{
  "name": "autonomous-web-research-agent",
  "version": "1.0.0",
  "goal": "Autonomously research a given query on the web using multiple search tools and generate a structured report with summary, detailed sections, source tracking, and bias analysis.",
  "inputs": [
    "query (string): the research question or topic to investigate",
    "tools (list, optional): selected web search/tools to use (e.g., Tavily, Google, NewsAPI, DuckDuckGo)",
    "api_keys (dict, optional): credentials for LLM and external search APIs",
    "model_config (dict, optional): LLM provider and parameters"
  ],
  "steps": [
    "1. Accept user query and optional tool selections.",
    "2. Initialize agent framework (e.g., LangGraph) with integrated tools: web search (Tavily, Google, DuckDuckGo), news API, web scraping.",
    "3. Decompose query into sub-questions if needed and iteratively call tools to gather relevant information.",
    "4. Extract and deduplicate content from retrieved sources, tracking source metadata (URL, tool used).",
    "5. Use a large language model to synthesize findings into an executive summary and detailed sections.",
    "6. Analyze potential biases or limitations of gathered sources.",
    "7. Compile a structured report object (ResearchReport) containing query, summary, sections, sources, biases.",
    "8. Optionally present report via a UI (e.g., Streamlit) or return as JSON."
  ],
  "outputs": [
    "ResearchReport (JSON/dict) with fields: query (string), summary (string), sections (list of {heading, content}), sources (list of {url, tool_used, title}), potential_biases (string)",
    "Optional UI rendering of report with source badges and expandable sections"
  ],
  "failure_modes": [
    "Missing or invalid API keys causing tool authentication failures",
    "Rate limits or network errors from search APIs",
    "Insufficient or low-quality search results leading to incomplete report",
    "LLM hallucination or mis-summarization despite source tracking",
    "Parsing errors in HTML/scraped content"
  ],
  "confidence": 0.85,
  "explanation": "The repository implements a generic autonomous web research agent that can be reused for any topical query. The workflow of querying, multi-tool retrieval, synthesis, and structured reporting is not domain-specific and can be extracted as a reusable skill.",
  "source_repo": "https://github.com/DennisDRX/Faraday-Web-Researcher-Agent.git",
  "score": 1.0
}