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Glama

Anilist

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent. The description adds crucial behavioral details: partial failures with bundlephobia timing (5-30s first measurement), graceful degradation via 'sources_failed', and the composite nature of the call.

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 informative but slightly lengthy. However, it is front-loaded with the main purpose and every sentence adds value. Could be broken into sections, but remains effective.

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 the composite nature and lack of output schema, the description thoroughly explains the return structure: summary block fields, per-advisory detail, links, and alternative versions. It covers partial failures and ecosystem limitations comprehensively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%. The description adds value beyond schema: clarifies that scoped packages (e.g., '@types/node') are accepted for the 'package' parameter, and specifies default behavior for 'version' (defaults to latest published version).

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's purpose: a composite check for adding an npm package, covering license, advisories, version history, and bundle size. It distinguishes from sibling tools by specifying the npm ecosystem focus and referencing deps.dev 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?

Explicit when-to-use guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also specifies limitations: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under 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.

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TDQS

A3.9/5.0
Disambiguation3/5

Most tools have distinct responsibilities, but several clusters blur together: ask_pipeworx/ask_pipeworx_beta/ask_peworx_grounded are near-identical entry points, the five Polymarket tools overlap heavily, and ai_visibility_check vs scan_competitor_ai_presence overlap in purpose. An agent would need to read long descriptions carefully to avoid misselection.

Naming Consistency4/5

Names are almost entirely snake_case and mostly follow a verb_noun pattern. Minor inconsistency exists in prefixes and verb styles (ask_pipeworx vs pipeworx_feedback vs polymarket_arbitrage vs bet_research), but the naming is generally predictable and readable.

Tool Count2/5

34 tools is well above the 25+ threshold for a cohesive set, and the count is not justified by the server's apparent Anilist scope: the majority of tools are unrelated Pipeworx data-research, prediction-market, memory, and npm-scanning utilities. Many meta-tools could be consolidated.

Completeness2/5

For a server named Anilist, the anime surface is severely incomplete: only search_anime, get_anime, and trending_anime exist, with no seasonal, top-rated, studio, character, staff, or recommendation operations. The Pipeworx data side is fairly complete, but that does not serve the stated domain.

Resources