{
  "schema_version": "1.1",
  "id": "archive:https://github.com/ZhuLinsen/daily_stock_analysis",
  "slug": "daily-stock-analysis-1feaxpv",
  "url": "https://feed7.dev/p/daily-stock-analysis-1feaxpv",
  "title": "ZhuLinsen/daily_stock_analysis",
  "why_included": "A configurable agent pipeline combines market data, news, LLM analysis, dashboards, and scheduled delivery. Useful as a reference architecture, but its free data sources carry reliability limits.",
  "summary": "The project analyzes watchlists across **six stock markets plus ETFs**, combining price data, indicators, news, filings, fundamentals, and reports. It offers **15 built-in strategies**, a web dashboard, backtesting, portfolio tracking, and several notification channels.",
  "practical_implication": "Builders can study it as an end-to-end agent application: interchangeable model and search providers, prioritized data fallbacks, Web/Bot/API surfaces, and deployment through **GitHub Actions, Docker, local scheduling, or FastAPI**. The default workflow runs weekdays at **18:00 Beijing time**.",
  "agent_context": "The project analyzes watchlists across **six stock markets plus ETFs**, combining price data, indicators, news, filings, fundamentals, and reports. It offers **15 built-in strategies**, a web dashboard, backtesting, portfolio tracking, and several notification channels.\n\nBuilders can study it as an end-to-end agent application: interchangeable model and search providers, prioritized data fallbacks, Web/Bot/API surfaces, and deployment through **GitHub Actions, Docker, local scheduling, or FastAPI**. The default workflow runs weekdays at **18:00 Beijing time**.\n\nFree market sources may be rate-limited, change interfaces, or suffer network failures; steadier batch operation requires token-based providers. News quality depends on a configured search service, and the generated analysis is explicitly not investment advice.",
  "source": {
    "name": "GitHub",
    "url": "https://github.com/ZhuLinsen/daily_stock_analysis",
    "published_at": null
  },
  "source_class": "tool",
  "content_type": "GitHub Repo",
  "layer": "tools",
  "domains": [
    "data",
    "research"
  ],
  "topics": [
    "tool-use",
    "skills"
  ],
  "verification": {
    "status": "needs_review",
    "label": "Needs Review",
    "method": "unverified",
    "verified_at": null
  },
  "uncertainty": [
    "Free market sources may be rate-limited, change interfaces, or suffer network failures; steadier batch operation requires token-based providers. News quality depends on a configured search service, and the generated analysis is explicitly not investment advice."
  ],
  "connected_context": {
    "meaning": "This turns general agent-workflow ideas into a deployable finance research application with provider interchangeability, data fallbacks, multiple interfaces, scheduling, and backtesting. It also makes operational limits concrete: dependable output depends on external market and search providers, while broad feature coverage does not establish investment validity or source stability.",
    "corpus_size": 419,
    "generated_at": "2026-08-12T10:04:56.899Z",
    "connections": [
      {
        "title": "Model ML completes finance work more efficiently with GPT-5.6 Sol",
        "source_name": "OpenAI",
        "source_url": "https://openai.com/index/model-ml",
        "feed7_url": "https://feed7.dev/p/model-ml-0pf36l4",
        "reason": "Both operationalize finance research beyond chat; Model ML emphasizes editable, traceable workbooks and decks, while this project emphasizes recurring analysis, dashboards, backtesting, and notifications."
      },
      {
        "title": "Panniantong/Agent-Reach",
        "source_name": "GitHub",
        "source_url": "https://github.com/Panniantong/Agent-Reach",
        "feed7_url": "https://feed7.dev/p/agent-reach-0huqxvi",
        "reason": "Agent Reach’s diagnostics for fragile web backends provide relevant context for this project’s prioritized fallbacks and its exposure to rate limits, interface changes, and authentication-dependent sources."
      },
      {
        "title": "Use any Chat SDK adapter with eve",
        "source_name": "Vercel",
        "source_url": "https://vercel.com/changelog/eve-chat-sdk-channel",
        "feed7_url": "https://feed7.dev/p/eve-chat-sdk-channel-03h905c",
        "reason": "eve generalizes multi-channel agent delivery, while this project demonstrates the same implementation consequence in a finance application through Web, Bot, API, and notification surfaces."
      },
      {
        "title": "Full Workshop: Setting Yourself Up for Success —Jason Liu, OpenAI Codex",
        "source_name": "AI Engineer",
        "source_url": "https://www.youtube.com/watch?v=il1c1a2FufU",
        "feed7_url": "https://feed7.dev/p/full-workshop-setting-yourself-up-for-success-jason-liu-openai-codex-13uegzi",
        "reason": "Its scheduled weekday runs exemplify the candidate’s persistent, scheduled-agent pattern, while provider failures and financial stakes strengthen the need for explicit operational boundaries."
      }
    ]
  },
  "lifecycle": "Current",
  "published_at": null,
  "modified_at": null,
  "supersedes": [],
  "expires_at": null,
  "formats": {
    "html": "https://feed7.dev/p/daily-stock-analysis-1feaxpv",
    "json": "https://feed7.dev/p/daily-stock-analysis-1feaxpv.json",
    "markdown": "https://feed7.dev/p/daily-stock-analysis-1feaxpv.md"
  }
}