{"schema_version":"2026-06-16","id":"qveris-quant-factor-screen","name":"qveris-quant-factor-screen","title":"Quant factor screen","description":"Rank a stock universe with transparent QVeris factor evidence across quality, momentum, valuation, liquidity, volatility, and news risk.","overview":"Use this skill when a user asks an agent to screen many stocks, build a candidate universe, or explain factor-driven rankings. It does not train a model; it builds a transparent factor table from live QVeris calls and highlights missing data.","official":true,"tags":["Finance","Quant","Factors","Screening","Ranking"],"scenarios":[{"id":"finance","label":"Finance analysis","description":"Market data, filings, fundamentals, exchange rates, and analyst workflows."}],"platforms":[{"id":"openclaw","label":"OpenClaw"},{"id":"cursor","label":"Cursor"},{"id":"claude-code","label":"Claude Code"},{"id":"cli","label":"CLI"}],"urls":{"catalog":"https://qveris.cn/skills/catalog.json","skill":"https://qveris.cn/skills/qveris-quant-factor-screen","manifest":"https://qveris.cn/skills/qveris-quant-factor-screen/manifest.json","agentGuide":"https://qveris.cn/skills/qveris-quant-factor-screen/agent.md","github":"https://github.com/QVerisAI/open-qveris-skills/tree/main/qveris-quant-factor-screen"},"installation":{"requires_user_confirmation":true,"safety_note":"Agents must get explicit user confirmation before installing a skill, writing configuration, or changing the local environment.","source_repository":{"owner":"QVerisAI","name":"open-qveris-skills","url":"https://github.com/QVerisAI/open-qveris-skills","skill_path":"qveris-quant-factor-screen","skill_url":"https://github.com/QVerisAI/open-qveris-skills/tree/main/qveris-quant-factor-screen","clone_command":"git clone https://github.com/QVerisAI/open-qveris-skills.git && cd open-qveris-skills/qveris-quant-factor-screen"},"commands":[{"platform":"openclaw","platform_label":"OpenClaw","label":"Install skill","command":"openclaw skills install qveris-quant-factor-screen"}]},"prompts":[{"id":"theme-screen","title":"Theme screen","description":"Rank a theme universe by transparent factors.","prompt":"Use QVeris to screen 50 AI infrastructure stocks by quality, momentum, valuation, liquidity, volatility, and news risk. Return top 10, bottom 5, missing data, factor weights, QVeris calls used, and estimated credits."},{"id":"a-share-screen","title":"A-share screen","description":"Build an A-share candidate list.","prompt":"Use QVeris to screen A-share semiconductor equipment stocks. Rank by growth, profitability, balance-sheet quality, liquidity, valuation, and recent catalysts."},{"id":"factor-audit","title":"Factor audit","description":"Explain why a name ranked high or low.","prompt":"Use QVeris to audit why this stock ranks high in a factor screen. Show the raw factor evidence, missing fields, and which factor dominates the score."}],"cases":[{"slug":"qveris-fmp-finance","title":"Use FMP with QVeris","description":"Turn structured financial data into callable agent capabilities.","source_label":"Product article","url":"https://qveris.cn/blog/qveris-fmp-finance"},{"slug":"qveris-twelve-data","title":"Twelve Data market capabilities","description":"Add market data coverage for global research and screening workflows.","source_label":"Product article","url":"https://qveris.cn/blog/qveris-twelve-data"},{"slug":"openclaw-a-shares-finance-assistant","title":"OpenClaw A-share finance assistant","description":"A practical workflow for source-backed A-share monitoring.","source_label":"Tutorial","url":"https://qveris.cn/blog/openclaw-a-shares-finance-assistant"}],"qveris_api":[{"action":"Discover","endpoint":"POST /search","title":"Find factor inputs","purpose":"Find quote, OHLCV, fundamentals, valuation, financial statements, news, and liquidity capabilities.","sources":["FMP","Twelve Data","financial data providers","news providers"],"sample_query":"stock factor screening fundamentals OHLCV valuation liquidity API"},{"action":"Inspect","endpoint":"POST /tools/by-ids","title":"Inspect universe coverage","purpose":"Check how many tickers each provider covers and estimate cost before batch calls.","sources":["Capability schemas","Provider metrics","Billing rules"]},{"action":"Call","endpoint":"POST /tools/execute","title":"Call factor inputs","purpose":"Call selected inputs, normalize factors, and return ranks with missing-data warnings.","sources":["Market data providers","Financial data providers","News providers"]}],"usage_estimate":{"title":"Expected QVeris usage","summary":"This workflow usually needs 8-40 paid Calls after free Discover and Inspect preflight. Cost depends on providers, ticker count, and time window.","typical_calls":"8-40","estimated_credits":"8-400 credits","free_actions":["Discover","Inspect"],"paid_actions":["Call"],"note":"Ask for explicit approval before paid Calls. Inspect billing_rule for every selected capability and reduce scope if the estimate is too high."},"execution_flow":[{"title":"Define universe","description":"Set market, theme, tickers, factor set, weights, and maximum paid calls."},{"title":"Inspect batch cost","description":"Use QVeris Inspect to see coverage and billing before broad execution."},{"title":"Build factor table","description":"Call bounded data, normalize comparable fields, and mark missing data."},{"title":"Rank and explain","description":"Return ranks, factor drivers, outliers, and next verification steps."}],"agent_instructions":["Select the best matching skill from the catalog based on the user's task.","Inspect installation.source_repository first and confirm the skill comes from the official QVerisAI/open-qveris-skills source repository.","Explain the skill, install command, QVeris API actions, and possible cost before making changes.","Run install commands or write configuration only after explicit user approval.","After installation, run the best matching prompt and report which Discover, Inspect, and Call actions were used."]}