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obhor

outmate-gtm-router

by obhor

Search the web with Tavily

tavily_search
Read-onlyIdempotent

Discover ranked webpages and source URLs for company, product, market, competitor, prospect, technology, pricing, or news research, returning titles, snippets, and optional short answers.

Instructions

Search the live web for company, product, market, competitor, prospect, technology, pricing, or news research. Use this tool to DISCOVER relevant webpages and source URLs. It returns ranked titles, URLs, snippets/content, and an optional short answer. Use jina_read_url when a specific result needs deeper page extraction. Do not use this tool to read a URL already known to the user.

Input Schema

NameRequiredDescriptionDefault
queryYesFocused web search query. Include company/product name, geography, or date when relevant.
topicNoSearch category. Use news for recent events and finance for financial/company-finance queries.general
timeRangeNoOptional recency window for results.
maxResultsNoMaximum number of search results to return. Default 5; maximum 10.
searchDepthNoUse basic for normal research; advanced for harder or more specific research.basic
excludeDomainsNoOptional domains to exclude.
includeDomainsNoOptional domains to restrict results to.

Output Schema

NameRequiredDescriptionDefault
queryYes
answerYes
resultsYes
providerYes
truncatedYes
responseTimeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world and non-destructive, so the safety profile is covered; the description usefully adds the return shape and routing behavior. The one loose end is the 'optional short answer', which no parameter exposes and which the description never explains, leaving ambiguity about whether extra synthesis is returned. No contradiction with annotations.

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?

Four short sentences, front-loaded with purpose, then return shape, then routing, then exclusion. The enumeration of research domains is slightly long but does real work in steering query intent.

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 an output schema exists, return values need not be explained in depth, and the usage rules are fully covered. The only gap is the unexplained 'optional short answer' and the absence of any note on result limits/cost of advanced depth, which an agent would benefit from at call time.

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% with enums for topic, timeRange and searchDepth, so the parameters are already well documented. The description adds essentially no parameter-level guidance (e.g., when to favor searchDepth=advanced or how domain filters combine), so the baseline 3 applies.

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?

States a specific verb ('Search the live web') plus the resource domains and the intent ('DISCOVER relevant webpages and source URLs'). It also signals the return shape (ranked titles, URLs, snippets/content), which lets an agent distinguish it from jina_read_url without opening either schema.

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

Usage Guidelines5/5

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

Gives explicit when-to-use ('DISCOVER relevant webpages'), names the alternative for the other case ('Use jina_read_url when a specific result needs deeper page extraction'), and states a clear exclusion ('Do not use this tool to read a URL already known to the user'). Nothing is left to inference.

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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