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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. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description goes beyond annotations by disclosing partial failure behavior (bundlephobia first measurement can take 5-30s, sources_failed lists timeouts), the non-atomic nature across sources, and the exact return summary fields. This adds significant behavioral context beyond the structured 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 long but information-dense, with a clear progression: purpose, usage triggers, return fields, ecosystem scope, and failure modes. Every sentence contributes unique value for a composite tool. It is not overly verbose given the complexity, though it could be tightened slightly without losing critical information.

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 no output schema, the description carries the full burden of explaining the return payload, and it does so thoroughly: it lists the summary fields, per-advisory details, links, and alternative versions. It also covers timeout behavior, partial failures, and ecosystem limitations. For a tool of this complexity, the description is remarkably complete.

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 description coverage is 100%, with both 'package' and 'version' well-documented in the schema. The description adds marginal value by framing 'version' as optional and defaulting to latest, and by mentioning scoped packages, but this is largely redundant with the schema. The description doesn't add deeper parameter-level semantics beyond the schema, so 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?

The description clearly states it is a composite check for 'should I add this npm package' and explicitly lists the data sources (deps.dev, bundlephobia) and the decision context. It distinguishes itself from siblings by being the only npm package evaluation tool, with a specific verb and resource ('scan' + 'dependency').

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 provides explicit trigger conditions ('whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"') and also gives an explicit exclusion/alternative for non-NPM ecosystems ('PyPI / Maven / Cargo / Go fall under deps.dev:version directly'). This is excellent guidance for tool selection.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation2/5

The ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded trio are three variants of the same router — and the beta variant is explicitly stated to be identical to the stable one right now, making mis-selection nearly inevitable. The six polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker, polymarket_kalshi_spread) also have subtly overlapping boundaries where an agent could easily grab the wrong one.

Naming Consistency4/5

Nearly all tools use snake_case with a clear verb_noun or noun_compound shape (get_company_facts, resolve_entity, recent_changes, polymarket_edges). Minor deviations: the bare-verb memory trio (remember/recall/forget), the brand-style ask_pipeworx* naming, and a mix of verb-first vs. entity-first ordering, but the overall pattern is readable and predictable.

Tool Count3/5

34 tools is well above the typical well-scoped range, but the server's actual scope is enormous — a universal structured-data gateway, prediction-market suite, memory system, subscription system, and utility tools. However, the count feels inflated by genuine redundancy: ask_pipeworx_beta currently duplicates ask_pipeworx, and the polymarket cluster could plausibly be consolidated into fewer tools.

Completeness4/5

Each sub-domain has strong lifecycle coverage: entity resolution (resolve_entity, search_companies), company analysis (get_company_facts/filings, entity_profile, recent_changes, compare_entities), full CRUD for both memory and subscriptions, and an exhaustively covered prediction-market domain (research, edges, arb, fill risk, tracking, cross-venue). Minor gaps exist — there's no direct single-filing document fetch tool (search_within implies fetching via the gateway but no explicit getter), and the AI-visibility tools lack historical tracking — but these are workaround-able rather than blocking.