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Glama

Fcc Regulations

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

A4.8/5.0
Behavior5/5

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

Annotations already declare idempotency and read-only behavior. The description adds critical behavioral nuance: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed will list timeouts. This goes well beyond 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?

The description is front-loaded with the main purpose and then provides detail in a logical order. While somewhat long, every sentence carries useful information. Could be slightly more concise but overall well structured.

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 lists all return fields (summary block, advisories, links, alternatives) and explains partial failure behavior. This fully prepares the agent for what to expect from the 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%, but the description adds value by noting that scoped packages (e.g., '@types/node') are accepted, which is not in the schema. The default version behavior is also reinforced. The added context justifies a score above baseline.

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: a composite check for npm packages, combining deps.dev and bundlephobia data. It uses specific verbs ('scan', 'check') and resources ('npm package'), and distinguishes from sibling tools by specifying the ecosystem and scope.

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 says 'Use whenever an agent asks "is X safe / popular / small"' and provides exclusion guidance: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly.' This clearly tells when and when not to use the tool.

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

All Fcc Regulations toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tool clusters have poorly defined boundaries: ask_pipeworx and ask_pipeworx_beta are currently functionally identical, the five polymarket tools all orbit 'find/validate trading edges', and ai_visibility_check overlaps heavily with scan_competitor_ai_presence. The memory and subscription tools are distinct, but the core query/edge clusters would cause frequent misselection.

Naming Consistency2/5

Naming conventions are mixed across the set: the ask_pipeworx* family uses verb+product, the polymarket_* family uses domain-prefixed nouns, fcc_regulation and fcc_regulations_search differ in singular/plural and lack a verb, and tools like discover_tools, entity_profile, and generate_llms_txt each follow different patterns. No single predictable convention holds across the server.

Tool Count2/5

33 tools is heavy on its own, but the count is especially inappropriate given the server is named 'Fcc Regulations': only 2 of the 33 tools actually serve FCC regulatory text, while the other 31 tools belong to a general-purpose Pipeworx data-query platform. The set is far too broad for the declared scope.

Completeness2/5

For the stated FCC-regulations purpose, the two relevant tools cover search and full-text retrieval, but there is no change tracking, no notification of rule updates, no historical/version comparison, and no adjacent FCC filings/licensing data despite the server name implying broader FCC coverage. The extra 31 unrelated tools do not fill these gaps, so an agent expecting FCC completeness would hit dead ends.

Resources