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Uk Food Hygiene

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds that results include full input schemas with curated examples and are ready to call directly, which aligns with and supplements the annotations without 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 well-structured with a clear purpose statement first, followed by usage guidance and output details. Every sentence serves a purpose, but it is slightly lengthy; however, it remains efficient and front-loaded.

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 role as a discovery mechanism, the description is comprehensive: it explains what it does, when to use it, what it returns, and includes examples in the schema. The absence of an output schema is compensated by describing the output format clearly.

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%, so baseline is 3. The description adds value by explaining that the limit parameter controls the number of tools returned (top-N) and that query accepts aliases. This enhances understanding beyond the schema's property 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 the tool's verb ('Find') and resource ('tools by describing the data or task'). It lists multiple domains (SEC filings, FDA drugs, etc.) and distinguishes itself from siblings like search_within or entity_profile by being a discovery tool for finding other tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly guides the agent to call this tool first when many tools are available and the option set is needed. It provides specific contexts (browse, search, look up, discover) but does not list alternative tools or cases where it should not be used.

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