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Answers

Organization
brave
answers

USE FOR AI-grounded answers via OpenAI-compatible /chat/completions. Two modes: single-search (fast) or deep research (enable_research=true, thorough multi-search). Streaming/blocking. Citations.

Overview

Publisherbrave
Repositorybrave-search-skills
Skill nameanswers
Stars
182
Forks
17
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by brave on GitHub. Read the source before you install it.

Installation

Install the Answers AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/brave/brave-search-skills/tree/main/skills/answers
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/brave/brave-search-skills.git /tmp/brave-search-skills
mkdir -p .claude/skills
cp -r /tmp/brave-search-skills/skills/answers .claude/skills/answers
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Answers in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Answers on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Answers is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Answers — AI Grounding

Requires API Key: Get one at https://api.search.brave.com

Plan: Included in the Answers plan. See https://api-dashboard.search.brave.com/app/subscriptions/subscribe

When to Use

Use CaseSkillWhy
Quick factual answer (raw context)llm-contextSingle search, returns raw context for YOUR LLM
Fast AI answer with citationsanswers (single-search)streaming, citations
Thorough multi-search deep researchanswers (research mode)Iterative deep research, synthesized cited answer

This endpoint (/res/v1/chat/completions) supports two modes:

  • Single-search (default): Fast AI-grounded answer from a single search. Supports enable_citations.
  • Research (enable_research=true): Multi-iteration deep research with progress events and synthesized cited answer.

Quick Start (cURL)

Blocking (Single-Search)

bash
curl -X POST "https://api.search.brave.com/res/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}" \
  -d '{
    "messages": [{"role": "user", "content": "How does the James Webb Space Telescope work?"}],
    "stream": false
  }'

Streaming with Citations (Single-Search)

bash
curl -X POST "https://api.search.brave.com/res/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}" \
  -d '{
    "messages": [{"role": "user", "content": "What are recent breakthroughs in fusion energy?"}],
    "stream": true,
    "enable_citations": true
  }'

Research Mode

bash
curl -X POST "https://api.search.brave.com/res/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}" \
  -d '{
    "messages": [{"role": "user", "content": "Compare quantum computing approaches"}],
    "stream": true,
    "enable_research": true,
    "research_maximum_number_of_iterations": 3,
    "research_maximum_number_of_seconds": 120
  }'

Endpoint

http
POST https://api.search.brave.com/res/v1/chat/completions

Authentication: X-Subscription-Token: <API_KEY> header (or Authorization: Bearer <API_KEY>)

SDK Compatible: Works with OpenAI SDK via base_url="https://api.search.brave.com/res/v1"

Two Modes

FeatureSingle-Search (default)Research (enable_research=true)
SpeedFastSlow
Searches1Multiple (iterative)
StreamingOptional (stream=true/false)Required (stream=true)
Citationsenable_citations=true (streaming only)Built-in (in <answer> tag)
Progress eventsNoYes (<progress> tags)
Blocking responseYes (stream=false)No

Parameters

Standard Parameters

ParameterTypeRequiredDefaultDescription
messagesarrayYes-Single user message (exactly 1 message)
streamboolNotrueEnable SSE streaming
countrystringNo"US"Search country (2-letter country code or ALL)
languagestringNo"en"Response language
safesearchstringNo"moderate"Search safety level (off, moderate, strict)
max_completion_tokensintNonullUpper bound on completion tokens
enable_citationsboolNofalseInclude inline citation tags (single-search streaming only)
web_search_optionsobjectNonullOpenAI-compatible; search_context_size: low, medium, high

Research Parameters

ParameterTypeRequiredDefaultDescription
enable_researchboolNofalseEnable research mode
research_allow_thinkingboolNotrueEnable extended thinking
research_maximum_number_of_tokens_per_queryintNo8192Max tokens per query (1024-16384)
research_maximum_number_of_queriesintNo20Max total search queries (1-50)
research_maximum_number_of_iterationsintNo4Max research iterations (1-5)
research_maximum_number_of_secondsintNo180Time budget in seconds (1-300)
research_maximum_number_of_results_per_queryintNo60Results per search query (1-60)

Constraints (IMPORTANT)

ConstraintError
enable_research=true requires stream=true"Blocking response doesn't support 'enable_research' option"
enable_research=true incompatible with enable_citations=true"Research mode doesn't support 'enable_citations' option"
enable_citations=true requires stream=true"Blocking response doesn't support 'enable_citations' option"

