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Glama

Twilio

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?

Beyond annotations (readOnly, idempotent, etc.), the description discloses partial failure behavior: bundlephobia first measurement may take 5-30 seconds, and sources_failed will list it if timed out. It also lists the exact fields returned, giving full transparency on what the agent gets.

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 packed with information but remains a single coherent paragraph. It front-loads the composite check purpose, then expands logically. The minor deduction is for slight length; it could be broken into two sentences for easier scanning, but it is still efficient.

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?

With no output schema, the description fully explains the return structure (summary fields, advisories, links, alternatives) and handles edge cases like partial failures and version defaults. It covers all necessary context for an agent to use this tool effectively.

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?

The schema covers both parameters, but the description adds: scoped packages are accepted (not in schema description), and version defaults to latest when omitted. This adds practical meaning beyond the schema alone.

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 composite check for whether to add an npm package, lists the data sources (deps.dev and bundlephobia), and specifies the return elements (summary block, advisories, links, alternative versions). It immediately distinguishes itself from sibling tools like validate_claim or deep_research by defining its specific function.

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?

Provides explicit when-to-use guidance: inquiries about safety, popularity, size, or cost of adding a package. Also specifies the ecosystem limitation (NPM only v1) and directs users to deps.dev:version directly for other ecosystems, which is a clear alternative.

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

B3.2/5.0
Disambiguation2/5

The server is named 'Twilio' but contains only 5 Twilio-specific tools mixed with 31 unrelated Pipeworx tools. An agent must distinguish between Twilio and Pipeworx functionality, and the tool descriptions are clear individually, but the overall set is confusing because the server name implies a focused Twilio service, not a general-purpose data platform with a few Twilio actions.

Naming Consistency2/5

The Twilio tools follow a consistent 'twilio_verb_noun' pattern (e.g., twilio_send_sms, twilio_make_call), while the Pipeworx tools use a separate snake_case convention (e.g., ask_pipeworx, entity_profile, deep_research). The two naming conventions are clearly distinct and do not mix, but the overall set is inconsistent because the server is named after one convention yet the majority of tools follow a different one.

Tool Count1/5

With 36 tools, the count is high, but the critical issue is that only 5 tools are relevant to the Twilio server name. The remaining 31 tools belong to Pipeworx, a completely different domain. This is an extreme mismatch between the claimed server purpose (Twilio) and the actual tool set, making the tool count inappropriate.

Completeness2/5

For a Twilio-focused server, the tool set is very incomplete: it covers only basic SMS sending, call initiation, and listing messages/calls. Missing are phone number management, media handling, conversation features, and other common Twilio operations. The Pipeworx tools are comprehensive for their own domain, but they are irrelevant to the Twilio server's stated purpose, leaving significant gaps.

Resources