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Glama

Un Sdg

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. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate safe, read-only, idempotent behavior. Description adds operational details: fan-out across two services, potential delay (5-30s for bundlephobia first measurement), and graceful degradation with sources_failed field.

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?

Description is informative and front-loaded with purpose. Every sentence adds value, though slightly verbose. Could be tightened without losing clarity, but overall well-structured.

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?

No output schema, but description thoroughly explains return structure: summary block with specific fields, per-advisory detail, links, alternative versions. Also covers failure modes and data sources. Complete for a composite tool.

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 covers both parameters with descriptions. Description reinforces that 'package' accepts scoped packages and 'version' defaults to latest, adding slight clarity beyond schema. With 100% schema coverage, baseline is 3, and description adds marginal value, earning a 4.

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 it's a composite check for npm packages, listing specific data sources (deps.dev, bundlephobia) and what it evaluates (license, advisories, bundle size, etc.). It distinctly differs from sibling tools by focusing on dependency evaluation.

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 says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. Also notes ecosystem limitation (NPM only) and points to alternatives (deps.dev:version for other ecosystems). Describes partial failure behavior gracefully.

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

A3.9/5.0
Disambiguation3/5

Several tools occupy overlapping territory: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research are all query routers, and the six Polymarket tools have closely related purposes. The descriptions are unusually detailed and do help, but an agent could still easily pick the wrong entry point.

Naming Consistency4/5

Almost all tools follow a clean lower_snake_case convention with recognizable prefixes like list_, ask_pipeworx, and polymarket_. A few names like entity_profile, recent_changes, and recent_alerts are noun phrases rather than verb-first, but the overall pattern is predictable and readable.

Tool Count2/5

36 tools is well above the threshold where a server starts to feel bloated, and many are variants of the same underlying query/research capability. This appears to be a full platform surface rather than a focused server, which creates a heavy and confusing toolset for agents to navigate.

Completeness4/5

The SDG-specific portion is reasonably complete: goals, indicators, series, geographic areas, and data retrieval are all covered. The broader Pipeworx layer also covers querying, grounded answers, deep research, entity comparisons, prediction markets, subscriptions, and memory, with only minor gaps such as no batch SDG data fetch or full-text indicator search.

Resources