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ZICQ

Skills ZICQ category:Writing & Research parallel-web-search

Parallel Web Search

DEFAULT for all research and web queries. Use for any lookup, research, investigation, or question needing current info. Fast and cost-effective. Only use parallel-deep-research if user explicitly requests 'deep' or 'exhaustive' research.

13122 installs

Official URL:skills.sh

What this skill does

Intro in this page language first. The official description stays in its original wording; we do not rewrite SKILL.md.

What it does

DEFAULT for all research and web queries. Use for any lookup, research, investigation, or question needing current info. Fast and cost-effective. Only use parallel-deep-research if user explicitly requests 'deep' or 'exhaustive' research.

When to use it

The official description does not include a separate “Use when”. Per the spec, agents activate this skill when the task matches keywords in that description.

How agents load it

Per Agent Skills progressive disclosure: name and description load at startup (~100 tokens); the full SKILL.md body loads when the skill activates; scripts/, references/, and assets/ load only as needed. This file's sections: Web Search; Command; Parsing results; Response format; Setup.

File analysis

File analysis: instruction-only skill (SKILL.md). The agent loads the full body when activated.

Web SearchCommandParsing resultsResponse formatSetup

Compatibility:Requires parallel-cli and internet access. · allowed-tools:Bash(parallel-cli:*)

Source category:skills.sh agent-skill

SKILL.md & Agent activation

Official spec ↗
name
parallel-web-search
description
DEFAULT for all research and web queries. Use for any lookup, research, investigation, or question needing current info. Fast and cost-effective. Only use parallel-deep-research if user explicitly requests 'deep' or 'exhaustive' research.
compatibility
Requires parallel-cli and internet access.
allowed-tools
Bash(parallel-cli:*)Experimental field; support depends on the client and does not grant permissions by itself.
  1. DiscoverThe client exposes names and descriptions to the agent.
  2. ActivateYour request or the task context selects the skill and loads its instructions.
  3. Load resourcesReferenced scripts, documentation and assets are used when needed.

Invocation syntax and available tools depend on your Agent client. Client integration guide ↗

Install this skill

Skills CLI ↗

Choose the target agent and installation scope, keep referenced package files, then verify the skill appears in the client's catalog.

Ask your Agent to install

Copy these instructions to a compatible agent and confirm the target directory matches your client.

Install the agent skill "parallel-web-search" into my project. The full SKILL.md and official description are at https://zicq.com/en/skills/skl-b2880bb8d325f120-Parallel-Web-Search.html
Save it as .cursor/skills/parallel-web-search/SKILL.md or .claude/skills/parallel-web-search/SKILL.md and keep the frontmatter name and description exactly as-is.

Full package on GitHub ↗

Install from the terminal · Skills CLI

Requires Node.js and npx. First inspect the repository's skill list to confirm the name.

npx skills add 'https://github.com/parallel-web/parallel-agent-skills' --list

npx skills add 'https://github.com/parallel-web/parallel-agent-skills' --skill 'parallel-web-search'

The CLI lets you choose the agent interactively. The default scope is the project; use -g for user scope. Confirm package availability with the discovery command, then use npx skills list to inspect installed skills.

Readable layout
--- name: parallel-web-search description: "DEFAULT for all research and web queries. Use for any lookup, research, investigation, or question needing current info. Fast and cost-effective. Only use parallel-deep-research if user explicitly requests 'deep' or 'exhaustive' research." user-invocable: true argument-hint: context: fork agent: parallel:parallel-subagent compatibility: Requires parallel-cli and internet access. allowed-tools: Bash(parallel-cli:*) metadata: author: parallel --- # Web Search Search the web for: $ARGUMENTS ## Command Choose a short, descriptive filename based on the query (e.g., `ai-chip-news`, `react-vs-vue`). Use lowercase with hyphens, no spaces. Substitute it into the command **inline** — `$FILENAME` and `` below are placeholders, not shell variables; do not copy them verbatim. ```bash parallel-cli search "$ARGUMENTS" -q "" -q "" --json --max-results 10 --excerpt-max-chars-total 27000 -o "/tmp/$FILENAME.json" ``` Concrete example for a query about React 19: ```bash parallel-cli search "latest React 19 features and adoption" -q "React 19" -q "concurrent rendering" --json --max-results 10 --excerpt-max-chars-total 27000 -o "/tmp/react-19-features.json" ``` The first argument is the **objective** — a natural language description of what you're looking for. It replaces multiple keyword searches with a single call for broad or complex queries. Add `-q` flags for specific keyword queries to supplement the objective. The `-o` flag saves the full results to a JSON file for follow-up questions. Options if needed: - `--after-date YYYY-MM-DD` for time-sensitive queries - `--include-domains domain1.com,domain2.com` to limit to specific sources - `--exclude-domains domain.com` to filter out noisy sources - `--mode turbo` for simple fact lookups where speed and cost matter most (p50 ~200ms, lowest cost). English and Japanese queries only - `--mode fast` for high-quality search within a ~1s latency budget - `--mode advanced` for harder questions (multi-step, agentic search). Default `basic` is right for almost everything; escalate to `advanced` only when basic results are insufficient, and drop to `turbo` for high-volume simple lookups - `--location us` (ISO 3166-1 alpha-2) for geo-targeted results ## Parsing results Do not set `max_output_tokens` on the command execution — the output is already bounded by `--max-results` and `--excerpt-max-chars-total`. Capping output tokens will truncate the JSON and break parsing. **Prefer reading from the saved `-o` file**, not stdout. Even bounded output regularly exceeds harness stdout limits and gets truncated. Read `/tmp/$FILENAME.json` for the authoritative payload. For each result, extract: - title, url, publish_date - Useful content from excerpts (skip navigation noise like menus, footers, "Skip to content") ## Response format **CRITICAL: Every claim must have an inline citation.** Use markdown links like [Title](URL) pulling only from the JSON output. Never invent or guess URLs. Synthesize a response that: - Leads with the key answer/finding - Includes specific facts, names, numbers, dates - Cites every fact inline as [Source Title](url) — do not leave any claim uncited - Organizes by theme if multiple topics **End with a Sources section** listing every URL referenced: ```text Sources: - [Source Title](https://example.com/article) (Feb 2026) - [Another Source](https://example.com/other) (Jan 2026) ``` This Sources section is mandatory. Do not omit it. After the Sources section, mention the output file path (`/tmp/$FILENAME.json`) so the user knows it's available for follow-up questions. ## Setup If `parallel-cli` is not found, install and authenticate: ```bash /parallel:parallel-cli-setup ``` If `parallel-cli search` returns `403`, tell the user balance is likely required. Offer to run `parallel-cli balance get`, and if needed ask for explicit confirmation before running `parallel-cli balance add `. Then retry the original search command.

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