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kagi_search_fetch

Fetch web search results for a query using the Kagi Search API. Supports filtering by domain, date, file type, and workflow type (news, videos, podcasts, images) with numbered results for easy reference.

Instructions

Fetch web results for a query using the Kagi Search API. Use for general search and when the user explicitly tells you to 'fetch' results/information. Results are numbered so that a user may refer to a result by a specific number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoOnly include results published/updated on or after this date (ISO format, e.g., '2024-01-15').
limitNoMaximum number of results per category. In the mixed 'search' workflow this caps each category independently, so the total can exceed this number; in single-category workflows it caps total results.
queryYesA concise, keyword-focused search query. Include essential context for standalone use.
beforeNoOnly include results published/updated on or before this date (ISO format, e.g., '2024-12-31').
lens_idNoApply a Kagi lens to narrow the search to a curated set of sources. Built-in lens IDs: '2' (Academic — education/.edu domains), '1' (Forums — discussion forums across the web), '15' (Programming — official programming language sites and forums), '29' (News 360 — multi-perspective coverage of global news), '120' (Recipes — high-quality recipe sites, English), '107' (Small Web — noncommercial domains and topics). You may also pass a custom lens ID or full URL from https://kagi.com/settings/lenses (only shareable lenses work). Mutually exclusive with 'include_domains', 'exclude_domains', 'time_relative', and 'file_type'; use those args or 'lens_id', not both.
workflowNoType of results to return. Use 'news' for current events and recent reporting, 'videos' for video content (e.g. tutorials, talks), 'podcasts' for audio shows, 'images' for image results, or the default 'search' for general web results. Note that 'search' may return a mix of categories (web, news, videos, images) in one response, like a typical SERP; the other workflows return only their single category.search
file_typeNoRestrict to results with this file type (e.g., 'pdf', 'docx', 'xlsx'). Specify the extension without a leading dot.
extract_countNoNumber of top results to fetch full page content for, inline as markdown.
time_relativeNoRestrict to results published/updated within the last day, week, or month, evaluated server-side. Mutually exclusive with 'after'/'before'.
exclude_domainsNoExclude results from these domains (e.g., ['pinterest.com', 'quora.com']). Overrides any 'site:' operators in the query.
include_domainsNoRestrict results to these domains (e.g., ['docs.python.org', 'github.com']). Overrides any 'site:' operators in the query.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description adds one behavioral trait: 'Results are numbered so that a user may refer to a result by a specific number.' With no annotations provided, the description carries the full burden, but it does not disclose other behaviors like rate limits, authentication needs, or error handling.

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 extremely concise with two sentences, front-loading the core purpose and adding essential usage guidance and a behavioral trait without any 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 the tool's complexity (11 parameters, output schema exists, sibling tool present), the description is mostly complete. It explains the tool's purpose and numbering, but could mention that results include standard fields (title, URL) though the output schema likely covers that.

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%, so the baseline is 3. The description does not add any parameter-level information beyond what is already in the schema; it merely states the overall purpose.

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 'Fetch web results for a query using the Kagi Search API', which specifies the verb and resource. It further distinguishes usage for general search and when the user explicitly says 'fetch', helping differentiate from sibling kagi_extract (which likely extracts content from a URL).

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 usage context: 'Use for general search and when the user explicitly tells you to fetch results/information.' It implies when to use it but does not explicitly exclude alternative tools like kagi_extract or list when not to use it.

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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