home / skills / openclaw / skills / parallel-search
This skill enables AI agents to perform up-to-date web searches via a powerful API, returning ranked results with concise, LLM-friendly excerpts.
npx playbooks add skill openclaw/skills --skill parallel-searchReview the files below or copy the command above to add this skill to your agents.
---
name: parallel-search
description: "AI-powered web search via Parallel API. Returns ranked results with LLM-optimized excerpts. Use for up-to-date research, fact-checking, and domain-scoped searching."
homepage: https://parallel.ai
---
# Parallel Search
High-accuracy web search built for AI agents. Returns ranked results with intelligent excerpts optimized for LLM consumption.
## When to Use
Trigger this skill when the user asks for:
- "search the web", "web search", "look up", "find online"
- "current news about...", "latest updates on..."
- "research [topic]", "what's happening with..."
- Fact-checking with citations needed
- Domain-specific searches (e.g., "search GitHub for...", "find on Reddit...")
## Quick Start
```bash
parallel-cli search "your query" --json --max-results 5
```
## CLI Reference
### Basic Usage
```bash
parallel-cli search "<objective>" [options]
```
### Common Flags
| Flag | Description |
|------|-------------|
| `-q, --query "<keyword>"` | Add keyword filter (repeatable, 3-8 recommended) |
| `--max-results N` | Number of results (1-20, default: 10) |
| `--json` | Output as JSON |
| `--after-date YYYY-MM-DD` | Filter for recent content |
| `--include-domains domain.com` | Limit to specific domains (repeatable, max 10) |
| `--exclude-domains domain.com` | Exclude domains (repeatable, max 10) |
| `--excerpt-max-chars-total N` | Limit total excerpt size (default: 8000) |
### Examples
**Basic search:**
```bash
parallel-cli search "When was the United Nations founded?" --json --max-results 5
```
**With keyword filters:**
```bash
parallel-cli search "Latest developments in quantum computing" \
-q "quantum" -q "computing" -q "2026" \
--json --max-results 10
```
**Domain-scoped search:**
```bash
parallel-cli search "React hooks best practices" \
--include-domains react.dev --include-domains github.com \
--json --max-results 5
```
**Recent news only:**
```bash
parallel-cli search "AI regulation news" \
--after-date 2026-01-01 \
--json --max-results 10
```
## Best-Practice Prompting
### Objective
Write 1-3 sentences describing:
- The real task context (why you need the info)
- Freshness constraints ("prefer 2026+", "latest docs")
- Preferred sources ("official docs", "news sites")
### Keyword Queries
Add 3-8 keyword queries including:
- Specific terms, version numbers, error strings
- Common synonyms
- Date terms if relevant ("2026", "Jan 2026")
## Response Format
Returns structured JSON with:
- `search_id` — unique identifier
- `results[]` — array of results:
- `url` — source URL
- `title` — page title
- `excerpts[]` — relevant text excerpts
- `publish_date` — when available
## Output Handling
When turning results into a user-facing answer:
- Prefer **official/primary sources** when possible
- Quote or paraphrase **only** the relevant extracted text
- Include **URL + publish_date** for transparency
- If results disagree, present both and note the discrepancy
## Running Out of Context?
For long conversations, save results and use `sessions_spawn`:
```bash
parallel-cli search "<query>" --json -o /tmp/search-<topic>.json
```
Then spawn a sub-agent:
```json
{
"tool": "sessions_spawn",
"task": "Read /tmp/search-<topic>.json and synthesize a summary with sources.",
"label": "search-summary"
}
```
## Error Handling
| Exit Code | Meaning |
|-----------|---------|
| 0 | Success |
| 1 | Unexpected error (network, parse) |
| 2 | Invalid arguments |
| 3 | API error (non-2xx) |
## Prerequisites
1. Get an API key at [parallel.ai](https://parallel.ai)
2. Install the CLI:
```bash
curl -fsSL https://parallel.ai/install.sh | bash
export PARALLEL_API_KEY=your-key
```
## References
- [API Docs](https://docs.parallel.ai)
- [Search API Reference](https://docs.parallel.ai/api-reference/search)
This skill provides AI-powered web search using the Parallel API, returning ranked results with LLM-optimized excerpts for fast, reliable synthesis. It is built for up-to-date research, fact-checking, and domain-scoped queries where source citations and publish dates matter. Use it when you need concise, machine-friendly results that are easy to incorporate into agent workflows.
The skill sends a query and optional filters to Parallel's search endpoint and receives structured JSON with ranked results, excerpts, titles, URLs, and publish dates. Excerpts are optimized for LLM consumption to reduce noise and highlight relevant passages. It supports domain inclusion/exclusion, date filters, and keyword boosts so agents can narrow scope and prioritize authoritative sources.
How many results can I request?
You can request 1–20 results; the default is 10 and smaller sets return faster excerpts.
How do I ensure results are recent?
Use the --after-date flag or include date keywords (e.g., "2026") in keyword filters to prioritize fresh content.