Neruva

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the general purpose ('search and analyze information') and reveals nothing about return format, side effects, how generate_mode affects behavior, or how site filtering works. This is a significant gap for a query tool with no output schema.

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 wastes no words. It directly opens with the action verb and resource, making it easy to parse quickly.

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?

With no output schema and no annotations, the description should at least hint at response behavior or parameter interplay. It does not mention generate_mode's effect on output, the meaning of 'NLWeb', or how site relates to configured data sources. An agent is left without enough context to fully understand the tool's capabilities and expected return behavior.

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 description coverage is 100%, so the input schema fully documents all three parameters. The description adds no extra parameter semantics beyond what the schema already provides; the baseline of 3 is appropriate.

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 states a specific action ('Query NLWeb') and resource ('configured data sources'), and indicates the purpose ('search and analyze information'). It is clear and distinct from sibling tools like list_sites and who, though it does not explicitly differentiate itself.

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 usage when an agent needs to search or analyze data from configured sources, but it gives no explicit when-to-use/when-not-to-use guidance or references to alternatives. The context is inferable but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden. It accurately indicates a read-only operation but does not disclose any side effects, authentication requirements, or potential limitations (e.g., rate limits, ordering, or whether the list is dynamic). For a simple list tool, this is adequate but not rich.

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 sentence that is fully front-loaded with the action and object. No wasted words, and it conveys everything needed for the tool's primary function.

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 zero-parameter tool with no output schema, the description is reasonably complete. It does not specify the shape of the returned sites list, but given the simplicity and lack of any schema, an agent can infer the output. Minor gap: it could mention that the list is meant for use with the sibling tools, but that is not essential.

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 tool has zero parameters and schema description coverage is 100% (trivially). The description does not need to add parameter meaning, and the baseline of 4 applies because there are no parameters to document.

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 states a clear verb ('List'), a specific resource ('sites'), and a scope ('all available'), and it distinguishes itself from the siblings 'ask' and 'who' by being the only discovery/list operation. Even without explicit differentiation, the purpose is 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 implies usage as a precursor to querying sites but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or prerequisites. For a zero-parameter discovery tool, this is acceptable but minimal; the context is clear enough for an agent to infer it should be called first.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It implies a read-only retrieval operation but reveals nothing about result count, ordering, what 'most relevant' means operationally, or whether the endpoint could return empty or error results.

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 17-word sentence that efficiently conveys the core purpose. The phrase 'by asking the who endpoint' is slightly redundant with the tool name, but the description is otherwise free of filler and well structured.

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 one-parameter tool with no output schema, the description conveys the essential input and rough output. However, with two ambiguous siblings and no annotation support, an agent would likely need to probe the tool to understand what it returns and when to prefer it over ask or list_sites.

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 description coverage is 100%, so the baseline of 3 applies. The description's mention of 'a query' loosely maps to the query parameter but adds no format, length, or syntax guidance beyond what the schema already provides.

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?

States a specific verb (Find) and resource (most relevant sites) with a clear query-driven purpose. However, 'by asking the who endpoint' is mildly circular since 'who' is the tool name itself, and it doesn't explicitly distinguish the tool from its sibling list_sites, which also deals with sites.

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?

Provides no when-to-use or when-not-to-use guidance. With siblings named ask and list_sites, there is no hint about how 'finding relevant sites for a query' differs from asking something or listing sites, leaving the selection decision entirely to the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.