parallel-web

name	parallel-web
description	Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API. Use for ALL web searches, research queries, and general information gathering. Provides synthesized summaries with citations.
allowed-tools	Read Write Edit Bash
license	MIT license
compatibility	PARALLEL_API_KEY required
tags	["scientific-skills","parallel-web","api","writing","search"]
metadata	{"skill-author":"K-Dense Inc."}

Model Selection Guide

The Chat API supports two research models. Use base for most searches and core for deep research.

Model	Latency	Strengths	Use When
base	15s-100s	Standard research, factual queries	Web searches, quick lookups
core	60s-5min	Complex research, multi-source synthesis	Deep research, comprehensive reports

Recommendations:

• search command defaults to base — fast, good for most queries
• research command defaults to core — thorough, good for comprehensive reports
• Override with --model when you need different depth/speed tradeoffs

---

Python API Usage

Search

from parallel_web import ParallelSearch

searcher = ParallelSearch()
result = searcher.search(
    objective="Find latest information about transformer architectures in NLP",
    model="base",
)

if result["success"]:
    print(result["response"])  # Synthesized summary
    for src in result["sources"]:
        print(f"  {src['title']}: {src['url']}")

Deep Research

from parallel_web import ParallelDeepResearch

researcher = ParallelDeepResearch()
result = researcher.research(
    query="Comprehensive analysis of AI regulation in the EU and US",
    model="core",
)

if result["success"]:
    print(result["response"])  # Full research report
    print(f"Citations: {result['citation_count']}")

Extract (Verification Only)

from parallel_web import ParallelExtract

extractor = ParallelExtract()
result = extractor.extract(
    urls=["https://docs.example.com/api-reference"],
    objective="API authentication methods and rate limits",
)

if result["success"]:
    for r in result["results"]:
        print(r["excerpts"])

---

MANDATORY: Save All Results to Sources Folder

Every web search and deep research result MUST be saved to the project's sources/ folder.

This ensures all research is preserved for reproducibility, auditability, and context window recovery.

Saving Rules

Operation	-o Flag Target	Filename Pattern
Web Search	sources/search_<topic>.md	search_YYYYMMDD_HHMMSS_<brief_topic>.md
Deep Research	sources/research_<topic>.md	research_YYYYMMDD_HHMMSS_<brief_topic>.md
URL Extract	sources/extract_<source>.md	extract_YYYYMMDD_HHMMSS_<brief_source>.md

How to Save (Always Use -o Flag)

CRITICAL: Every call to parallel_web.py MUST include the -o flag pointing to the sources/ folder.

# Web search — ALWAYS save to sources/
python scripts/parallel_web.py search "latest advances in quantum computing 2025" \
  -o sources/search_20250217_143000_quantum_computing.md

# Deep research — ALWAYS save to sources/
python scripts/parallel_web.py research "comprehensive analysis of the global EV battery market" \
  -o sources/research_20250217_144000_ev_battery_market.md

# URL extraction (verification only) — save to sources/
python scripts/parallel_web.py extract "https://example.com/article" --objective "key findings" \
  -o sources/extract_20250217_143500_example_article.md

Why Save Everything

1. Reproducibility: Every claim in the final document can be traced back to its raw source material
2. Context Window Recovery: If context is compacted mid-task, saved results can be re-read from sources/
3. Audit Trail: The sources/ folder provides complete transparency into how information was gathered
4. Reuse Across Sections: Saved research can be referenced by multiple sections without duplicate API calls
5. Cost Efficiency: Avoid redundant API calls by checking sources/ for existing results
6. Peer Review Support: Reviewers can verify the research backing every claim

Logging

When saving research results, always log:

[HH:MM:SS] SAVED: Search results to sources/search_20250217_143000_quantum_computing.md
[HH:MM:SS] SAVED: Deep research report to sources/research_20250217_144000_ev_battery_market.md

Before Making a New Query, Check Sources First

Before calling parallel_web.py, check if a relevant result already exists in sources/:

ls sources/  # Check existing saved results

---

Integration with Scientific Writer

Routing Table

Task	Tool	Command
Web search (any)	parallel_web.py search	python scripts/parallel_web.py search "query" -o sources/search_<topic>.md
Deep research	parallel_web.py research	python scripts/parallel_web.py research "query" -o sources/research_<topic>.md
Citation verification	parallel_web.py extract	python scripts/parallel_web.py extract "url" -o sources/extract_<source>.md
Academic paper search	research_lookup.py	Routes to Perplexity sonar-pro-search
DOI/metadata lookup	parallel_web.py extract	Extract from DOI URLs (verification)

When Writing Scientific Documents

1. Before writing any section, use search or research to gather background information — save results to sources/
2. For academic citations, use research-lookup (which routes academic queries to Perplexity) — save results to sources/
3. For citation verification (confirming a specific URL), use parallel_web.py extract — save results to sources/
4. For current market/industry data, use parallel_web.py research --model core — save results to sources/
5. Before any new query, check sources/ for existing results to avoid duplicate API calls

---

Environment Setup

# Required: Set your Parallel API key
export PARALLEL_API_KEY="your_api_key_here"

# Required Python packages
pip install openai        # For Chat API (search/research)
pip install parallel-web  # For Extract API (verification only)

Get your API key at https://platform.parallel.ai

---

Error Handling

The script handles errors gracefully and returns structured error responses:

{
  "success": false,
  "error": "Error description",
  "timestamp": "2025-02-14 12:00:00"
}

Common issues:

• PARALLEL_API_KEY not set: Set the environment variable
• openai not installed: Run pip install openai
• parallel-web not installed: Run pip install parallel-web (only needed for extract)
• Rate limit exceeded: Wait and retry (default: 300 req/min for Chat API)

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Complementary Skills

Skill	Use For
research-lookup	Academic paper searches (routes to Perplexity for scholarly queries)
citation-management	Google Scholar, PubMed, CrossRef database searches
literature-review	Systematic literature reviews across academic databases
scientific-schematics	Generate diagrams from research findings