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Uk Food Hygiene

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.

TDQS

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations, including composite fan-out, partial failure handling, and bundlephobia latency (5-30s on first measurement). It also mentions that sources_failed will list timeouts, which is critical for agent behavior understanding.

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 core purpose and usage, then provides output details and limitations. While slightly verbose, every sentence adds value. A minor conciseness improvement could tighten the output summary, but overall it's 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?

Given the tool's complexity (composite check, multiple data sources, partial failures) and absence of an output schema, the description is remarkably complete. It covers what the tool returns (summary fields, advisories, alternatives) and how it handles errors, enabling correct agent behavior.

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 coverage is 100% with both parameters described. The description adds minimal additional value: it confirms scoped package acceptance and default version behavior, but these are already implied by the schema descriptions. 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 using deps.dev and bundlephobia, with a specific verb ('scan') and resource ('dependency'). It distinguishes from sibling tools by focusing on npm package analysis, which is unique among the listed siblings.

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 explicitly advises when to use the tool: when an agent asks about npm package safety, popularity, or size. It also specifies the scope (NPM only) and directs users to deps.dev:version for other ecosystems, providing clear when-not-to-use guidance.

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

All Uk Food Hygiene toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tools blur together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions over the same data, and five polymarket_* tools overlap on edge detection and arbitrage. Descriptions help somewhat, but the boundaries are subtle and the server name 'Uk Food Hygiene' adds a layer of confusion.

Naming Consistency3/5

All names are lowercase snake_case, but conventions vary widely: brand-style names (ask_pipeworx, pipeworx_feedback), noun phrases (entity_profile, recent_changes), verb_noun pairs (list_subscriptions, validate_claim), and bare verbs (recall, forget). It is readable but does not follow one predictable pattern.

Tool Count1/5

A server named 'Uk Food Hygiene' has 33 tools, of which only two (uk_food_hygiene_search, uk_food_hygiene_details) relate to food hygiene. The rest are a grab-bag of Pipeworx platform utilities, prediction-market tools, memory helpers, and subscription features — an extreme mismatch between count and stated scope.

Completeness2/5

The two food hygiene tools cover search and detail lookup, which handles the core use case, but the broader tool surface has notable gaps: citation URIs are returned but no fetch/read tool exists, and the unrelated domains (prediction markets, company research, AI visibility) are deep in some places and absent in others. The overall surface feels like an incoherent collection rather than a complete domain toolkit.

Resources