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parallel-ai-search

Use Parallel's parallel-cli to do live web search, URL extraction (clean markdown), deep research reports, bulk data enrichment (CSV/JSON), FindAll entity discovery, and web monitoring. Use when the user asks to look something up online, needs current sources/citations, provides URLs to read or summarise, requests deep/exhaustive research, wants to enrich a dataset with web-sourced fields, wants a list of entities (companies/people/places), or wants to monitor the web for changes over time.

作者: admin | 来源: ClawHub
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ClawHub
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V 1.0.3
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parallel-ai-search

# Parallel AI Search (CLI Master) This is a **single “master” skill** that replaces the earlier Node-script-based version of `parallel-ai-search`. It routes to the right `parallel-cli` capability for the task: - **Search**: quick web lookup with citations (`parallel-cli search`) - **Extract**: turn URLs (including PDFs and JS-heavy pages) into clean, LLM-ready text (`parallel-cli extract`) - **Deep research**: multi-source reports with processor tiers (`parallel-cli research ...`) - **Enrich**: add web-sourced columns to CSV/JSON (`parallel-cli enrich ...`) - **FindAll**: discover entities from the web with optional enrichments (`parallel-cli findall ...`) - **Monitor**: track web changes on a cadence, optionally via webhook (`parallel-cli monitor ...`) ## Routing rules (pick ONE) Choose the smallest / cheapest action that solves the user’s request: 1. **Extract** — if the user gives one or more URLs *or* says “read/summarise this page”, “extract”, “quote”, “pull the content”, “what does this page say”. 2. **Deep research** — ONLY if the user explicitly asks for *deep*, *exhaustive*, *comprehensive*, *thorough investigation*, or a multi-source “report”. 3. **Enrich** — if the user provides a list/table (CSV/JSON/inline objects) and wants new columns like CEO, revenue, funding, contact info, etc. 4. **FindAll** — if the user wants you to **discover many entities** (companies/people/venues/etc.) that match criteria. 5. **Monitor** — if the user wants **ongoing tracking** (“alert me”, “track changes”, “monitor this weekly”) rather than a one-off answer. 6. **Search** — default for everything else that needs current web info or citations. Optional manual prefixes if the user invoked this skill directly: - `search: ...` - `extract: ...` - `research: ...` - `enrich: ...` - `findall: ...` - `monitor: ...` If a prefix is present, honour it. ## Setup and authentication (only when needed) Before running any Parallel command, ensure auth works: ```bash parallel-cli auth ``` If `parallel-cli` is missing, install it: ```bash curl -fsSL https://parallel.ai/install.sh | bash ``` If you cannot use the install script, use pipx: ```bash pipx install "parallel-web-tools[cli]" pipx ensurepath ``` Then authenticate (choose one): ```bash # Interactive OAuth (opens browser) parallel-cli login # Headless / SSH / CI parallel-cli login --device # Or environment variable export PARALLEL_API_KEY="your_api_key" ``` ## Output & citation rules - **Always cite web-sourced facts** with inline markdown links: `[Source Title](https://...)`. - **End with a Sources list** whenever you used Search/Extract/Research output. - Prefer **official/primary** sources when available. - For long outputs, save to files in `/tmp/` and summarise in-chat. ## Search (default web lookup) Use Search for fast, cost-effective answers with citations. ### Command template ```bash parallel-cli search "$OBJECTIVE" --mode agentic --max-results 10 --json ``` Add any of these only when relevant: - `--after-date YYYY-MM-DD` (freshness constraint) - `--include-domains a.com b.org` (restrict sources) - `--exclude-domains spam.com` (block sources) - one or more `-q "keyword query"` flags (extra keyword probes) - `-o "/tmp/$SLUG.search.json"` (save full JSON to a file) ### Parse + respond From the JSON results, extract **title**, **url**, and any **publish_date** / **excerpt** fields. Answer the user’s question, and cite each claim inline. ## Extract (read one or more URLs) Use Extract when you need the actual contents of specific URLs (webpages, PDFs, JS-heavy sites). ### Command template ```bash parallel-cli extract "$URL" --json ``` Add when relevant: - `--objective "Focus area"` (e.g., pricing, API usage, constraints) - `--full-content` (only if the user needs the whole page) - `--no-excerpts` (if you only want full content) - `-o "/tmp/$SLUG.extract.json"` (save full JSON to a file) ### Respond - If the user asked for a **summary**, summarise with citations to the extracted URL. - If the user asked for the **verbatim