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Glama

Microsoft Onenote

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. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already provide readOnly, idempotent, openWorld hints, and non-destructive. Description adds value by explaining fan-out behavior, graceful partial failures, and a 5-30s timeout for bundlephobia's first measurement on new versions. 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 relatively long but every sentence adds value. It is front-loaded with purpose and usage guidelines. Could be slightly more concise but remains effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema is provided, but the description thoroughly explains the return fields (summary block, advisories, links, alternative versions) and behavior on partial failures. Adequate for an agent to understand what to expect.

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 the description does not need to repeat schema details. It adds minimal context (e.g., scoped packages accepted, version defaults to latest). Baseline 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?

The description clearly states the tool's purpose as a composite check for npm packages covering license, advisories, version history, and bundle size. It uses specific verbs and resources, and distinguishes from sibling tools by noting ecosystem limitations.

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 tells when to use this tool (agent asks about package safety/popularity/size or cost of adding a package) and when not to use it (non-NPM ecosystems fall under deps.dev:version directly). Provides clear alternatives.

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

A3.5/5.0
Disambiguation2/5

Several tools are genuinely easy to confuse: ask_pipeworx and ask_pipeworx_beta are explicitly described as currently identical, and the five polymarket_* tools overlap significantly in purpose. There are also wrapper-like pairs such as ai_visibility_check vs. scan_competitor_ai_presence and entity_profile vs. recent_changes vs. compare_entities that require reading long descriptions to disambiguate.

Naming Consistency3/5

The names are mostly lowercase snake_case and readable, but there is no consistent verb_noun pattern: entity_profile and recent_changes are noun phrases, pipeworx_trending and pipeworx_feedback use a prefix, ask_pipeworx_beta is a single-family variant, and scan_competitor_ai_presence uses a different structure from ai_visibility_check. The naming is not chaotic, but it is a mix of conventions.

Tool Count1/5

A server labeled Microsoft Onenote exposes 31 tools, none of which actually relate to OneNote note-taking, notebooks, or pages. Even as a general research/prediction-market server, 31 tools is far above the coherent range, and for the stated product purpose this count is wildly inappropriate.

Completeness1/5

For the server's declared OneNote domain, there is zero coverage: no tools for creating, reading, updating, or deleting notes, pages, sections, or notebooks. The actual tool surface is centered on Pipeworx data lookups, Polymarket arbitrage, and memory helpers, which leaves the apparent note-taking domain completely unrepresented.

Resources