geo time
geo_timeGeocode + timezone + currency context for any location string. [price: $0.001/call USDC via x402]
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Location string |
ThirdMade Shelf
TDQS
A3.8/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden. It adds useful pricing and payment details via x402, and implies a read-only lookup, but it does not mention response format, rate limits, errors, or operational behavior beyond cost.
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?
A single, front-loaded sentence delivers the core capability and pricing with no filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter lookup with no output schema, the description covers input, output domains, and cost. It omits the exact return structure, but the tool is simple enough that an agent can invoke it and inspect the response.
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?
The schema already documents q as 'Location string' with 100% coverage, so the description adds little beyond reinforcing 'any location string'. It does not clarify accepted formats such as address, city, coordinates, or place name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies what the tool does: geocode, timezone, and currency context for a location string. It is readily distinguishable from the sibling tools, though it uses a noun-phrase rather than an explicit verb and does not name an alternative.
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 phrase 'for any location string' provides a clear usage context: when an agent has a location string and needs geographic/time/currency context. It does not mention exclusions or alternatives, but the tool's niche is unique among the siblings.
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
B3.2/5.0
Disambiguation3/5
Most tools have distinct purposes, but several clusters overlap: domain_facts, page_meta, and scrape all return page title information, and search_verify, hallucination_check, and sweep all target claim validation. The descriptions usually clarify the use case, but the boundaries are not always obvious.
Naming Consistency3/5
All names use lowercase snake_case, so there is a baseline consistency, but the pattern is mixed: bare verbs like scrape, summarize, and sweep sit alongside noun+noun forms like domain_facts and noun+verb forms like entity_find. The names are readable but do not form a predictable verb_noun API convention.
Tool Count3/5
At 26 tools, this is heavy and above the typical well-scoped 3-15 range, though the server is explicitly positioned as a broad shelf of paid utilities. Many tools are small one-purpose endpoints, so the count feels more like a catalog than a focused suite, but it is not an extreme mismatch.
Completeness4/5
The shelf covers the major advertised areas: web page analysis, research verification, text guards and NLP, blockchain reads, and image generation. There are some gaps such as no web search and no transaction sending, but agents can typically work around them or pair this with another server.