parallel-cli skill
Agent-native web search, deep research, and enrichment.
Is the parallel-cli skill safe?
Read the findings before you install it. We read 1 file in the folder on 2026-11-04.
- high
SKILL.md:67Downloads a script and runs it in one step, so what runs is whatever that server sends that day. Common for installers, and still worth a look at the address.
curl -fsSL https://parallel.ai/install.sh | bash
Install the parallel-cli skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/NousResearch/hermes-agent.git /tmp/hermes-agent mkdir -p ~/.claude/skills cp -r /tmp/hermes-agent/optional-skills/research/parallel-cli ~/.claude/skills/parallel-cli
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
Parallel CLI
Use parallel-cli when the user explicitly wants Parallel, or when a terminal-native workflow would benefit from Parallel's vendor-specific stack for web search, extraction, deep research, enrichment, entity discovery, or monitoring.
This is an optional third-party workflow, not a Hermes core capability.
Important expectations:
- Parallel is a paid service with a free tier, not a fully free local tool.
- It overlaps with Hermes native websearch / webextract, so do not prefer it by default for ordinary lookups.
- Prefer this skill when the user mentions Parallel specifically or needs capabilities like Parallel's enrichment, FindAll, or monitor workflows.
parallel-cli is designed for agents:
- JSON output via --json
- Non-interactive command execution
- Async long-running jobs with --no-wait, status, and poll
- Context chaining with --previous-interaction-id
- Search, extract, research, enrichment, entity discovery, and monitoring in one CLI
When to use it
Prefer this skill when:
- The user explicitly mentions Parallel or parallel-cli
- The task needs richer workflows than a simple one-shot search/extract pass
- You need async deep research jobs that can be launched and polled later
- You need structured enrichment, FindAll entity discovery, or monitoring
Prefer Hermes native websearch / webextract for quick one-off lookups when Parallel is not specifically requested.
Installation
Try the least invasive install path available for the environment.
Homebrew
brew install parallel-web/tap/parallel-clinpm
npm install -g parallel-web-cliPython package
pip install "parallel-web-tools[cli]"Standalone installer
curl -fsSL https://parallel.ai/install.sh | bashIf you want an isolated Python install, pipx can also work:
pipx install "parallel-web-tools[cli]"
pipx ensurepathAuthentication
Interactive login:
parallel-cli loginHeadless / SSH / CI:
parallel-cli login --deviceAPI key environment variable:
export PARALLEL_API_KEY="***"Verify current auth status:
parallel-cli authIf auth requires browser interaction, run with pty=true.
Core rule set
- Always prefer --json when you need machine-readable output.
- Prefer explicit arguments and non-interactive flows.
- For long-running jobs, use --no-wait and then status / poll.
- Cite only URLs returned by the CLI output.
- Save large JSON outputs to a temp file when follow-up questions are likely.
- Use background processes only for genuinely long-running workflows; otherwise run in foreground.
- Prefer Hermes native tools unless the user wants Parallel specifically or needs Parallel-only workflows.
Quick reference
parallel-cli
├── auth
├── login
├── logout
├── search
├── extract / fetch
├── research run|status|poll|processors
├── enrich run|status|poll|plan|suggest|deploy
├── findall run|ingest|status|poll|result|enrich|extend|schema|cancel
└── monitor create|list|get|update|delete|events|event-group|simulateCommon flags and patterns
Commonly useful flags:
- --json for structured output
- --no-wait for async jobs
- --previous-interaction-id for follow-up tasks that reuse earlier context
- --max-results for search result count
- --mode one-shot|agentic for search behavior
- --include-domains domain1.com,domain2.com
- --exclude-domains domain1.com,domain2.com
- --after-date YYYY-MM-DD
Read from stdin when convenient:
echo "What is the latest funding for Anthropic?" | parallel-cli search - --json
echo "Research question" | parallel-cli research run - --jsonSearch
Use for current web lookups with structured results.
parallel-cli search "What is Anthropic's latest AI model?" --json
parallel-cli search "SEC filings for Apple" --include-domains sec.gov --json
parallel-cli search "bitcoin price" --after-date 2026-01-01 --max-results 10 --json
parallel-cli search "latest browser benchmarks" --mode one-shot --json
parallel-cli search "AI coding agent enterprise reviews" --mode agentic --jsonUseful constraints:
- --include-domains to narrow trusted sources
- --exclude-domains to strip noisy domains
- --after-date for recency filtering
- --max-results when you need broader coverage
If you expect follow-up questions, save output:
parallel-cli search "latest React 19 changes" --json -o ~/.hermes/cache/scratch/react-19-search.jsonWhen summarizing results:
- lead with the answer
- include dates, names, and concrete facts
- cite only returned sources
- avoid inventing URLs or source titles
Extraction
Use to pull clean content or markdown from a URL.
parallel-cli extract https://example.com --json
parallel-cli extract https://company.com --objective "Find pricing info" --json
parallel-cli extract https://example.com --full-content --json
parallel-cli fetch https://example.com --jsonUse --objective when the page is broad and you only need one slice of information.
Deep research
Use for deeper multi-step research tasks that may take time.
Common processor tiers:
- lite / base for faster, cheaper passes
- core / pro for more thorough synthesis
- ultra for the heaviest research jobs
Synchronous
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