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Glama

Fda 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

A5/5.0
Behavior5/5

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

The description goes beyond annotations by detailing graceful degradation on partial failures, bundlephobia's first measurement latency (5-30s), and that sources_failed will list timeouts. Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, but the description adds valuable operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is tightly written with every sentence adding value. It front-loads the main purpose, then covers data sources, use cases, limitations, and behavior in a logical flow. 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?

Given the tool's complexity (multiple external sources, partial failures), the description covers all essential aspects: what it does, when to use, edge cases (timeouts), return format, and ecosystem scope. Despite no output schema, the description provides sufficient completeness.

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?

Schema coverage is 100% and the description adds meaning by explaining the package parameter (npm package name, scoped packages accepted) and version default behavior. It also describes the return structure (summary block, per-advisory detail, links, alternative versions), compensating for the lack of an output schema.

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 explicitly states it is a composite check for deciding whether to add an npm package, covering deps.dev (license, advisories, version history) and bundlephobia (bundle size, dependency count, ESM/tree-shake support). It clearly distinguishes itself from sibling tools like deps.dev:version by qualifying it as a one-call package evaluation.

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?

The description provides clear use cases: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also explicitly states limitations: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly', guiding when to use this tool versus 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
Disambiguation1/5

The tool set contains near-duplicate query tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and many overlapping accessors (deep_research, validate_claim, fda_search, fda_regulation). The server name 'Fda Regulations' is also misleading because the vast majority of tools (e.g., polymarket_*, generate_llms_txt, remember) have nothing to do with FDA regulations, making correct selection extremely difficult.

Naming Consistency2/5

Most names use snake_case, but the verb/noun pattern is inconsistent: some are verb-first (ask_pipeworx, generate_llms_txt, validate_claim), some are noun-first (entity_profile, recent_changes, pipeworx_trending), and the ask_pipeworx_beta/grounded variants break the convention. Some names are also semantically misleading (scan_dependency checks an npm package rather than scanning a dependency).

Tool Count1/5

With 33 tools, this is far too many for a server nominally about FDA regulations; only two tools directly address that domain. Even as a general-purpose data platform, 33 tools is excessive and includes many unrelated utilities (e.g., generate_llms_txt, scan_dependency), making the server's scope unclear and bloated.

Completeness2/5

For the stated FDA regulations purpose, only fda_regulation (get by citation) and fda_search (keyword search) exist, providing basic read coverage but no access to FDA data (drug labels, adverse events, recalls), guidance documents, or regulatory history. The many unrelated tools do not fill these gaps, so the surface is severely incomplete for its apparent purpose.

Resources