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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.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive. Description adds that partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed lists timeouts. No contradictions.

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?

Single paragraph is reasonably concise for the amount of information. Front-loaded with purpose, then details. Could be slightly more structured but no wasted sentences.

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?

For a tool with no output schema, the description thoroughly explains return structure: summary block fields, per-advisory detail, links, alternative versions. Also covers edge cases like partial failures and timeouts.

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 has 100% coverage for both parameters. Description adds that scoped packages are accepted and version defaults to latest. Also explains how parameters are used in the composite check.

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 does a composite check for adding an npm package, covering license, advisories, version history, and bundle size. It is distinct from all sibling tools listed.

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 states when to use: 'whenever an agent asks is X safe / popular / small or what does adding lodash cost me'. It also notes ecosystem limitation and directs to deps.dev for other ecosystems.

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

A3.8/5.0
Disambiguation2/5

Multiple tools occupy the same general query/research space: ask_pipeworx, ask_pipeworx_beta (currently identical), ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, and recent_changes all overlap in what they can return. The descriptions are detailed and try to steer usage, but the boundaries are fuzzy enough that agents can easily select the wrong tool.

Naming Consistency3/5

All names are snake_case and descriptive, but there is no consistent verb_noun convention across the set. It mixes bare verbs (remember, recall, forget), noun phrases (entity_profile, recent_changes), domain-prefixed families (securitytrails_*, polymarket_*), and Pipeworx meta-tools (ask_pipeworx_*), so the pattern is predictable only within each family.

Tool Count2/5

35 tools is above the 25+ threshold for a coherent MCP surface, and many are highly specialized (Polymarket arbitrage, AI visibility checks, npm dependency scans) rather than core Securitytrails functionality. The set feels like multiple products merged into one rather than a well-scoped toolset.

Completeness3/5

The broad data-research workflows are well covered: routing, entity resolution, profiling, comparison, validation, subscriptions, memory, and basic Securitytrails domain lookups. But for a server named Securitytrails, there are obvious missing security-intelligence operations such as associated domains, IP/certificate enrichment, and broader DNS infrastructure enumeration.