Agent skill · Data & Analytics

parallel-web

All-in-one web toolkit powered by parallel-cli, with a strong emphasis on academic and scientific sources. Use this skill whenever the user needs to search the web, fetch/extract URL content, enrich data with web-sourced fields, or run deep research reports. Covers: web search (fast lookups, research, current info — prioritizing peer-reviewed papers, preprints, and scholarly databases), URL extraction (fetching pages, articles, academic PDFs), bulk data enrichment (adding fields to CSV/lists from the web), and deep research (exhaustive multi-source reports grounded in academic literature). Als

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill parallel-web-k-dense-ai-scientific-agent-ski --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Declared author: K-Dense, Inc.
Requires: Requires parallel-cli and internet access.
Path: skills/analysis/parallel-web-k-dense-ai-scientific-agent-ski/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Parallel Web Toolkit A unified skill for all web-powered tasks: searching, extracting, enriching, and researching — with academic and scientific sources as the default priority. ## Routing — pick the right capability Read the user's request and match it to one of the capabilities below. For web search, extract, enrichment, and deep research, read the corresponding reference file for detailed instructions. | User wants to... | Capability | Where | |---|---|---| | Look something up, research a topic, find current info | **Web Search** | `references/web-search.md` | | Fetch content from a specific URL (webpage, article, PDF) | **Web Extract** | `references/web-extract.md` | | Add web-sourced fields to a list of companies/people/products | **Data Enrichment** | `references/data-enrichment.md` | | Get an exhaustive, multi-source report (user says "deep research", "exhaustive", "comprehensive") | **Deep Research** | `references/deep-research.md` | | Install or authenticate parallel-cli | **Setup** | Below | | Check status of a running research/enrichment task | **Status** | Below | | Retrieve completed research results by run ID | **Result** | Below | ### Decision guide - **Default to

What's inside
Steps it walks through
  1. Routing — pick the right capability
  2. Decision guide
  3. Academic source priority
  4. Context chaining
  5. Setup
  6. Check task status
  7. Get completed result
Ships with 1 file
  • metadata.json
Commands it runs
curl -fsSL https://parallel.ai/install.sh | bash
uv tool install "parallel-web-tools[cli]"
dotenv -f .env run parallel-cli auth
parallel-cli login
parallel-cli auth
parallel-cli research status "$RUN_ID" --json
parallel-cli research poll "$RUN_ID" --json
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About this skill
What does the parallel-web skill do?

All-in-one web toolkit powered by parallel-cli, with a strong emphasis on academic and scientific sources. Use this skill whenever the user needs to search the web, fetch/extract URL content, enrich data with web-sourced fields, or run deep research reports. Covers: web search (fast lookups, research, current info — prioritizing peer-reviewed papers, preprints, and scholarly databases), URL extraction (fetching pages, articles, academic PDFs), bulk data enrichment (adding fields to CSV/lists from the web), and deep research (exhaustive multi-source reports grounded in academic literature). Als

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill parallel-web-k-dense-ai-scientific-agent-ski --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going