plugin.json

{
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "name": "lucy-sec-filings-search",
  "version": "1.0.0",
  "description": "Search U.S. SEC EDGAR filings and ground AI answers in real disclosure passages.",
  "author": {
    "name": "Ezar Inc.",
    "email": "help@lucydata.ai",
    "url": "https://lucydata.ai"
  },
  "homepage": "https://lucydata.ai",
  "extensions": {
    "com.openai": {
      "interface": {
        "displayName": "Lucy \u2014 SEC Filings Search",
        "shortDescription": "Search U.S. SEC EDGAR filings",
        "longDescription": "Lucy connects your AI assistant to a retrieval pipeline over U.S. SEC EDGAR filings. Ask about a public company's risk factors, financial performance, business segments, executive compensation, or governance \u2014 Lucy returns the most relevant source passages from the actual filings, so the assistant can answer with citations instead of guessing from model memory. One read-only tool, rag_context(question, thread_id), returns relevant filing passages plus a thread_id for multi-turn follow-ups. When nothing relevant exists in the corpus, Lucy says so instead of letting the model guess. The tool never modifies any user or third-party data.",
        "developerName": "Ezar Inc.",
        "category": "Finance",
        "capabilities": [
          "Read"
        ],
        "websiteURL": "https://lucydata.ai",
        "supportURL": "https://lucydata.ai/contact-us",
        "privacyPolicyURL": "https://lucydata.ai/privacy-policy",
        "termsOfServiceURL": "https://lucydata.ai/terms-of-service",
        "defaultPrompt": [
          "What are Apple's main risk factors in its latest 10-K?",
          "Which NVIDIA business segments generate the most revenue, and how fast are they growing?",
          "How do Apple and Microsoft describe AI-related risks in their latest annual reports?"
        ],
        "brandColor": "#0A1833",
        "composerIcon": "./assets/icon.png",
        "composerIconDark": "./assets/icon-dark.png",
        "logo": "./assets/logo.png",
        "logoDark": "./assets/logo-dark.png"
      },
      "review": {
        "test_cases": {
          "positive": [
            {
              "description": "Form-Specific Analysis \u2014 TSMC\u2019s Tariff and Trade Risks. Tests whether Lucy retrieves relevant evidence from a specified company, filing form, and reporting year.",
              "prompt": "In TSMC's 2025 Form 20-F, what tariff and trade-restriction risks does it disclose, and how could they affect its U.S. manufacturing operations?",
              "tools_triggered": "rag_context",
              "expected_behavior": "Lucy retrieves relevant passages from TSMC's 2025 Form 20-F. The assistant explains the disclosed tariff and trade-restriction risks and their potential effects on U.S. manufacturing operations, cites the filing, and distinguishes potential risks from effects that have already occurred."
            },
            {
              "description": "Tracking Developments Across Filings and Retrieving Detailed Data \u2014 NVIDIA. Tests whether Lucy connects initial announcements with subsequent updates and retrieves specific figures, dates, transaction terms, and management changes.",
              "prompt": "Based on NVIDIA's SEC filings throughout 2026, provide a chronological timeline of its major corporate developments, including financial results, acquisitions, strategic partnerships, investments, and significant management changes. Explain what was initially announced, how each development has progressed through subsequent filings, and what remains pending or uncertain as of the latest filing.",
              "tools_triggered": "rag_context",
              "expected_behavior": "Lucy retrieves evidence from NVIDIA's SEC filings filed during 2026 through the latest available filing. The assistant builds a chronological timeline with relevant financial figures, transaction amounts, dates, and terms where disclosed. It connects initial announcements to subsequent updates, distinguishes announced agreements from completed transactions, and identifies pending conditions or uncertainty. Each development is supported by filing references. Missing updates or categories are acknowledged rather than invented."
            },
            {
              "description": "Incorporating Amendments to Previously Filed Reports \u2014 WK Kellogg. Tests whether Lucy finds and uses corrected information from an amendment even when the user does not explicitly request the amended filing.",
              "prompt": "According to WK Kellogg Co's 2024 annual report, how much net cash did it provide from operating activities for the year ended December 28, 2024?",
              "tools_triggered": "rag_context",
              "expected_behavior": "Lucy retrieves WK Kellogg's amended Form 10-K/A (0001628280-25-038568). The assistant reports restated net cash provided by operating activities of $107 million for the year ended December 28, 2024, and explains that the originally reported $100 million was increased by $7 million. It cites the amendment. Reporting $100 million as the final figure without acknowledging the correction fails this test."
            },
            {
              "description": "Small-Cap Company Analysis \u2014 Rigetti\u2019s Revenue, Customer Dependence, and Technology Roadmap. Tests whether Lucy retrieves financial results, government-customer concentration, and technical milestones across annual, quarterly, and current reports.",
              "prompt": "How much revenue does Rigetti Computing make, how dependent is it on government customers, and what is its roadmap for qubit count and gate fidelity?",
              "tools_triggered": "rag_context",
              "expected_behavior": "Lucy retrieves evidence addressing all three parts of the question. Verified evidence includes FY2025 revenue of $7.088 million, compared with $10.790 million in FY2024, and first-half 2026 revenue of $9.538 million. Government entities accounted for 90.2% and 89.4% of revenue in 2025 and 2024, respectively; this includes U.S. and foreign government customers, not only the U.S. government. Technical disclosures include a deployed 108-qubit system with internally tested median two-qubit gate fidelity of 99.1%, and an August 2026 roadmap targeting approximately 1,000 qubits and 99.9% two-qubit gate fidelity over roughly three years. The assistant labels reporting periods, distinguishes achieved performance from future targets, and cites the relevant filings. If later filings update these figures or targets, it uses and cites those updates."
            },
            {
              "description": "Latest Information on Upcoming IPOs \u2014 Anthropic. Tests whether an ordinary investor question leads Lucy to retrieve the company's latest available IPO disclosures without the user specifying a filing form or source.",
              "prompt": "Anthropic's revenue is growing fast, but it's also spending a lot. Can it become profitable, or will it keep needing more money? Would it be an attractive investment after going public, and what are the biggest risks?",
              "tools_triggered": "rag_context",
              "expected_behavior": "Lucy retrieves the latest available evidence on Anthropic's revenue, costs, losses, cash flows, liquidity, spending commitments, and material risks. The assistant uses the disclosed figures to assess the path to profitability and potential financing needs, distinguishing company disclosures from its own analysis. It presents both the investment case and the principal risks, explains where the evidence is insufficient, and does not treat future profitability or investment returns as certain. If offering price or valuation terms are unavailable, it explains that limitation when discussing investment attractiveness. Claims are supported by filing references."
            }
          ],
          "negative": [
            {
              "description": "Out-of-corpus question. The corpus only contains SEC filings, so the tool finds no relevant passages and the assistant relays the not-found message instead of answering from model memory.",
              "prompt": "What's the weather in SF today?"
            },
            {
              "description": "Real-time market data is not in SEC filings. rag_context returns zero passages and a not-found message, and the assistant must not invent a price or answer from memory.",
              "prompt": "What is Apple's stock price today?"
            },
            {
              "description": "Company not in the corpus. Cargill is privately held and files no periodic reports (10-K, 10-Q) with the SEC, so rag_context returns zero passages and a not-found message. The assistant tells the user the company is not available instead of answering from model memory.",
              "prompt": "What did Cargill report in its latest 10-K about revenue and risk factors?"
            }
          ]
        }
      },
      "apps": "./.app.json"
    }
  }
}