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Crates

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

A4.6/5.0
Behavior5/5

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

Adds significant context beyond annotations: explains fan-out to two services, partial failure handling, and timing caveat (5-30s for bundlephobia first measurement). 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?

Single paragraph with dense but clear information. Front-loaded with purpose. Could be slightly more structured (e.g., bullet points), but efficiently conveys all needed details.

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 fully explains return fields, notes ecosystem restriction, and covers edge cases (partial failures, timeout). Complete for the tool's complexity.

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% with good parameter descriptions. The description adds context about version defaulting to latest and scoped package acceptance, enhancing parameter understanding.

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 evaluating npm packages, covering license, advisories, bundle size, etc. It distinguishes itself from sibling tools like get_crate (Rust ecosystem) by explicitly limiting to NPM ecosystem.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit use cases ('is X safe / popular / small' or 'what does adding lodash cost me') and mentions ecosystem limitation with fallback to deps.dev:version for other ecosystems. Could be improved by listing when not to use, but sufficient.

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

A4/5.0
Disambiguation3/5

The tool set includes several overlapping research/lookup tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) and multiple Polymarket tools, which could confuse an agent despite detailed descriptions. The boundaries between these tools are explained in the descriptions, but the sheer number of similar-purpose tools creates ambiguity.

Naming Consistency4/5

Most tools follow a verb_noun pattern (e.g., search_crates, get_versions, validate_claim), but there are exceptions like entity_profile, deep_research, and bet_research, which break the pattern. The overall naming is readable and mostly consistent, with the polymarket_ and pipeworx_ prefixes providing grouping.

Tool Count2/5

With 35 tools, the server is far too heavy for a focused service. The server name 'Crates' suggests a narrow domain, but only 5 tools relate to Rust crates, while the rest cover disparate areas (Pipeworx, Polymarket, memory management). This mismatch and high count make the tool surface unwieldy.

Completeness4/5

For the underlying Pipeworx/Polymarket domain that the majority of tools serve, the coverage is strong: lookup, grounded answers, research, entity profiles, comparisons, changes, claim validation, scanning, memory, subscriptions, tool discovery. Minor gaps exist (e.g., no direct summarization), but the set feels well-rounded for a data analysis agent.

Resources