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Disney

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?

Description adds valuable behavioral details beyond annotations: fans out to external services, partial failures degrade gracefully, bundlephobia first measurement can take 5-30s, and sources_failed will list failures. Annotations already indicate readOnlyHint, idempotentHint, etc., and description does not contradict.

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 fairly long but dense with useful information. Well-structured: starts with summary, then usage, then returned fields, then ecosystem constraint, then behavior notes. Almost every sentence adds value; only minor redundancy ('NPM ecosystem only in v1' could be merged with later note).

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?

Given complexity of tool (two services, multiple data points, partial failures, timeouts) and absence of output schema, description fully covers what an agent needs: return structure, failure modes, timeouts, and constraints. No gaps identified.

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 coverage is 100% (both parameters described in schema). Description adds minimal extra: mentions scoped packages are accepted and default version behavior, but these are already implied by schema. Baseline score of 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?

Description clearly states composite check for adding npm package, combining deps.dev and bundlephobia data. Specifies exact questions it answers ('is X safe/popular/small') and lists returned fields. Distinguishes from sibling tools by its specific niche.

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?

Explicit usage guidance: 'Use whenever an agent asks...' and states it's only for NPM ecosystem in v1, with alternatives for other ecosystems mentioned. Provides concrete examples and constraints.

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

All Disney toolsInspect
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TDQS

A3.6/5.0
Disambiguation5/5

Each tool has a highly distinct purpose, from Disney character lookups to financial data and prediction market analysis. Agent can easily distinguish them by name and description.

Naming Consistency2/5

Naming conventions vary wildly: some use verb_noun (list_characters), others are phrases (ask_pipeworx) or compound nouns (polymarket_arbitrage). No consistent pattern across tools.

Tool Count1/5

34 tools is far too many for a Disney-themed server. Only 3 tools (list_characters, search_characters, get_character) relate to Disney; the rest are general-purpose data tools that belong elsewhere.

Completeness1/5

For a Disney server, the tool surface is severely incomplete. Missing basic CRUD for characters, no info on movies, parks, or media. Extraneous tools do not fill these gaps.

Resources