airqualityAir-quality forecast (Norway).
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | ||
| lon | Yes | ||
| areaclass | No | grunnkrets | delomraade | kommune | fylke | land (default grunnkrets) |
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Feature type (GeoJSON) | |
| geometry | No | ||
| properties | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive, which the description does not contradict. However, the description adds no additional behavioral context, such as temporal resolution, units, or geographic limitations beyond the word 'Norway'.
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, front-loaded sentence that is free of extraneous text. It is concise, though perhaps overly terse given the missing parameter guidance.
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 input schema (3 params) and the presence of an output schema, the description provides only the core purpose without contextual details like expected usage patterns or coordinate interpretation. It is minimally adequate but not sufficient for an agent to fully understand the tool's capabilities.
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?
With schema description coverage at only 33%, the description needed to explain the coordinate parameters and any constraints. It does not mention lat/lon or how areaclass relates to forecast granularity, failing to compensate for the sparse schema.
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 identifies the tool as providing air-quality forecasts for Norway, which distinguishes it from sibling environmental forecast tools like oceanforecast and sunrise. However, it lacks an explicit verb (e.g., 'retrieve' or 'get'), making it a noun phrase rather than a full action statement.
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?
No guidance is provided about when to choose this tool over alternatives. The description does not mention use cases, prerequisites, or distinguish from other forecast-related tools, leaving the agent to infer from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but there is some overlap among closely related ones (e.g., ask_pipeworx, ask_pipeworx_grounded, deep_research; multiple Polymarket tools). Descriptions are detailed enough to differentiate, but an agent might still misselect on subtle differences.
Names consistently use lowercase with underscores, but no strong verb_noun pattern. Some are noun-based (airquality, nowcast), others verb-based (ask_pipeworx, compare_entities). This is readable but not perfectly predictable.
35 tools is high but justified by the server's broad scope (data queries, betting analysis, weather, memory, subscriptions). The number feels appropriate given the comprehensive functionality described.
The tool set covers an impressively wide range of capabilities: data querying with multiple modes, entity profiling, comparisons, search, betting analysis, weather, memory, subscriptions, and feedback. Missing features (e.g., updating memories) are minor; the surface is remarkably complete.