noun-phrase names like entity_profile, recent_alerts, polymarket_edges, and pipeworx_trending. The lack of a single verb_noun pattern makes the surface feel inconsistent, though each family is internally recognizable.

Tool Count2/5

At 37 tools, this is well beyond the 25+ threshold where an agent starts paying significant selection and context cost. The broad domain could justify some breadth, but many tools are meta-wrappers or near-duplicates (ask_pipeworx_beta, compare_entities, entity_profile, deep_research) that inflate the count.

Completeness4/5

Within its main subdomains, the surface is fairly complete: OpenAIRE search has matching get_project/get_research_product retrieval, memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and there are discovery/onboarding helpers like suggest_questions and discover_tools. Minor gaps exist (e.g., no direct generic Polymarket market quote tool, no memory update besides overwrite), but no major workflow is a dead end.

Resources