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Glama

L2beat

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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false. Description adds valuable behavioral context: composite fans-out, partial failures degrade gracefully, bundlephobia first measurement can take 5-30s, and sources_failed shows timeouts. 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 relatively long but well-structured, front-loading the composite nature and use case, then detailing behavior and return format. Every sentence adds value, though minor trimming could improve conciseness.

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 thoroughly explains the return values (summary block, per-advisory detail, links, alternative versions) and handles edge cases like partial failures and timing. Comprehensive for a complex tool.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. Description adds: 'Scoped packages (e.g. "@types/node") are accepted' and 'Defaults to the latest published version when omitted', which provides additional clarity beyond the schema descriptions.

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's a composite check for npm packages covering license, advisories, bundle size, etc. It distinguishes from siblings by explicitly noting the NPM ecosystem limitation and directing other ecosystems to a separate 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?

Explicit usage guidance is given: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' Also notes that NPM only in v1 and other package managers fall under a different tool.

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

All L2beat toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

The tool set mixes L2beat-specific tools with a large number of unrelated Pipeworx, Polymarket, and other domain tools. While individual descriptions are clear, the overall set forces agents to navigate many irrelevant tools, causing confusion about the server's primary purpose.

Naming Consistency2/5

Tool names follow inconsistent conventions: snake_case (list_projects), camelCase (ask_pipeworx), and mixed patterns (generate_llms_txt, bet_research). No unified naming pattern exists across the set, reducing predictability.

Tool Count1/5

With 35 tools, the count is far too high for an L2beat server. Only about 5-6 tools are actually related to L2 scaling; the rest are from other domains, making the tool surface bloated and unfocused.

Completeness2/5

The L2beat-specific tools cover basic operations (list projects, get project, TVS, activity) but lack important features like bridge analysis, project comparisons, or detailed risk breakdowns. The numerous unrelated tools do not address gaps in L2 functionality.

Resources