Awesome-openclaw-skills parallel
High-accuracy web search and research via Parallel.ai API. Optimized for AI agents with rich excerpts and citations.
install
source · Clone the upstream repo
git clone https://github.com/sundial-org/awesome-openclaw-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/parallel" ~/.claude/skills/sundial-org-awesome-openclaw-skills-parallel && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/parallel" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-parallel && rm -rf "$T"
manifest:
skills/parallel/SKILL.mdsource content
Parallel.ai 🔬
High-accuracy web search API built for AI agents. Outperforms Perplexity/Exa on research benchmarks.
Setup
pip install parallel-web
API key is configured. Uses Python SDK.
from parallel import Parallel client = Parallel(api_key="YOUR_KEY") response = client.beta.search( mode="one-shot", max_results=10, objective="your query" )
Quick Usage
# Search with Python SDK python3 {baseDir}/scripts/search.py "Who is the CEO of Anthropic?" --max-results 5 # JSON output python3 {baseDir}/scripts/search.py "latest AI news" --json
Response Format
Returns structured results with:
- unique search identifiersearch_id
- array of results with:results[]
- source URLurl
- page titletitle
- relevant text excerptsexcerpts[]
- when availablepublish_date
- API usage statsusage
When to Use
- Deep research requiring cross-referenced facts
- Company/person research with citations
- Fact-checking with evidence-based outputs
- Complex queries that need multi-hop reasoning
- Higher accuracy than traditional search for research tasks
API Reference
Docs: https://docs.parallel.ai Platform: https://platform.parallel.ai