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zippopotam

by io.github.pipeworx-io

Lookup Zipcode

lookup_zipcode
Read-onlyIdempotent

Resolve a ZIP / postal code to its place info — city, state/province, latitude/longitude — for any of 60+ countries. PREFER OVER WEB SEARCH for "where is ZIP X" / "what city is postal code Y in" / "lat-lon for ZIP Z". Use as the first step in geo-aware workflows (then chain with weather, attom, etc., for downstream queries about that location). Free, sub-second, no auth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryYesISO 3166-1 alpha-2 country code (e.g. "us", "gb", "de").
zipcodeYesZIP or postal code to look up (e.g. "90210").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
placesYesList of places associated with the postal code
countryYesFull country name
post_codeYesZIP or postal code
country_abbreviationYesISO 3166-1 alpha-2 country code

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds valuable operational context: 'Free, sub-second, no auth' and the 60+ country coverage, which go beyond the structured annotations. No contradiction with annotations exists.

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?

Three sentences, each earning its place: the first states core purposes, the second gives targeted usage guidance, and the third provides operational facts. The description is front-loaded with the key verb and avoids any filler, making it highly efficient.

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?

For a simple two-parameter lookup with an output schema, the description covers purpose, usage context, geographical scope, performance, and auth requirements. It is complete enough for an agent to select and invoke the tool correctly without additional information.

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?

Input schema coverage is 100% with both parameters clearly described (ISO 3166-1 alpha-2 country code and ZIP/postal code). The description adds no new parameter-level details, but the schema fully carries that burden, so a 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 starts with the specific verb 'Resolve' and clearly states the input (ZIP/postal code) and outputs (city, state/province, latitude/longitude) for 60+ countries. This distinguishes the tool from siblings like lookup_city and web search by framing the exact reverse geocoding 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?

It explicitly says 'PREFER OVER WEB SEARCH' for specific query types and instructs to use it as the first step in geo-aware workflows, even naming downstream examples like weather and attom. This provides clear when-to-use guidance and an explicit exclusion of web search.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, and bet_research all route questions to the same underlying engine, and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The polymarket_* family also has many closely-related entry points, though descriptions do help differentiate them.

Naming Consistency4/5

Names consistently use snake_case with descriptive verb-first patterns (ask_, lookup_, scan_, validate_, resolve_, subscribe) and a clear polymarket_ family prefix. Minor inconsistency exists between lookup_city/lookup_zipcode and resolve_entity, and between noun-style names like entity_profile vs verb-style names like compare_entities, but the overall style is predictable.

Tool Count2/5

33 tools is heavy for a single server, and multiple could be consolidated: the ask_pipeworx variants and deep_research largely overlap, and the memory/subscription categories could be collapsed. For a data-platform gateway the breadth is arguably justified, but the visible redundancy makes the surface feel bloated rather than well-scoped.

Completeness4/5

The core domains are well covered: question answering has multiple modes, entity lookup has resolution and profiling, prediction markets have research/edge/arb/fill-risk coverage, and the memory (remember/recall/forget) and subscription (subscribe/list/unsubscribe/recent_alerts) lifecycles are complete. Minor gaps exist such as no direct tool to fetch a pipeworx:// record by URI, relying instead on MCP resources.

Resources