Agent skill

Parallel Web

by LeonChaoX in LeonChaoX/qinyan-academic-skills

Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API.

MITAuto-check: notesResearch & Science

Install Parallel Web

skills CLI
$ npx skills add LeonChaoX/qinyan-academic-skills --skill parallel-web -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeonChaoX/qinyan-academic-skills parallel-web --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'skills/01-论文检索与文献管理/parallel-web' .claude/skills/parallel-web && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
parallel-web
GitHub stars
943
Used in
1 other repo
Token cost
~2.9k tokens
SKILL.md length
878 words
Files
7 (incl. scripts, references)
Skills in repo
31
Repo updated
First seen
Licence
MIT

At a glance

Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API.

  • Works in 3 steps: Web Search (search command) → Deep Research (research command) → URL Extraction (extract command) —…
  • ALL web searches
  • SKILL.md covers Overview, When to Use This Skill, Two Capabilities and Model Selection Guide, plus 6 more sections
  • Runs Python scripts from its folder; calls python and pip; reaches paper-url.com; needs PARALLEL_API_KEY

What it does

Parallel Web is an agent skill from LeonChaoX/qinyan-academic-skills. 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.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/api_reference.md`, `references/deep_research_guide.md` and `references/extraction_patterns.md`). Compatibility notes: PARALLELAPIKEY required

It sits in Research & Science, covering Web search, Deep research and Citation management. The repository describes itself as: A curated, multilingual library of 182 installable AI agent skills for end-to-end academic research—spanning literature discovery, scientific writing, grant development… The licence is MIT.

When your agent uses it

  • ALL web searches
  • Research queries
  • General information gathering

Example prompts

  • “/parallel-web”

Requirements

  • Python 3
  • A credential in PARALLEL_API_KEY
  • Compatibility (from SKILL.md): PARALLEL_API_KEY required
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Web Search (search command)
  2. Deep Research (research command)
  3. URL Extraction (extract command) — Verification Only

What it can do on your machine

Read from SKILL.md and the folder at commit df5a498. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • paper-url.com

    Also links to:

    • platform.parallel.ai
    • docs.parallel.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • PARALLEL_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    PARALLEL_API_KEY required

    From compatibility in the SKILL.md frontmatter.

Context cost

Parallel Web loads about 2.9k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 878 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~16k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeonChaoX/qinyan-academic-skills at commit df5a498, republished under its MIT licence (© LeonChaoX). 878 words, ~2,909 tokens.

Download SKILL.mdSave it as .claude/skills/parallel-web/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
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
compatibility
PARALLEL_API_KEY required
license
MIT license
metadata.skill-author
K-Dense Inc.

Parallel Web Systems API

Overview

This skill provides access to Parallel Web Systems APIs for web search, deep research, and content extraction. It is the primary tool for all web-related operations in the scientific writer workflow.

Primary interface: Parallel Chat API (OpenAI-compatible) for search and research. Secondary interface: Extract API for URL verification and special cases only.

API Documentation: https://docs.parallel.ai API Key: https://platform.parallel.ai Environment Variable: PARALLEL_API_KEY

When to Use This Skill

Use this skill for ALL of the following:

  • Web Search: Any query that requires searching the internet for information
  • Deep Research: Comprehensive research reports on any topic
  • Market Research: Industry analysis, competitive intelligence, market data
  • Current Events: News, recent developments, announcements
  • Technical Information: Documentation, specifications, product details
  • Statistical Data: Market sizes, growth rates, industry figures
  • General Information: Company profiles, facts, comparisons

Use Extract API only for:

  • Citation verification (confirming a specific URL's content)
  • Special cases where you need raw content from a known URL

Do NOT use this skill for:

  • Academic-specific paper searches (use research-lookup which routes to Perplexity for purely academic queries)
  • Google Scholar / PubMed database searches (use citation-management skill)

Two Capabilities

1. Web Search (search command)

Search the web via the Parallel Chat API (base model) and get a synthesized summary with cited sources.

Best for: General web searches, current events, fact-finding, technical lookups, news, market data.

bash
# Basic search
python scripts/parallel_web.py search "latest advances in quantum computing 2025"

# Use core model for more complex queries
python scripts/parallel_web.py search "compare EV battery chemistries NMC vs LFP" --model core

# Save results to file
python scripts/parallel_web.py search "renewable energy policy updates" -o results.txt

# JSON output for programmatic use
python scripts/parallel_web.py search "AI regulation landscape" --json -o results.json

Key Parameters:

  • objective: Natural language description of what you want to find
  • --model: Chat model to use (base default, or core for deeper research)
  • -o: Output file path
  • --json: Output as JSON

Response includes: Synthesized summary organized by themes, with inline citations and a sources list.

2. Deep Research (research command)

Run comprehensive multi-source research via the Parallel Chat API (core model) that produces detailed intelligence reports with citations.

Best for: Market research, comprehensive analysis, competitive intelligence, technology surveys, industry reports, any research question requiring synthesis of multiple sources.

bash
# Default deep research (core model)
python scripts/parallel_web.py research "comprehensive analysis of the global EV battery market"

# Save research report to file
python scripts/parallel_web.py research "AI adoption in healthcare 2025" -o report.md

# Use base model for faster, lighter research
python scripts/parallel_web.py research "latest funding rounds in AI startups" --model base

# JSON output
python scripts/parallel_web.py research "renewable energy storage market in Europe" --json -o data.json

Key Parameters:

  • query: Research question or topic
  • --model: Chat model to use (core default for deep research, or base for faster results)
  • -o: Output file path
  • --json: Output as JSON
3. URL Extraction (extract command) — Verification Only

Extract content from specific URLs. Use only for citation verification and special cases.

