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Glama

Opensea

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

A4.6/5.0
Behavior5/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint. Description adds valuable behavioral details: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, sources_failed lists timeouts, and explains the fan-out behavior across two APIs. 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 two sentences and packs substantial information, but is slightly dense. It is front-loaded with purpose and usage. Minor room for better structure, but overall concise.

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 no output schema, the description explains the return summary block in detail, covers per-advisory detail, links, and alternative versions. Also addresses error behavior (partial failures, timeouts). Complete for an agent to understand tool capabilities.

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 description coverage is 100%, so baseline is 3. The description adds minimal extra meaning: mentions scoped packages are accepted and version defaults to latest. This is helpful but not extensive.

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 uses a specific verb ('scan') and resource ('dependency'), and distinguishes itself from siblings by specifying it's one-call for npm and mentioning alternatives 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 states when to use: 'whenever an agent asks “is X safe / popular / small” or “what does adding lodash cost me”.' Also provides exclusion: '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

A3.6/5.0
Disambiguation2/5

Tools cluster into overlapping groups: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates distinguished only by mode; bet_research, polymarket_edges, and polymarket_arbitrage all target prediction-market opportunities. The five OpenSea read tools are distinct, but they are buried among several unrelated domains, making misselection likely.

Naming Consistency4/5

Names are overwhelmingly snake_case with a verb_noun structure (get_collection, list_owned_nfts, validate_claim, create nothing but still remember/unsubscribe). Pipelined families like ask_pipeworx_* and polymarket_* are consistent, with only minor deviations such as pipworx_trending or bet_research not following a clear verb-object pattern.

Tool Count2/5

36 tools is too many for a coherent server, and the count is inflated by at least four unrelated domains: OpenSea NFT reads, Pipeworx data lookup/research, Polymarket betting, and memory/subscription utilities. Only five tools actually relate to the server's stated OpenSea purpose, so the surface is heavily bloated with off-scope functionality.

Completeness2/5

The OpenSea-relevant tools cover basic read operations—collections, stats, single NFT, collection NFTs, and owned NFTs—but omit search, events, offers/listings, order book data, and account/contract details. The many unrelated Pipeworx tools do not fill these gaps, so an agent needing real marketplace behavior would hit dead ends.

Resources