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web_search_tool

Search the web to find real-world facts like venue capacities, geographic details, and traffic patterns for realistic simulation scenario design.

Instructions

Search the web using DuckDuckGo. Use this to look up real-world information
that helps with simulation scenario design.

Useful for:
- Venue/facility capacity (e.g., "Madison Square Garden capacity")
- Geographic/infrastructure info (e.g., "bridges connecting Manhattan to Brooklyn")
- Traffic patterns and event schedules
- Road/highway specifications
- Any factual information needed to set realistic simulation parameters

Args:
    query: Search query string. Be specific for better results.
    max_results: Number of results to return (default: 5, max: 10)

Returns:
    List of search results, each with title, url, and snippet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states the tool is read-only (search, look up) and returns a list of results, but does not disclose potential rate limits, authentication needs, or that it does not modify any state. For a search tool, this is acceptable but not exhaustive.

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?

The description is concise (about 10 lines) with a clear structure: purpose sentence, bullet list of use cases, then Args and Returns. Every sentence adds value; no fluff.

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?

Given no output schema, the description details the return format (list with title, url, snippet). It provides sufficient context for an AI agent to decide when to use this tool versus siblings. Missing explicit mention of search engine limitations or privacy, but adequate overall.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, yet the description adds meaningful explanations: 'query: Search query string. Be specific for better results.' and 'max_results: Number of results to return (default: 5, max: 10)'. This compensates well for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the verb 'search', the resource 'the web using DuckDuckGo', and the context 'simulation scenario design'. It lists specific use cases (venue capacity, geographic info, traffic patterns) which clearly distinguish it from sibling tools that are all simulation-related.

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 description provides clear when-to-use guidance with specific examples (venue capacity, geographic info, etc.) and advises on query specificity. However, it does not explicitly state when NOT to use it, though the context of sibling tools implies it is only for external factual lookups.

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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