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Parallel Web Extract

Organization
parallel-web
parallel-web-extract

CLI-backed URL extraction. Use when the user explicitly invokes this skill, needs CLI-only controls or saved JSON output, or no Parallel web_fetch MCP tool is available. When the bundled Parallel Search MCP is available, prefer its web_fetch tool for ordinary webpages, articles, PDFs, and JavaScript-heavy sites.

Overview

Publisherparallel-web
Repositoryparallel-agent-skills
Skill nameparallel-web-extract
Stars
77
Forks
10
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by parallel-web on GitHub. Read the source before you install it.

Installation

Install the Parallel Web Extract AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-web-extract
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/parallel-web/parallel-agent-skills.git /tmp/parallel-agent-skills
mkdir -p .claude/skills
cp -r /tmp/parallel-agent-skills/skills/parallel-web-extract .claude/skills/parallel-web-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Parallel Web Extract in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Parallel Web Extract on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Parallel Web Extract is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

URL Extraction

Extract content from: $ARGUMENTS

Command

Choose a short, descriptive filename based on the URL or content (e.g., vespa-docs, react-hooks-api). Use lowercase with hyphens, no spaces. Substitute it into the command inline — $FILENAME is a placeholder, not a shell variable.

Pass each requested URL as a separate quoted positional argument, up to 20 per call. Do not collapse multiple URLs into one quoted $ARGUMENTS string or use eval to split them. Construct arguments directly from the requested URLs. For example:

bash
parallel-cli extract "https://docs.parallel.ai/integrations/cli" "https://docs.parallel.ai/integrations/cursor-marketplace" --json -o "/tmp/parallel-docs.json"

-o saves JSON. Use a .json extension and inspect an existing path before use because Extract overwrites it. Read the saved file as authoritative; stdout may truncate and human-readable output previews only part of the content. Do not treat a stale file as a successful response after a failed call.

Options if needed:

  • --objective "focus area" to focus extraction on a specific goal (also silences the "neither objective nor search_queries" warning that V1 emits when neither is set)
  • -q "keyword" (repeatable) to prioritize keywords in excerpts
  • --full-content to include the complete page body (for long articles, PDFs, or when excerpts may not capture what you need)
  • --full-content-max-chars N to cap full-content size per result
  • --no-excerpts to strip excerpts when you only want full content
  • --session-id "<returned-session-id>" to group related Search/Extract calls. A session ID is not a Task interaction ID or run ID; never use it with research status/poll or --previous-interaction-id

Handling failed extractions

Inspect the exit status, API error, results, per-URL errors and any warnings. errors: [] is normal success. Nonempty errors can coexist with successful results: retain and present successful content, then name each failed URL and its returned reason. Empty results or missing content are not a successful extraction. Do not fabricate content. For affected URLs, suggest:

  • Verifying the URL (the page may have moved)
  • Requesting --full-content if excerpts are empty but the returned metadata supports that the page was fetched
  • Using parallel-cli search to locate the current URL if the page was renamed

Response format

Return content as:

Page Title

Use returned full_content for full-page requests; excerpts alone are selected passages and must be labelled as such. Even full content may be capped by --full-content-max-chars or upstream limits; do not promise completeness when capped. Preserve retrieved content verbatim, with these rules:

  • Keep content verbatim - do not paraphrase or summarize
  • Preserve every numbered/bulleted item in the retrieved content; do not claim an excerpt contains the whole page
  • Strip only obvious noise: nav menus, footers, ads
  • Preserve all facts, names, numbers, dates, quotes

After the response, mention the output file path (/tmp/$FILENAME.json) so the user knows it's available for follow-up questions.

For large content, keep the full verbatim text in the saved file and provide a brief labelled preview plus its path. Never silently truncate content while claiming it is the complete extraction.

Setup

If parallel-cli is not found, install and authenticate:

bash
/parallel:parallel-cli-setup

If a documented command or option is missing, check the installed version and upgrade through its installation method: standalone parallel-cli update, pipx pipx upgrade parallel-web-tools, uv uv tool upgrade parallel-web-tools, Homebrew brew upgrade parallel-web/tap/parallel-cli, or npm npm update -g parallel-web-cli. Verify help in the same terminal before retrying.

For authentication errors, inspect parallel-cli auth --json and its authenticated boolean; exit zero alone does not prove authentication. A 403 can indicate permissions, policy or billing. Report the actual error; check balance only for a billing-specific failure and never add funds without explicit confirmation.

Frequently asked questions

What does the Parallel Web Extract AI skill do?

CLI-backed URL extraction. Use when the user explicitly invokes this skill, needs CLI-only controls or saved JSON output, or no Parallel web_fetch MCP tool is available. When the bundled Parallel Search MCP is available, prefer its web_fetch tool for ordinary webpages, articles, PDFs, and JavaScript-heavy sites.

Why use Parallel Web Extract on TypingMind?

Because you install it once and use it with any model. Parallel Web Extract is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Parallel Web Extract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-web-extract. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Parallel Web Extract?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Parallel Web Extract?

As many as you like. As long as a model supports skills, you can use Parallel Web Extract with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Parallel Web Extract AI skill free?

Yes. It is published on GitHub by parallel-web under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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