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jlbjulio

tavily-research

by jlbjulio

Start Tavily Research

tavily_research

Launch an in-depth research task for complex questions that require broad analysis. It runs multiple searches and returns a cited report, with a request ID for tracking progress.

Instructions

Start an in-depth, billable research task that performs multiple searches and produces a cited report. Use only for complex questions requiring broad analysis. After starting, use tavily_research_status with the returned request ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesA detailed description of the topic, questions, scope, and desired research outcome.
modelNoResearch model. Mini is cheaper; Pro is more comprehensive; Auto lets Tavily choose.mini
outputLengthNoTarget length of the generated report.standard
citationFormatNoCitation style for the generated report.numbered
excludeDomainsNoOptional domains Tavily must exclude from the report.
includeDomainsNoOptional domains Tavily should prioritize as sources.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate this is not read-only and not idempotent, but the description adds important context not present there: the task is 'billable' and involves an asynchronous follow-up via tavily_research_status. This gives the agent critical operational expectations beyond the structured metadata.

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 three sentences with no filler: it front-loads the core purpose, adds a clear usage restriction, and ends with the required follow-up action. Every sentence contributes essential information.

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?

Since there is no output schema, the description appropriately mentions the returned request ID and directs the caller to the status tool. It could additionally describe failure modes or how the final report is delivered, but for starting a research task it is largely complete.

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 description coverage is 100%, and each parameter already has defaults, enums, and explanations. The description adds no parameter-level detail, but it does not need to because the input schema fully documents the parameters.

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 clearly states a specific action and resource: 'Start an in-depth, billable research task' that performs multiple searches and produces a cited report. It distinguishes itself from the status sibling by emphasizing the initiation behavior and the eventual cited-report output.

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?

It explicitly says to use the tool 'only for complex questions requiring broad analysis,' which provides a clear when-to-use boundary. It also directs the caller to follow up with tavily_research_status, but it does not explicitly name tavily_search as the alternative for simpler questions.

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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