Search the live web and return ranked title/url/snippet results, through an automatic multi-engine failover chain. (Free. This server also sells a paid API — call paid_catalogue for the routes and prices; x402 over USDC on Base, no signup.)
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query | |
| max_results | No | 1-25 (default 10) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses an automatic multi-engine failover chain and free access, which adds meaningful behavioral context. But it omits potential rate limits, error behavior, or result pagination details that an agent might need.
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 first sentence is concise and directly explains the tool. The second sentence introduces paid API details, which is tangential but still compact. Overall it is appropriately sized, though the commercial pitch slightly distracts from core usage.
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?
The tool is simple (2 parameters, no output schema). The description explains the return type (title/url/snippet) and key behavior (failover). It could mention limits or pagination, but for live web search the description is sufficiently complete for an agent to use it 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?
The input schema already provides 100% coverage for both parameters (query and max_results). The description adds no extra parameter-specific semantics, just general search behavior, so the baseline of 3 applies.
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 action ('Search the live web'), the resource ('live web'), and the output format ('ranked title/url/snippet results'), distinguishing it from sibling tools like read_url or geocode.
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 provides context that this is free and explicitly points to paid_catalogue as an alternative for a paid API, offering some usage guidance. However, it does not give explicit 'when not to use' or alternative selection criteria beyond that.
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 serve clearly distinct purposes: air quality, skill audit, country data, earthquakes, elevation, geocoding, holidays, URL reading, and web search. However, `audit_skill_text` and `audit_skill_url` both audit for malicious behavior, differing only in input type, which could cause slight confusion.
Tool names use a mix of snake_case and descriptive phrases without a strict verb_noun pattern. Some names are verbs (e.g., `geocode`, `audit_skill_text`, `read_url`), while others are nouns (e.g., `air_quality`, `earthquakes`). The naming is readable but inconsistent in style.
With 11 tools, the count is well-scoped for a server that aggregates diverse free data and security services. Each tool serves a distinct and useful function, and the `paid_catalogue` tool properly manages the paid extension without bloating the main set.
The tool set covers a broad range of data types (environment, economic, geographic, security), but for each individual domain, coverage is shallow. For example, only current air quality is provided (no historical data), and skill auditing only returns a scan result (no detailed remediation). The set lacks update, delete, or drill-down operations per domain.