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Tavily Search

tavily.search
Read-onlyIdempotent

Search the web using natural-language queries to find relevant information when specific URLs are unknown. Customize results with filters for depth, date range, domains, and more.

Instructions

Search the web when relevant URLs are not yet known.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language web search query.
max_resultsNoMaximum number of results.
topicNoSearch topic mode.general
include_answerNoInclude Tavily's answer field.
include_raw_contentNoInclude cleaned page content.
include_imagesNoInclude image URLs.
include_image_descriptionsNoInclude image descriptions.
search_depthNoTavily search depth.basic
time_rangeNoRelative publish-date filter.
start_dateNoInclusive start date in YYYY-MM-DD format.
end_dateNoInclusive end date in YYYY-MM-DD format.
include_domainsNoDomains to include.
exclude_domainsNoDomains to exclude.
include_usageNoInclude usage metadata.
ctxNoOptional FastMCP context.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
answerNo
resultsNo
imagesNo
response_timeNo
request_idNo
follow_up_questionsNo
usageNo
Behavior2/5

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

Annotations already confirm read-only, idempotent, and open-world behavior. The description adds no additional behavioral context (e.g., rate limits, pagination, or result composition). With annotations covering safety, the description falls short of enhancing transparency beyond the structured data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that immediately conveys the core purpose. It is efficient but could be slightly restructured to include a brief mention of key features or output without losing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description is too sparse for a tool with 15 parameters and complex filtering capabilities. It does not indicate the rich set of options (date range, domains, depth) available, leaving agents unaware of the tool's full potential.

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

Parameters3/5

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

Schema coverage is 100%, with each parameter having a description. The tool description itself does not elaborate on parameters, but the schema already does so adequately. Baseline score of 3 is appropriate given the high schema coverage.

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

Purpose4/5

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

The description clearly states the tool performs web searches when URLs are not known, distinguishing it from siblings like 'extract' (which requires URLs). However, it does not explicitly mention the return of search results or snippets, which would further clarify its purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear usage context ('when relevant URLs are not yet known'), implying when to use this tool versus others like 'extract' or 'crawl'. However, it lacks explicit guidance on when not to use it or direct comparisons with sibling tools, leaving room for ambiguity.

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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