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Doaj

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.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and non-destructive nature. The description adds behavioral details like partial failures, timeouts (5-30s), and sources_failed field. No contradiction.

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 information-dense. It is front-loaded with the key purpose. Could be slightly more concise, but the length is justified by the composite nature.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but the description lists return fields and explains partial failures. Covers essentials for an agent to use the tool correctly.

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%. The description adds meaning: explains scoped packages for 'package' and default 'latest' for 'version'. Provides context beyond schema.

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 npm packages covering license, advisories, version history, and bundle size. It distinguishes from siblings by specifying the npm ecosystem and mentioning alternative uses for other ecosystems.

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 when to use: 'Use whenever an agent asks 'is X safe / popular / small''. Also mentions when not to use (other ecosystems) and gives alternatives (deps.dev:version directly).

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

All Doaj toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tool clusters have overlapping purposes: the three ask_pipeworx variants are nearly identical, polymarket_edges and polymarket_arbitrage both scan for opportunities, and ai_visibility_check vs scan_competitor_ai_presence create confusion. Although descriptions are detailed, an agent could easily misselect among these.

Naming Consistency3/5

Most tools follow snake_case verb_noun (get_article, search_journals, resolve_entity), but there are brand-prefixed names (ask_pipeworx*, pipeworx_trending, pipeworx_feedback) and noun-phrase tools (entity_profile, bet_research) that break the pattern. The three ask_pipeworx variants are consistently named but confusable.

Tool Count2/5

35 tools is excessive for a coherent server, especially one where many tools are meta-routes (ask_pipeworx, deep_research) that could consolidate functionality. The count exceeds the 25-tool threshold for 'heavy' and includes several one-off tools (generate_llms_txt, scan_dependency) that don't fit the dominant data-access theme.

Completeness3/5

The DOAJ subset is complete for read-only search and retrieval, but the server lacks a clear domain: it mixes DOAJ, prediction markets, memory, and subscriptions. For the broader Pipeworx platform, there are some dead ends (e.g., no subscription editing, no raw historical market data, no batch tools), and the non-DOAJ tools create confusion about what the server is actually for.

Resources