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Glama

Gtex

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?

Beyond annotations (readOnly, idempotent, openWorld), the description discloses key behaviors: partial failures degrade gracefully, bundlephobia first measurement latency (5-30s), and sources_failed field. 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?

Description is informative but somewhat lengthy; however, every sentence adds value. Front-loaded with purpose and usage. Could be slightly tighter, but no wasted words.

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?

Despite no output schema, the description fully enumerates return fields, explains partial failure behavior, and covers edge cases (new version latency). Complete for a composite tool with two data sources.

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 no new meaning beyond what the schema already provides (package name, version defaulting). No extra semantics needed.

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 the verb 'check' and resource 'npm package', and distinguishes from siblings by specifying the composite nature (deps.dev + bundlephobia) and ecosystem scope. It precisely conveys what the tool does.

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 ('is X safe / popular / small', 'what does adding lodash cost me') and when not to use (non-npm ecosystems, directing to deps.dev directly). Provides clear context for agent decision-making.

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

All Gtex toolsInspect
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TDQS

B3.3/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are currently described as functionally identical, which is a direct ambiguity, and ai_visibility_check/scan_competitor_ai_presence plus the polymarket_* tools create several overlapping boundaries. The long descriptions help, but an agent still has to read deep into each one to avoid selecting the wrong tool.

Naming Consistency3/5

Most tools use readable lowercase snake_case verb_noun names like discover_tools, resolve_entity, and validate_claim, but the set also includes bare nouns like gene and tissues, verb-only memory tools like remember/recall/forget, and noun-phrase names like entity_profile, recent_changes, and pipeworx_trending. The style is not chaotic, but no single convention is sustained.

Tool Count2/5

36 tools exceeds the 25+ threshold and the surface is heavily padded with overlapping meta-tools, near-duplicate routers, and unrelated clusters such as Polymarket arbitrage, AI-visibility checks, and GTEx expression queries. For a server named Gtex, most of these tools are outside the apparent domain, making the count feel overgrown rather than well-scoped.

Completeness2/5

The GTEx-specific subset has only five tools and lacks obvious endpoints like multi-issue eQTLs, isoform expression, or sample-level querying, while the remaining 31 tools belong to unrelated Pipeworx, Polymarket, memory, and subscription domains. There is no coherent single purpose against which the surface can be considered complete, so agents will often hit dead ends or spend calls figuring out what the server is actually for.

Resources