Location intelligence — geocoding & reverse geocoding (OpenStreetMap), weather forecasts (Open-Meteo), timezone lookup, and Point of Interest search (restaurants, hotels, hospitals, 20+ types).
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Average 3.7/5 across 3 of 3 tools scored.
Each tool addresses a distinct concern: geocoding addresses, retrieving timezone information, and fetching weather data. There is no overlap in functionality.
All tools follow a consistent verb_noun pattern (geocode_address, get_timezone, get_weather), making them predictable and easy to understand.
Three tools is well-scoped for a server covering geocoding, timezone, and weather. Each tool earns its place without being too few or too many.
The tool set covers forward/reverse geocoding, timezone lookup, and weather with forecast. A minor gap might be a tool for IP-based location, but the core domain is well-covered.
geocode_addressAInspectForward or reverse geocoding using OpenStreetMap Nominatim. Forward: convert an address to lat/lon. Reverse: convert lat/lon to an address.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Address or place name to forward geocode | |
| lat | No | Latitude for reverse geocoding | |
| lon | No | Longitude for reverse geocoding | |
| limit | No | Number of results (max 5) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It accurately describes the two modes of operation. However, it omits important behavioral details such as rate limits, external API dependency, or any constraints on usage, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the core purpose. Every word adds value, with no redundancy or unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of geocoding and the lack of an output schema, the description is incomplete. It does not specify the structure of the returned data (e.g., coordinates for forward, address for reverse) or any pagination or result format, leaving the agent uncertain about what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond the schema; it merely summarizes the two modes. It does not explain how parameters interact (e.g., q vs lat/lon) or provide extra context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool does forward and reverse geocoding using OpenStreetMap Nominatim, distinguishing between the two modes (address to lat/lon and lat/lon to address). This is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use each mode (forward for address conversion, reverse for lat/lon conversion), providing clear context. However, it does not discuss when not to use the tool or mention any limitations or alternatives, missing a chance for more complete guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_timezoneAInspectGet timezone and country information by coordinates, country code/name, or IP address.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | No | IP address for timezone lookup | |
| lat | No | Latitude | |
| lon | No | Longitude | |
| country | No | ISO country code (US, DE) or country name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. While 'Get' implies a read operation, the description does not explicitly state it is read-only, side-effect-free, or mention any restrictions. It adds no behavioral context beyond what the name suggests.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single succinct sentence that covers all key aspects: what is retrieved and how. No unnecessary words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature (4 optional params, no output schema, no nested objects), the description is largely complete. It could mention priority if multiple params are used or what happens if no params, but overall it provides sufficient context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by grouping parameters into three lookup methods (coordinates, country, IP), which provides reasoning about how to use them in conjunction or as alternatives, going beyond individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves timezone and country information using coordinates, country code/name, or IP address. It distinguishes from siblings like geocode_address and get_weather by the output (timezone vs addresses or weather), but does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (e.g., after getting coordinates from geocode_address or when an IP is available), but it does not explicitly state when not to use or provide alternatives. No mention of fallback behavior when multiple params are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_weatherAInspectCurrent weather and multi-day forecast for any location. Provide coordinates or a city name.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | Latitude | |
| lon | No | Longitude | |
| days | No | Forecast days (1-7, default 3) | |
| units | No | metric or imperial | metric |
| location | No | City name (geocoded automatically) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It only states it provides weather and forecast but omits details like data sources, accuracy, rate limits, or what happens on invalid input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that effectively communicates the core functionality. It is front-loaded and to the point, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple weather tool with 5 parameters and no output schema, the description covers the essential aspects: what it returns and how to specify location. It is sufficient for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds little beyond the schema. It only reiterates that location can be specified via coordinates or city name, which is already clear from parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns current weather and multi-day forecast for any location, distinguishing it from sibling tools like geocode_address and get_timezone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It tells the user to provide coordinates or a city name, which is sufficient context. However, it doesn't explicitly mention when not to use this tool or suggest alternatives, but the siblings are distinct enough.
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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{
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