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kagi quick

Generate a Kagi Quick Answer from the authenticated web product and return the full answer envelope, references, and follow-up questions. Quick Answer demo

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Synopsis

kagi quick [OPTIONS] <QUERY>

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Description

kagi quick targets Kagi’s Quick Answer web-product flow, not FastGPT and not the public Search API. It is useful when you want a fast answer plus references without opening a browser tab. This command is ideal for:
  • factual questions with references
  • shell workflows that want a single answer envelope
  • quick terminal lookups with pretty or markdown output
  • automations that want the Quick Answer thread id for later inspection

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Authentication

Required: KAGI_SESSION_TOKEN Quick Answer uses subscriber session-token auth. The CLI accepts either:
  • the raw session token
  • the full Session Link URL such as https://kagi.com/search?token=...

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Arguments

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<QUERY> (Required)

The text to send to Quick Answer. The CLI sends the query verbatim. It does not auto-append a trailing question mark, so both of these are valid: 
kagi quick "what is rust"
kagi quick "what is rust?"

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Options

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--format <FORMAT>

Output format for the response. Supported values: json, compact, pretty, markdown Default: json 
kagi quick --format pretty "what is rust"
kagi quick --format markdown "what is rust"

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--no-color

Disable ANSI colors in --format pretty. 
kagi quick --format pretty --no-color "what is rust"

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--lens <INDEX>

Scope the query to one of your Kagi lenses by numeric index. 
kagi quick --lens 0 "best rust tutorials"
Lens indices are user-specific. Use the same l= numeric value you would use with kagi search --lens.

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Output Format

Default JSON output: 
{
  "meta": {
    "version": "202603171911.stage.707e740",
    "trace": "trace-123"
  },
  "query": "what is rust",
  "lens": null,
  "message": {
    "id": "msg-1",
    "thread_id": "thread-1",
    "created_at": "2026-03-19T00:00:00Z",
    "state": "done",
    "prompt": "what is rust",
    "html": "<p>Rust is a systems programming language.</p>",
    "markdown": "Rust is a systems programming language."
  },
  "references": {
    "markdown": "[^1]: [Rust](https://www.rust-lang.org/) (26%)",
    "items": [
      {
        "index": 1,
        "title": "Rust",
        "domain": "www.rust-lang.org",
        "url": "https://www.rust-lang.org/",
        "contribution_pct": 26
      }
    ]
  },
  "followup_questions": [
    "Why is Rust memory-safe?"
  ]
}

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Fields

FieldTypeDescription
metaobjectStream metadata such as version and trace id
querystringThe original query text sent to Quick Answer
lensstring or nullThe requested lens index, if one was supplied
messageobjectFinal Quick Answer message payload
referencesobjectReference markdown plus parsed reference items
followup_questionsarrayFollow-up suggestions returned by Kagi

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Examples

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Basic Queries

kagi quick "what is rust"
kagi quick "best way to clean cast iron"

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Pretty Terminal Output

kagi quick --format pretty "what is rust"

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Markdown for Notes

kagi quick --format markdown "what is rust?" > quick-answer.md

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Lens-Scoped Quick Answers

kagi quick --lens 0 "best rust tutorials"

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JSON Processing

# Extract the answer body
kagi quick "what is rust" | jq -r '.message.markdown'

# Extract reference URLs
kagi quick "what is rust" | jq -r '.references.items[].url'

# Save the Quick Answer thread id
kagi quick "what is rust" | jq -r '.message.thread_id'

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Output Modes

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json

Pretty-printed JSON envelope for scripts and inspection.

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compact

Minified JSON envelope for pipelines or storage-sensitive paths.

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pretty

Terminal-friendly answer text followed by a references section and any follow-up questions.

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markdown

The answer markdown, then the references markdown, then a follow-up section if present.

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Limitations

  • Requires an active Kagi subscription and session token
  • This command is single-turn only
  • The returned message.thread_id is informational today; there is no --thread-id follow-up mode yet
  • Output quality and references depend on the live Quick Answer product

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See Also

  • assistant - Conversational multi-turn AI via Kagi Assistant
  • search - Full search results instead of a single synthesized answer
  • Authentication - Session-token setup