by QVeris
Use this skill when the user wants an agent that can research listed companies with live market data and source-backed context instead of relying on static model memory.
A finance workflow for quotes, fundamentals, filings, earnings context, and analyst-style summaries.
Investor research agents, portfolio monitors, and analyst workflows
A source-backed research brief with evidence, risk notes, QVeris calls used, and estimated credits.
Each article or tutorial is treated as a reusable workflow source: content, copied prompt, QVeris API recipe, and expected output.
Product article
Turn structured financial data into callable agent capabilities.
Analyze AAPL using live market data, recent fundamentals, valuation context, and the latest relevant filings or news. Separate facts from interpretation and cite which QVeris capabilities were called.
Analyst memo · Markdown memo
Tutorial
A practical workflow for always-on market monitoring.
Compare NVDA and AMD across price action, revenue growth, margins, valuation, recent news, and key risks. Use QVeris to discover and call the required finance capabilities.
Signal table · Table
Product article
Add market data coverage for agent research tasks.
Create a daily watchlist brief for AAPL, NVDA, MSFT, and TSLA. For each ticker, identify what changed, the strongest data point, and what to watch next.
Audit appendix · JSON / appendix
Starter prompts that turn the skill into executable agent work.
Generate a source-backed research snapshot for one ticker.
Analyze AAPL using live market data, recent fundamentals, valuation context, and the latest relevant filings or news. Separate facts from interpretation and cite which QVeris capabilities were called.
Compare market data and company fundamentals in one agent workflow.
Compare NVDA and AMD across price action, revenue growth, margins, valuation, recent news, and key risks. Use QVeris to discover and call the required finance capabilities.
Turn a watchlist into a repeatable daily report.
Create a daily watchlist brief for AAPL, NVDA, MSFT, and TSLA. For each ticker, identify what changed, the strongest data point, and what to watch next.
The formats an agent should return after the workflow runs, with enough structure for reuse and auditing.
A concise research memo with conclusion, evidence, dissent, and caveats.
A scan-friendly table for tickers, sources, events, or watchlist items.
A provenance record of capabilities, sources, windows, and estimated cost.
The concrete Discover, Inspect, and Call sequence this skill expects the agent to run.
POST /searchSearch for quote, filings, financial statement, market data, or analyst data capabilities.
Sample query: real-time stock quote and financial statements API
POST /tools/by-idsConfirm ticker parameters, coverage, latency, success rate, and billing rule before the agent calls a provider.
POST /tools/executeCall selected finance capabilities and compose results into an analyst-style memo.
A planning estimate before execution. Discover and Inspect are free; successful Call execution follows the selected provider billing rule.
A typical stock memo calls several market, fundamentals, filings, or news capabilities after free discovery and inspection.
The range depends on provider billing rules and how many tickers, filings, or news sources the agent calls.
Install the skill in the target agent environment. Agents must ask before running commands or changing local configuration.
This is the source of record for QVeris skills. Inspect or fork the skill folder before installing it in an agent environment.
QVerisAI/open-qveris-skills/stock-copilot-progit clone https://github.com/QVerisAI/open-qveris-skills.git && cd open-qveris-skills/stock-copilot-proopenclaw skills install stock-copilot-proThe visible chain the agent should expose after the user copies a prompt.
The agent turns a user request into capability-oriented search intent.
QVeris returns ranked capabilities with quality, latency, and pricing signals.
The agent checks parameters, examples, and provider signals before calling.
The selected capability is executed and the agent turns results into the final workflow output.
Read manifest and agent.md first. Explain the install command, API actions, and possible credit usage. Wait for explicit approval before making local changes.