Documentation Index
Fetch the complete documentation index at: https://usenaive.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Three search modes, each with increasing depth and cost:
| Command | Description | Cost |
|---|
naive search <query> | Quick web search | 1 credit |
naive search url <url> | Extract content from a URL | 1 credit |
naive search research <query> | Deep multi-source AI research (async) | 3–8 credits |
Web Search
naive search "best project management tools 2026"
naive search "competitor analysis SaaS pricing" --count 10
Options
| Flag | Required | Description |
|---|
query | Yes | Search query (positional argument) |
--count <n> | No | Number of results (default: 5, max: 20) |
Output
{
"success": true,
"action": "search",
"result": {
"results": [
{ "title": "Top PM Tools in 2026", "url": "https://example.com/article", "snippet": "A comprehensive look at...", "score": 0.95 },
{ "title": "Building Better Teams", "url": "https://blog.example.com/post", "snippet": "How to organize..." }
],
"credits_used": 1,
"credits_remaining": 99,
"provider": "web"
},
"next_steps": [
{ "command": "naive search url https://example.com/article", "description": "Extract full content from the top result" },
{ "command": "naive search research \"best project management tools 2026\"", "description": "Run deep research on this topic" },
{ "command": "naive search \"best project management tools 2026\" --count 10", "description": "Get more results" }
],
"hints": ["Found 5 results", "Use 'naive search url <url>' to extract full page content", "Cost: 1 credit"]
}
Fetches a URL and extracts content. Optionally uses AI to extract specific information.
naive search url https://example.com/pricing
naive search url https://news.ycombinator.com --extract "top 5 stories with links"
naive search url https://docs.example.com/api --extract "authentication methods"
Options
| Flag | Required | Description |
|---|
url | Yes | URL to fetch and extract from |
--extract <prompt> | No | AI extraction prompt for targeted information |
Output
{
"success": true,
"action": "search.url",
"result": {
"url": "https://example.com/pricing",
"title": "",
"content": "...(raw text content, up to 5000 chars)...",
"extracted": "Free: $0/mo, Pro: $29/mo, Enterprise: custom",
"credits_used": 1,
"credits_remaining": 98
},
"next_steps": [
{ "command": "naive search url https://example.com/pricing --extract \"specific question\"", "description": "Re-extract with a different focus" },
{ "command": "naive search \"related topic\"", "description": "Search for related information" }
],
"hints": ["Use --extract to focus on specific information from the page", "Cost: 1 credit"]
}
When --extract is provided and AI extraction is configured, an LLM extracts the specific information you requested from the page content. Without --extract, you get the raw text content.
Deep Research
Multi-source, AI-synthesized research. Runs synchronously for “quick” depth, asynchronously for thorough/exhaustive.
naive search research "market size for AI developer tools" --depth thorough
naive search research "competitive analysis: Figma vs Canva" --depth exhaustive --wait
naive search research "microservice auth best practices" --depth quick
Options
| Flag | Required | Description |
|---|
query | Yes | Research topic |
--depth <level> | No | quick (default), thorough, or exhaustive |
--wait | No | Block until research completes (for thorough/exhaustive) |
Depth Levels
| Level | Sources | Behavior | Cost |
|---|
quick | 5 | Synchronous (immediate response) | 3 credits |
thorough | 8 | Async job (~45s) | 5 credits |
exhaustive | 15 | Async job (~90s) | 8 credits |
Output (quick — inline response)
{
"success": true,
"action": "search.research",
"result": {
"synthesis": "Based on analysis of 5 sources...",
"sources": [
{ "url": "https://...", "title": "...", "relevance": 0.9 }
],
"credits_used": 3,
"credits_remaining": 97
},
"next_steps": [
{ "command": "naive search \"follow-up query\"", "description": "Quick search for additional context" }
],
"hints": ["Research completed synchronously (quick depth)"]
}
Output (thorough/exhaustive — submitted)
{
"success": true,
"action": "search.research.submitted",
"result": { "job_id": "job-uuid-123", "status": "queued", "depth": "thorough" },
"next_steps": [
{ "command": "naive jobs get job-uuid-123", "description": "Check research progress" },
{ "command": "naive jobs --status running", "description": "List all running jobs" }
],
"hints": [
"Research job submitted (depth: thorough)",
"Credits will be deducted only on successful completion",
"Expected completion: ~45s"
]
}
Output (completed — with --wait)
{
"success": true,
"action": "search.research.completed",
"result": {
"id": "job-uuid-123",
"status": "completed",
"type": "deep_research",
"result": {
"synthesis": "Based on analysis of 8 sources...",
"sources": [
{ "url": "https://...", "title": "...", "relevance": 0.92 }
]
},
"credits_used": 5
},
"next_steps": [
{ "command": "naive search \"related topic\"", "description": "Search for additional information" },
{ "command": "naive search url <url>", "description": "Deep-dive into a specific source from the report" }
],
"hints": ["Research completed successfully"]
}
Credit behavior: Credits are NOT deducted at submission. They are deducted only when the job completes successfully. Failed or cancelled research jobs cost nothing.