OpenAI SDK Usage

Blocking (Single-Search)

python
from openai import OpenAI

client = OpenAI(
    base_url="https://api.search.brave.com/res/v1",
    api_key="your-brave-api-key",
)

response = client.chat.completions.create(
    model="brave",
    messages=[{"role": "user", "content": "How does the James Webb Space Telescope work?"}],
    stream=False,
)
print(response.choices[0].message.content)

Streaming with Citations (Single-Search)

python
from openai import OpenAI

client = OpenAI(
    base_url="https://api.search.brave.com/res/v1",
    api_key="your-brave-api-key",
)

stream = client.chat.completions.create(
    model="brave",
    messages=[{"role": "user", "content": "What are the current trends in renewable energy?"}],
    stream=True,
    extra_body={"enable_citations": True}
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Research Mode

python
from openai import AsyncOpenAI

client = AsyncOpenAI(
    base_url="https://api.search.brave.com/res/v1",
    api_key="your-brave-api-key",
)

stream = await client.chat.completions.create(
    model="brave",
    messages=[{"role": "user", "content": "Compare quantum computing approaches"}],
    stream=True,
    extra_body={
        "enable_research": True,
        "research_maximum_number_of_iterations": 3,
        "research_maximum_number_of_seconds": 120
    }
)

async for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Response Format

Blocking Response (stream=false, single-search only)

Standard OpenAI-compatible JSON:

json
{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "choices": [{"message": {"role": "assistant", "content": "The James Webb Space Telescope works by..."}, "index": 0, "finish_reason": "stop"}],
  "usage": {"prompt_tokens": 10, "completion_tokens": 50, "total_tokens": 60}
}

Streaming Response

SSE response with OpenAI-compatible chunks:

text
data: {"id":"chatcmpl-...","object":"chat.completion.chunk","choices":[{"delta":{"content":"Based on"},"index":0}]}

data: {"id":"chatcmpl-...","object":"chat.completion.chunk","choices":[{"delta":{"content":" recent research"},"index":0}]}

data: [DONE]

Streaming Tags by Mode

Single-Search (with enable_citations=true)
TagPurpose
<citation>Inline citation references
<usage>JSON cost/billing data
Research Mode
TagPurposeKeep?
<queries>Generated search queriesDebug
<analyzing>URL counts (verbose)Debug
<thinking>URL selection reasoningDebug
<progress>Stats: time, iterations, queries, URLs analyzed, tokensMonitor
<blindspots>Knowledge gaps identifiedYes
<answer>Final synthesized answer (only the final answer is emitted; intermediate drafts are dropped)Yes
<usage>JSON cost/billing data (included at end of streaming response)Yes

Usage Tag Format

The <usage> tag contains JSON-stringified cost and token data:

text
<usage>{"X-Request-Requests":1,"X-Request-Queries":8,"X-Request-Tokens-In":15000,"X-Request-Tokens-Out":2000,"X-Request-Requests-Cost":0.005,"X-Request-Queries-Cost":0.032,"X-Request-Tokens-In-Cost":0.075,"X-Request-Tokens-Out-Cost":0.01,"X-Request-Total-Cost":0.122}</usage>

Use Cases

  • Chat interface integration: Drop-in OpenAI SDK replacement with web-grounded answers. Set base_url="https://api.search.brave.com/res/v1".
  • Deep research / comprehensive topic research: Use research mode (enable_research=true) for complex questions needing multi-source synthesis (e.g., "Compare approaches to nuclear fusion").
  • OpenAI SDK drop-in: Same SDK, same streaming format — just change base_url and api_key. Works with both sync and async clients.
  • Cited answers: Enable enable_citations=true in single-search mode for inline citation tags, or use research mode which automatically includes citations in its answer.

Notes

  • Timeout: Set client timeout to at least 30s for single-search, 300s (5 min) for research
  • Single message: The messages array must contain exactly 1 user message
  • Cost monitoring: Parse the <usage> tag from streaming responses to track costs

Frequently asked questions

What does the Answers AI skill do?

USE FOR AI-grounded answers via OpenAI-compatible /chat/completions. Two modes: single-search (fast) or deep research (enable_research=true, thorough multi-search). Streaming/blocking. Citations.

Why use Answers on TypingMind?

Because you install it once and use it with any model. Answers is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Answers in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/brave/brave-search-skills/tree/main/skills/answers. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Answers?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Answers?

As many as you like. As long as a model supports skills, you can use Answers with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Answers AI skill free?

Yes. It is published on GitHub by brave under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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