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deep-research

Execute autonomous multi-step research using Google Gemini Deep Research Agent. Use for: market analysis, competitive landscaping, literature review…

读凭据联网严重 8 · 高危 4sanjay3290/ai-skills

它会碰到什么

扫了多少5 个文本文件，34 KB
它会碰到什么读凭据联网
命中总数19 处
命中统计严重 8 · 高 4 · 中 6 · 低 1
逐条看命中（12 条严重或高危）
  • 严重 README.md:27cred-paths
    cp .env.example .env
  • 严重 README.md:27cred-paths
    cp .env.example .env
  • 严重 README.md:28cred-paths
    # Edit .env and add your GEMINI_API_KEY
  • 严重 README.md:36cred-paths
    4. Copy the key to your `.env` file
  • 严重 README.md:134cred-paths
    ### .env File
  • 严重 README.md:190cred-paths
    | `GEMINI_API_KEY not set` | Missing API key | Set in `.env` or environment |
  • 严重 scripts/research.py:123cred-paths
    "GEMINI_API_KEY not set. Set it in .env or environment variables."
  • 严重 SKILL.md:27cred-paths
    Or create a `.env` file in the skill directory.
  • 高 scripts/research.py:42cred-envread
    self.cache_dir = Path(cache_dir or os.getenv("DEEP_RESEARCH_CACHE_DIR", default_dir))
  • 高 scripts/research.py:120cred-envread
    self.api_key = api_key or os.getenv("GEMINI_API_KEY")
  • 高 scripts/research.py:126cred-envread
    self.timeout = int(os.getenv("DEEP_RESEARCH_TIMEOUT", "600"))
  • 高 scripts/research.py:127cred-envread
    self.poll_interval = int(os.getenv("DEEP_RESEARCH_POLL_INTERVAL", "10"))

这一栏是扫描器报的事实，不是结论。命中多不等于有毒（安全工具、规则库、示例脚本本来就会包含危险写法），命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系，需要你自己看。

技能内容

Gemini Deep Research Skill

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

Requirements

  • Python 3.8+
  • httpx: pip install -r requirements.txt
  • GEMINI_API_KEY environment variable

Setup

  1. Get a Gemini API key from Google AI Studio
  2. Set the environment variable:
   export GEMINI_API_KEY=your-api-key-here

Or create a .env file in the skill directory.

Usage

Start a research task

python3 scripts/research.py --query "Research the history of Kubernetes"

With structured output format

python3 scripts/research.py --query "Compare Python web frameworks" \
  --format "1. Executive Summary\n2. Comparison Table\n3. Recommendations"

Stream progress in real-time

python3 scripts/research.py --query "Analyze EV battery market" --stream

Start without waiting

python3 scripts/research.py --query "Research topic" --no-wait

Check status of running research

python3 scripts/research.py --status <interaction_id>

Wait for completion

python3 scripts/research.py --wait <interaction_id>

Continue from previous research

python3 scripts/research.py --query "Elaborate on point 2" --continue <interaction_id>

List recent research

python3 scripts/research.py --list

Output Formats

  • Default: Human-readable markdown report
  • JSON (--json): Structured data for programmatic use
  • Raw (--raw): Unprocessed API response

Cost & Time

| Metric | Value |

|--------|-------|

| Time | 2-10 minutes per task |

| Cost | $2-5 per task (varies by complexity) |

| Token usage | ~250k-900k input, ~60k-80k output |

Best Use Cases

  • Market analysis and competitive landscaping
  • Technical literature reviews
  • Due diligence research
  • Historical research and timelines
  • Comparative analysis (frameworks, products, technologies)

Workflow

  1. User requests research → Run --query "..."
  2. Inform user of estimated time (2-10 minutes)
  3. Monitor with --stream or poll with --status
  4. Return formatted results
  5. Use --continue for follow-up questions

Exit Codes

  • 0: Success
  • 1: Error (API error, config issue, timeout)
  • 130: Cancelled by user (Ctrl+C)

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去原始仓库

它属于哪个仓库

仓库sanjay3290/ai-skills
星标★ 424
本站分层T2
该仓技能数24
原文件路径skills/deep-research/SKILL.md

同一个仓库里的其他技能

看这个仓库的全部 24 个技能