Parallel Deep Research

Deep, multi-source research for complex topics requiring synthesis from many sources. Returns comprehensive reports with citations.

When to Use

Trigger this skill when the user asks for:

"deep research on...", "thorough investigation of...", "comprehensive report about..."
"research everything about...", "full analysis of..."
Complex topics requiring synthesis from 10+ sources
Competitive analysis, market research, due diligence
Questions where depth and accuracy matter more than speed

NOT for:

Quick lookups or simple questions (use parallel-search)
Current news or recent events (use parallel-search with
```
--after-date
```
)
Reading specific URLs (use parallel-extract)

Quick Start

parallel-cli research run "your research question" --processor pro-fast --json -o ./report

CLI Reference

Basic Usage

parallel-cli research run "<question>" [options]

Common Flags

Flag	Description
`-p, --processor <tier>`	Processor tier (see table below)
`--json`	Output as JSON
`-o, --output <path>`	Save results to file (creates .json and .md)
`-f, --input-file <path>`	Read query from file (for long questions)
`--timeout N`	Max wait time in seconds (default: 3600)
`--no-wait`	Return immediately, poll later with `research status`

Processor Tiers

Processor	Time	Use Case
`lite-fast`	10-20s	Quick lookups
`base-fast`	15-50s	Simple questions
`core-fast`	15s-100s	Moderate research
`pro-fast`	30s-5min	Exploratory research (default)
`ultra-fast`	1-10min	Multi-source deep research
`ultra2x-fast`	1-20min	Difficult deep research
`ultra4x-fast`	1-40min	Very difficult research
`ultra8x-fast`	1min-1hr	Most challenging research

Non-fast variants (e.g.,

pro

ultra

) take longer but use fresher data.

Examples

Basic research:

parallel-cli research run "What are the latest developments in quantum computing?" \
  --processor pro-fast \
  --json -o ./quantum-report

Deep competitive analysis:

parallel-cli research run "Compare Stripe, Square, and Adyen payment platforms: features, pricing, market position, and developer experience" \
  --processor ultra-fast \
  --json -o ./payments-analysis

Long research question from file:

# Create question file
cat > /tmp/research-question.txt << 'EOF'
Investigate the current state of AI regulation globally:
1. What regulations exist in the US, EU, and China?
2. What's pending or proposed?
3. How do companies like OpenAI, Google, and Anthropic respond?
4. What industry groups are lobbying for/against regulation?
EOF

parallel-cli research run -f /tmp/research-question.txt 

--processor ultra-fast 

--json -o ./ai-regulation-report

Non-blocking research:

# Start research without waiting
parallel-cli research run "research question" --no-wait
Check status later
parallel-cli research status <task-id>
Poll until complete

parallel-cli research poll <task-id> --json -o ./report

Best-Practice Prompting

Research Question

Write 2-5 sentences describing:

The specific question or topic
Scope boundaries (time period, geography, industries)
What aspects matter most (pricing? features? market share?)
Desired output format (comparison table, timeline, pros/cons)

Good:

Compare the top 5 CRM platforms for B2B SaaS companies with 50-200 employees.
Focus on: pricing per seat, integration ecosystem, reporting capabilities.
Include recent 2024-2026 changes and customer reviews from G2/Capterra.

Poor:

Tell me about CRMs

Response Format

Returns structured JSON with:

```
task_id
```
— unique identifier for polling
```
status
```
—
```
pending
```
,
```
running
```
,
```
completed
```
,
```
failed
```
```
result
```
— when complete:
- ```
summary
```
  — executive summary
- ```
findings[]
```
  — detailed findings with sources
- ```
sources[]
```
  — all referenced URLs with titles

Output Handling

When presenting research results:

Lead with the executive summary verbatim
Present key findings without paraphrasing
Include source URLs for all facts
Note any conflicting information between sources
Preserve all facts, names, numbers, dates, quotes

Running Out of Context?

For long conversations, save results and use

sessions_spawn

parallel-cli research run "<question>" --json -o /tmp/research-<topic>

Then spawn a sub-agent:

{
  "tool": "sessions_spawn",
  "task": "Read /tmp/research-<topic>.json and present the executive summary and key findings with sources.",
  "label": "research-summary"
}

Error Handling

Exit Code	Meaning
0	Success
1	Unexpected error (network, parse)
2	Invalid arguments
3	API error (non-2xx)

Prerequisites

Get an API key at parallel.ai
Install the CLI:

curl -fsSL https://parallel.ai/install.sh | bash
export PARALLEL_API_KEY=your-key

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