Global Multi-Source Stock Analysis with QVeris.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstock-copilot-proExecute the skills CLI command in your project's root directory to begin installation:
Fetches stock-copilot-pro from qverisai/open-qveris-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate stock-copilot-pro. Access via /stock-copilot-pro in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
11
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
11
stars
Global Multi-Source Stock Analysis with QVeris.
OpenClaw, stock analysis skill, AI stock copilot, China A-shares, Hong Kong stocks, US stocks, quantitative analysis, fundamental analysis, technical analysis, sentiment analysis, industry radar, morning evening brief, watchlist, portfolio monitoring, QVeris API, THS iFinD, Caidazi, Alpha Vantage, Finnhub, X sentiment, investment research assistant
analyze): valuation, quality, technicals, sentiment, risk/timingcompare): cross-symbol ranking and portfolio-level viewwatch): list/add/remove for holdings and watchlistbrief): holdings-focused daily actionable briefingradar): multi-source topic aggregation for investable themesmarkdown, json, chatSKILL.mdqveris.ai (QVERIS_API_KEY)ths_ifind.real_time_quotationths_ifind.financial_statementsths_ifind.company_basicsths_ifind.history_quotationcaidazi.news.querycaidazi.report.querycaidazi.search.hybrid.listcaidazi.search.hybrid_v2.queryalpha_news_sentimentfinnhub.newsqveris_social.x_domain_hot_topicsqveris_social.x_domain_hot_eventsqveris_social.x_domain_new_postsx_developer.2.tweets.search.recentStock Copilot Pro performs end-to-end stock analysis with five data domains:
It then generates a data-rich analyst report with:
--evidence)references/tool-chains.jsonResolve user input to symbol + market (supports company-name aliases, e.g. Chinese name -> 600089.SH).
Search tools by capability (quote, fundamentals, indicators, sentiment, X sentiment).
Route by hardcoded tool chains first (market-aware), then fallback generic capability search.
caidazi channels (report/news/wechat).Before execution, try evolution parameter templates; if unavailable, use default param builder.
Run quality checks:
Produce analyst report with:
--evidence is enabledPreference routing (public audience default):
--skip-questionnaire.Primary script: scripts/stock_copilot_pro.mjs
node scripts/stock_copilot_pro.mjs analyze --symbol AAPL --market US --mode comprehensivenode scripts/stock_copilot_pro.mjs analyze --symbol "<company-name>" --mode comprehensivenode scripts/stock_copilot_pro.mjs compare --symbols AAPL,MSFT --market US --mode comprehensivenode scripts/stock_copilot_pro.mjs watch --action listnode scripts/stock_copilot_pro.mjs watch --action add --bucket holdings --symbol AAPL --market USnode scripts/stock_copilot_pro.mjs watch --action remove --bucket watchlist --symbol 0700.HK --market HKnode scripts/stock_copilot_pro.mjs brief --type morning --format chatnode scripts/stock_copilot_pro.mjs brief --type evening --format markdownnode scripts/stock_copilot_pro.mjs radar --market GLOBAL --limit 10To set up morning brief, evening brief, or daily radar in OpenClaw, use only the official OpenClaw cron format and create jobs via the CLI or Gateway cron tool. Do not edit ~/.openclaw/cron/jobs.json directly.
jobs array in config/openclaw-cron.example.json; each item is one cron.add payload (fields: name, schedule: { kind, expr, tz }, sessionTarget: "isolated", payload: { kind: "agentTurn", message: "..." }, delivery).openclaw cron add --name "Stock morning brief" --cron "0 9 * * 1-5" --tz Asia/Shanghai --session isolated --message "Use stock-copilot-pro to generate morning brief: run brief --type morning --max-items 8 --format chat" --announce. To deliver to Feishu, add --channel feishu --to <group-or-chat-id>.schedule as string, command, delivery.channels array) or pasting the example into jobs.json will cause Gateway parse failure or crash.caidazi (research reports, news, wechat/public-account channels).revenuenetProfittotalAssetstotalLiabilitiesoperatingCashflowindustrymainBusinesstagsmarkdown (default): human-readable reportjson: machine-readable merged payloadchat: segmented chat-friendly output for messaging appssummary-first: compact output style via --summary-onlyPreference flags:
--horizon short|mid|long--risk low|mid|high--style value|balanced|growth|trading--actionable (include execution-oriented rules)--skip-questionnaire (force analysis without preference Q&A)Event radar flags:
--event-window-days 7|14|30--event-universe global|same_market--event-view timeline|theme.evolution/tool-evolution.json.param_templates and sample_successful_params for reuse.tool-chains.json.--no-evolution to disable loading/saving runtime learning state.QVERIS_API_KEY.full_content_file_url fetching is kept enabled for data completeness, but only HTTPS URLs under qveris.ai are allowed..evolution/tool-evolution.json (metadata + parameter templates only).config/watchlist.json (bootstrap from config/watchlist.example.json).config/openclaw-cron.example.json. Create jobs with the official format (schedule.kind, payload.kind, sessionTarget, etc.) via openclaw cron add or the Gateway cron tool; do not paste or merge the example JSON into ~/.openclaw/cron/jobs.json (schema mismatch can cause Gateway parse failure or crash). Set delivery.channel and delivery.to for your channel (e.g. feishu).--include-source-urls is explicitly enabled.When analyzing analyze output, act as a senior buy-side analyst and deliver a professional but not overlong report.
data fields.| Metric | Value |
|--------|-------|
| Price | $264.58 (+1.54%) |
| Market Cap | $3.89T |
| P/E | 33.45 |
| P/B | 57.97 |
| Profit Margin | 27% |
| Revenue (TTM) | $394B |
| Net Profit | $99.8B |
| RSI | 58.3 |
| 52W Range | $164 - $270 |
Key view (30 seconds)
Investment thesis
Valuation and key levels
Recommendation (required)
Risk monitor
Data Sources (required)
dataSources, meta.sourceStats, or data.*.selectedTool.> Data powered by [QVeris](https://qveris.ai) | Sources: Alpha Vantage (quote/fundamentals), Finnhub (news sentiment), X/Twitter (social sentiment) | Generated at 2026-02-22T13:00:00Z
When analyzing brief output, generate an actionable morning/evening briefing for OpenClaw conversation.
marketOverview.indices (index name, price, % change, timestamp)When analyzing radar output, cluster signals into investable themes and provide concise actionable conclusions.
source label for each theme (for example: caidazi_report, alpha_news_sentiment, x_hot_topics)Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Useful defaults in stock-copilot-pro — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
stock-copilot-pro is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for stock-copilot-pro matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: stock-copilot-pro is focused, and the summary matches what you get after install.
I recommend stock-copilot-pro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
stock-copilot-pro has been reliable in day-to-day use. Documentation quality is above average for community skills.
stock-copilot-pro reduced setup friction for our internal harness; good balance of opinion and flexibility.
stock-copilot-pro has been reliable in day-to-day use. Documentation quality is above average for community skills.
stock-copilot-pro fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: stock-copilot-pro is focused, and the summary matches what you get after install.
showing 1-10 of 50