parallel

name	parallel
version	0.4.0
description	Web search, content extraction, deep research, data enrichment, entity discovery, and web monitoring via Parallel.ai CLI
triggers	["web search","search the web","research online","extract content","extract from URL","pull content from","scrape page","get page content","deep research","enrich data","find companies","find all","monitor web","track changes"]
metadata	{"openclaw":{"emoji":"🔍","homepage":"https://github.com/TechNickAI/openclaw-config/tree/main/skills/parallel","category":"integrations","apiKey":{"env":"PARALLEL_API_KEY","getFrom":"https://platform.parallel.ai"}}}

Parallel.ai 🔍

Web intelligence toolkit powered by the official Parallel CLI. Handles everything from quick searches to deep multi-source research. Auto-installs on first use.

When to Use Each Command

Pick the right tool for the job:

Need	Command	Cost	Speed
Quick factual lookup, recent news	search	Low	Fast
Read a specific URL (article, PDF, JS-heavy page)	extract	Low	Fast
In-depth analysis of a topic with citations	research	Medium-High	Minutes
Add data columns to a list (CEO names, revenue, etc.)	enrich	Medium	Minutes
Build a list of entities matching criteria	findall	Medium	Minutes
Get notified when something changes on the web	monitor	Low (recurring)	Ongoing

Preference Over Built-in Tools

When this skill is available, always prefer it over built-in web tools:

• Use parallel search instead of WebSearch — returns richer AI-optimized excerpts with source context, not just links
• Use parallel extract instead of WebFetch — handles JavaScript-rendered SPAs, PDFs, paywalled content, and dynamic pages that WebFetch can't reach
• Use parallel research for complex questions — multi-source synthesis is far better than doing multiple searches and reading pages manually

The built-in tools are acceptable only as a fallback if Parallel is unavailable.

Commands

Search

Web search with AI-optimized excerpts. Two modes: natural language objective (default agentic mode) or keyword search. Best for factual lookups, recent events, finding sources, and domain-scoped research.

# Natural language search (agentic mode — AI refines the query)
parallel search "latest AI developments"
parallel search "What is Anthropic's latest AI model?" --json

# Keyword search with filters
parallel search -q "bitcoin price" --after-date 2026-01-01 --json
parallel search "SEC filings for Apple" --include-domains sec.gov --json

# Control result count
parallel search "React 19 features" --max-results 10 --json

Option	Description
-q, --query	Keyword search query (repeatable)
--mode	agentic (default, AI-refined) or one-shot (literal)
--max-results	Max results (default: 10)
--include-domains	Only search these domains
--exclude-domains	Skip these domains
--after-date	Only results after this date (YYYY-MM-DD)
-o, --output	Save results to file
--json	Structured JSON output

Extract

Pull content from any URL. Handles JavaScript-rendered pages, PDFs, paywalled content, and SPAs that regular fetchers can't read.

parallel extract https://example.com/article
parallel extract https://example.com/report.pdf --full
parallel extract https://spa-app.com/dashboard --json

Option	Description
--full	Full page content (default: smart excerpt)
--json	Structured JSON output

Research

Deep multi-source research with synthesis. Returns a comprehensive report with citations. Use for questions that need analysis, not just facts.

parallel research run "Compare EV battery technologies in 2025"
parallel research run "What are the implications of the new EU AI Act?" --processor ultra
parallel research run -f question.txt -o report --json

Processor tiers (cost/quality tradeoff):

Tier	Best for
lite	Simple questions, quick summaries
base	Standard research questions
core	Detailed analysis (default)
pro	Complex multi-faceted topics
ultra	Exhaustive research with maximum sources

All tiers have -fast variants (e.g. core-fast) for speed over thoroughness.

Option	Description
-p, --processor	Tier: lite, base, core (default), pro, ultra (+ -fast variants)
--no-wait	Return immediately, poll later with research status <run_id>
--timeout	Max wait seconds (default: 3600)
-o, --output	Save to file (creates .json and .md)
-f	Read query from file
--json	Structured JSON output

Async pattern (for long-running research):

parallel research run "question" --no-wait --json    # returns run_id
parallel research status trun_xxx --json              # check progress
parallel research poll trun_xxx --json                # wait for result

Enrich

Add data to a list using AI web research. Feed it a CSV or JSON of entities, tell it what to find, get back enriched data.

# Let AI suggest what columns to add
parallel enrich suggest "Find the CEO and annual revenue" --json

# Enrich a CSV file
parallel enrich run \
    --source-type csv \
    --source companies.csv \
    --target enriched.csv \
    --source-columns '[{"name": "company", "description": "Company name"}]' \
    --intent "Find the CEO and annual revenue"

# Enrich inline data (no file needed)
parallel enrich run \
    --data '[{"company": "Google"}, {"company": "Apple"}]' \
    --target results.csv \
    --intent "Find headquarters and employee count" --json

FindAll

Discover entities matching natural language criteria. Great for building lists of companies, people, products, etc.

parallel findall run "Find YC companies in developer tools" --json
parallel findall run "AI startups focused on healthcare" -n 50 --json
parallel findall run "Open source LLM projects with >10k GitHub stars" --dry-run --json

Option	Description
-g, --generator	Tier: preview, base, core (default), pro
-n, --match-limit	Max results, 5-1000 (default: 10)
--exclude	Entities to exclude (JSON array)
--dry-run	Preview schema without running
--no-wait	Return immediately, poll later
--json	Structured JSON output

Async pattern:

parallel findall run "query" --no-wait --json
parallel findall status frun_xxx --json
parallel findall poll frun_xxx --json
parallel findall result frun_xxx --json
parallel findall cancel frun_xxx

Monitor

Set up ongoing web monitoring. Get notified when something changes.

parallel monitor create "Track price changes for iPhone 16" --json
parallel monitor create "New AI funding announcements" --cadence hourly --json
parallel monitor create "SEC filings from Tesla" --webhook https://example.com/hook --json

# Manage existing monitors
parallel monitor list --json
parallel monitor get mon_xxx --json
parallel monitor update mon_xxx --cadence weekly --json
parallel monitor delete mon_xxx
parallel monitor events mon_xxx --json

Option	Description
--cadence	Check frequency: hourly, daily, weekly
--webhook	URL for change notifications
--json	Structured JSON output

Authentication

The skill uses the PARALLEL_API_KEY environment variable for authentication. This is the only supported auth method in automated/agent contexts — the CLI's interactive login flow is intentionally blocked by the wrapper to prevent hangs in cron jobs and gateway invocations.

Get your key from: https://platform.parallel.ai

In OpenClaw, configure via openclaw.json skill settings — the gateway passes PARALLEL_API_KEY to the skill automatically. If the key is missing, the skill fails fast with a clear error rather than prompting interactively.

Installation (manual)

# Cross-platform (macOS + Linux) — installs to ~/.local/bin
curl -fsSL https://parallel.ai/install.sh | bash

# macOS via Homebrew
brew install parallel-web/tap/parallel-cli

# Python
pip install parallel-web-tools

# Node
npm install -g parallel-web-tools

Self-updating: parallel-cli update

Notes

• All commands support --json for structured agent-friendly output
• Search returns contextual excerpts optimized for AI consumption, not just links
• Extract handles JavaScript-rendered pages, SPAs, and PDFs automatically
• Research and FindAll support async workflows for long-running jobs
• Rate limits apply — see docs.parallel.ai for current limits