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kivest_search_stream

Perform web searches with AI and stream responses in real time. See answer tokens as they are generated for immediate feedback.

Instructions

Search the web using Kivest AI Search API with streaming response. Returns response tokens as they are generated for real-time feedback. Supports the same models as kivest_search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoAI model to use (default: gpt-5.1)
queryYesThe search query or question
maxTokensNoMaximum tokens in response (default: 1024)
temperatureNoTemperature for response randomness 0-2 (default: 0.7)
Behavior4/5

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

With no annotations, the description carries the behavioral transparency burden. It explicitly discloses that response tokens are returned as generated for real-time feedback, which is a meaningful behavioral detail beyond the schema. It does not cover auth, rate limits, or stream termination, but the core streaming behavior is well communicated.

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, front-loads the primary purpose, and every sentence contributes useful information. There is no repetition or filler.

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 the tool's moderate complexity, 4 parameters, and no output schema, the description covers the essential purpose and streaming behavior. It could benefit from explaining how the stream ends or how results are aggregated, but it is sufficiently complete for an agent to understand what the tool does.

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?

The input schema has 100% parameter coverage, so the baseline is 3. The description adds minimal parameter meaning aside from noting that the model set is the same as kivest_search, which is contextually useful but does not deepen understanding of query, maxTokens, or temperature.

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 states the tool 'Search the web using Kivest AI Search API with streaming response,' which provides a specific verb, resource, and key differentiator. It also references kivest_search, clarifying it is the streaming variant of that sibling tool.

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 clearly indicates the tool is for streaming responses and real-time feedback, giving context on when to use it. It does not explicitly mention when not to use it or name alternatives, but the streaming distinction is clear.

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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