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Parallel Deep Research

skill-nc9-skills-parallel-deep-research · by nc9

Performs comprehensive deep research using Parallel AI. Use for in-depth analysis, market research, competitive intelligence, or complex multi-faceted questions requiring thorough web exploration.

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Install

$ agentstack add skill-nc9-skills-parallel-deep-research

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Parallel Deep Research

Comprehensive intelligence reports from natural language queries using Parallel AI Task API.

When to Use

  • User needs thorough, multi-source research on a topic
  • User asks complex questions requiring synthesis of multiple sources
  • User needs market research or competitive analysis
  • User wants comprehensive reports with citations
  • Simple web search is insufficient for the depth needed

Requirements

Environment variable must be set:

  • PARALLEL_API_KEY - Parallel AI API key

Command

./scripts/parallel_research research "query" [options]

Options

| Option | Description | |--------|-------------| | -p, --processor | Model: pro-fast (default), pro, ultra-fast, ultra | | -t, --timeout | Max wait in seconds (default: 600) | | -f, --format | Output: json (default) or markdown |

Processors

| Processor | Speed | Quality | Cost | |-----------|-------|---------|------| | pro-fast | 2-5x faster | Good | Lower | | pro | Standard | Better | Medium | | ultra-fast | 2-5x faster | Better | Medium | | ultra | Standard | Best | Higher |

Output Format

Default JSON for LLM parsing:

{
  "query": "What are the latest developments in fusion energy?",
  "processor": "pro-fast",
  "run_id": "run_abc123",
  "content": {
    "summary": "...",
    "key_developments": [...],
    "companies": [...],
    "timeline": [...]
  },
  "basis": [
    {
      "field": "summary",
      "excerpts": [
        {"url": "https://...", "text": "..."}
      ]
    }
  ]
}

Examples

Basic research:

./scripts/parallel_research research "What are the key players in the AI chip market and their competitive positions?"

Higher quality (slower):

./scripts/parallel_research research "Comprehensive analysis of renewable energy trends 2024" -p ultra

Human-readable output:

./scripts/parallel_research research "Electric vehicle battery technology advances" -f markdown

Extended timeout for complex research:

./scripts/parallel_research research "Deep competitive analysis of cloud providers" -t 1800

Notes

  • Research can take 1-45 minutes depending on complexity
  • The pro model and ultra models are expensive and can take 10-45 minutes to complete
  • Query must be under 15,000 characters
  • Status updates print to stderr, results to stdout
  • basis field contains citations mapping content to sources

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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