For general research, use search or research instead.

bash
# Verify a citation's content
python scripts/parallel_web.py extract "https://example.com/article" --objective "key findings"

# Get full page content for verification
python scripts/parallel_web.py extract "https://docs.example.com/api" --full-content

# Save extraction to file
python scripts/parallel_web.py extract "https://paper-url.com" --objective "methodology" -o extracted.md

Model Selection Guide

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

ModelLatencyStrengthsUse When
base15s-100sStandard research, factual queriesWeb searches, quick lookups
core60s-5minComplex research, multi-source synthesisDeep 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

python
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
python
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)
python
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 TargetFilename Pattern
Web Searchsources/search_<topic>.mdsearch_YYYYMMDD_HHMMSS_<brief_topic>.md
Deep Researchsources/research_<topic>.mdresearch_YYYYMMDD_HHMMSS_<brief_topic>.md
URL Extractsources/extract_<source>.mdextract_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.

bash
# 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
Show full SKILL.md (350 more words)Show less
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/:

bash
ls sources/  # Check existing saved results

Integration with Scientific Writer

Routing Table
TaskToolCommand
Web search (any)parallel_web.py searchpython scripts/parallel_web.py search "query" -o sources/search_<topic>.md
Deep researchparallel_web.py researchpython scripts/parallel_web.py research "query" -o sources/research_<topic>.md
Citation verificationparallel_web.py extractpython scripts/parallel_web.py extract "url" -o sources/extract_<source>.md
Academic paper searchresearch_lookup.pyRoutes to Perplexity sonar-pro-search
DOI/metadata lookupparallel_web.py extractExtract 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

bash
# 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:

json
{
  "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)

Complementary Skills

SkillUse For
research-lookupAcademic paper searches (routes to Perplexity for scholarly queries)
citation-managementGoogle Scholar, PubMed, CrossRef database searches
literature-reviewSystematic literature reviews across academic databases
scientific-schematicsGenerate diagrams from research findings

© LeonChaoX, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in skills/01-论文检索与文献管理/parallel-web of LeonChaoX/qinyan-academic-skills.

  • SKILL.md
  • references/api_reference.md
  • references/deep_research_guide.md
  • references/extraction_patterns.md
  • references/search_best_practices.md
  • references/workflow_recipes.md
  • scripts/parallel_web.py

Open the folder on GitHubat commit df5a498

Used in 1 other repository

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in LeonChaoX/qinyan-academic-skills, which our catalogue first saw on October 9, 2026.

Compare with similar skills

Parallel Web next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Parallel Web compared with similar skills
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Parallel Web this skillLeonChaoX/qinyan-academic-skills9431 repos~2.9kAutomated safety check: NotesMIT
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Research Analystsimranjeet97/Awsome_AI_Agents229—~150Automated safety check: PassApache-2.0
Ulw Researchrlaope/oh-my-hermes3.2k—~4.2kAutomated safety check: PassMIT
ResearchEliasOulkadi/shokunin114—~3.4kAutomated safety check: PassMIT
Pp Keenablemvanhorn/printing-press-library2.1k—~6.8kAutomated safety check: NotesApache-2.0

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Questions about Parallel Web

What does Parallel Web do?

Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API. Parallel Web is an agent skill from LeonChaoX/qinyan-academic-skills. Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API.

When should I use Parallel Web?

Parallel Web fits situations like: ALL web searches; research queries; general information gathering.

How do I install Parallel Web in Claude Code?

Run `npx skills add LeonChaoX/qinyan-academic-skills --skill parallel-web -a claude-code`. Or copy the skill folder (skills/01-论文检索与文献管理/parallel-web in LeonChaoX/qinyan-academic-skills) into .claude/skills/parallel-web in your project. Claude Code loads it when a task matches its description.

How do I install Parallel Web in Codex?

Run `npx skills add LeonChaoX/qinyan-academic-skills --skill parallel-web -a codex`. Or copy the skill folder (skills/01-论文检索与文献管理/parallel-web in LeonChaoX/qinyan-academic-skills) into .agents/skills/parallel-web in your project. Codex loads it when a task matches its description.

Can I use Parallel Web in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeonChaoX/qinyan-academic-skills --skill parallel-web -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/parallel-web, .gemini/skills/parallel-web, .github/skills/parallel-web and .opencode/skills/parallel-web in your project.

What does Parallel Web need to run?

Going by SKILL.md and its folder, Parallel Web needs Python for the scripts in its folder, the command-line tools its instructions call (python and pip) and credentials named PARALLEL_API_KEY. Our summary lists: Python 3; A credential in PARALLEL_API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash. Compatibility (from SKILL.md): PARALLEL_API_KEY required.

Does Parallel Web access the network?

SKILL.md names 3 domains. In commands or code: paper-url.com; the agent is likely to contact it when it follows the instructions. As links in the text: platform.parallel.ai and docs.parallel.ai. This is read from the text; nothing was executed.

Is Parallel Web safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Parallel Web use?

Parallel Web is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Parallel Web use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.

What are the alternatives to Parallel Web?

Skills that share tags, products or a category with Parallel Web: Live Research (brightdata/skills, 264 stars), Research Analyst (simranjeet97/Awsome_AI_Agents, 229 stars), Ulw Research (rlaope/oh-my-hermes, 3.2k stars) and Research (EliasOulkadi/shokunin, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Parallel Web?

LeonChaoX (a GitHub user) maintains it in LeonChaoX/qinyan-academic-skills, which has 943 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeonChaoX/qinyan-academic-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.