text**, provide the extracted markdown *only if it is reasonably sized*; otherwise provide the key sections + offer to read more from the saved output. ## Deep research (only when explicitly requested) Deep research is slower and may cost more than Search. Use it only when the user explicitly wants depth. ### Step 1 — start (always async) ```bash parallel-cli research run "$QUESTION" --processor pro-fast --no-wait --json ``` Parse `run_id` (and any monitoring URL) from JSON and tell the user the run started. ### Step 2 — poll (bounded timeout) Choose a short slug filename (lowercase-hyphen), then: ```bash parallel-cli research poll "$RUN_ID" -o "/tmp/$SLUG" --timeout 540 ``` - Share the **executive summary** printed by the poll command. - Mention the output files: - `/tmp/$SLUG.md` - `/tmp/$SLUG.json` If polling times out, re-run the same poll command — the run continues server-side. ## Enrich (CSV/JSON or inline data) Use Enrich to add web-sourced columns to structured data. ### Step 1 — (optional) suggest columns ```bash parallel-cli enrich suggest "$INTENT" --json ``` Use this when the user knows the goal but not the exact output schema. ### Step 2 — run (always async for large jobs) For CSV: ```bash parallel-cli enrich run --source-type csv --source "input.csv" --target "/tmp/enriched.csv" --source-columns '[{"name":"company","description":"Company name"}]' --intent "$INTENT" --no-wait --json ``` For inline JSON rows: ```bash parallel-cli enrich run --data '[{"company":"Google"},{"company":"Apple"}]' --target "/tmp/enriched.csv" --intent "$INTENT" --no-wait --json ``` Parse `taskgroup_id` from JSON. ### Step 3 — poll ```bash parallel-cli enrich poll "$TASKGROUP_ID" --timeout 540 --json ``` After completion: - Tell the user the output file path (the `--target` you chose). - Preview a few rows (using file read tools if available) and report row counts. If poll times out, re-run it — the job continues server-side. ## FindAll (entity discovery) Use FindAll when the user wants you to discover a set of entities (e.g., “AI startups in healthcare”, “roofing companies in Charlotte”, “YC devtools companies”). ### Step 1 — run ```bash parallel-cli findall run "$OBJECTIVE" --generator core --match-limit 25 --no-wait --json ``` Useful options: - `--dry-run --json` to preview schema before spending money - `--exclude '[{"name":"Example Corp","url":"example.com"}]'` to avoid known entities - `--generator preview|base|core|pro` (core default; pro for hardest queries) Parse `run_id` from JSON. ### Step 2 — poll + fetch results ```bash parallel-cli findall poll "$RUN_ID" --json parallel-cli findall result "$RUN_ID" --json ``` Respond with: - total entities found - a clean list/table of the best matches (name + URL + key attributes) - any caveats about ambiguous matches ## Monitor (web change tracking) Use Monitor when the user wants ongoing tracking. Create: ```bash parallel-cli monitor create "$OBJECTIVE" --cadence daily --json ``` Optional: - `--cadence hourly|daily|weekly|every_two_weeks` - `--webhook https://example.com/hook` (deliver events externally) - `--output-schema '<JSON schema string>'` (structured events) Manage: ```bash parallel-cli monitor list --json parallel-cli monitor get "$MONITOR_ID" --json parallel-cli monitor update "$MONITOR_ID" --cadence weekly --json parallel-cli monitor delete "$MONITOR_ID" parallel-cli monitor events "$MONITOR_ID" --json parallel-cli monitor simulate "$MONITOR_ID" --json ``` Respond with the monitor id and how to retrieve events (or confirm webhook delivery). ## Reference material - Copy/paste command templates and patterns: `references/command-templates.md` - Troubleshooting common failures: `references/troubleshooting.md`

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skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

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帮我安装 SkillHub 和 parallel-ai-search-1776368065 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 parallel-ai-search-1776368065 技能

通过命令行安装

skillhub install parallel-ai-search-1776368065

下载 Zip 包

⬇ 下载 parallel-ai-search v1.0.3

文件大小: 6.28 KB | 发布时间: 2026-4-17 14:05

v1.0.3 最新 2026-4-17 14:05
**Major Update: Now uses parallel-cli instead of Node scripts. All previous script-based files removed; new CLI-focused docs and references added.**

- Replaced Node.js script-based workflow with unified `parallel-cli` command-line interface.
- Added new routing and usage instructions for Search, Extract, Deep Research, Enrich, FindAll, and Monitor modes.
- Removed all Node.js scripts and their references.
- Added command templates and troubleshooting guides specific to CLI workflow.
- Documentation now guides users to install and authenticate with `parallel-cli` before use.

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