Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
Stock Copilot Pro
OpenClaw stock analysis skill for US/HK/CN markets. Combines QVeris data sources (THS, Caidazi, Alpha Vantage, Finnhub, X sentiment) for quote, fundamentals,...
skill openclawclawhub Free
OpenClaw stock analysis skill for US/HK/CN markets. Combines QVeris data sources (THS, Caidazi, Alpha Vantage, Finnhub, X sentiment) for quote, fundamentals,...
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, config/openclaw-cron.example.json, config/watchlist.example.json, config/watchlist.json, references/metrics-and-signals.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.3.0
Provenance
- Publisher
- buxibuxi
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Stock Copilot Pro
Global Multi-Source Stock Analysis with QVeris.
SEO Keywords
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
Supported Capabilities
Single-stock analysis (analyze): valuation, quality, technicals, sentiment, risk/timing Multi-stock comparison (compare): cross-symbol ranking and portfolio-level view Watchlist/holdings management (watch): list/add/remove for holdings and watchlist Morning/Evening brief (brief): holdings-focused daily actionable briefing Industry hot-topic radar (radar): multi-source topic aggregation for investable themes Multi-format output: markdown, json, chat OpenClaw LLM-ready flow: structured data in code + guided narrative in SKILL.md
Data Sources
Core MCP/API gateway: qveris.ai (QVERIS_API_KEY) CN/HK quote and fundamentals: ths_ifind.real_time_quotation ths_ifind.financial_statements ths_ifind.company_basics ths_ifind.history_quotation CN/HK news and research: caidazi.news.query caidazi.report.query caidazi.search.hybrid.list caidazi.search.hybrid_v2.query Global news sentiment: alpha_news_sentiment finnhub.news X/Twitter sentiment and hot topics: qveris_social.x_domain_hot_topics qveris_social.x_domain_hot_events qveris_social.x_domain_new_posts x_developer.2.tweets.search.recent
What This Skill Does
Stock Copilot Pro performs end-to-end stock analysis with five data domains: Market quote / trading context Fundamental metrics Technical signals (RSI/MACD/MA) News and sentiment X sentiment It then generates a data-rich analyst report with: value-investing scorecard event-timing anti-chasing classification safety-margin estimate thesis-driven investment framework (drivers/risks/scenarios/KPIs) multi-style playbooks (value/balanced/growth/trading) event radar with candidate ideas from news and X scenario-based recommendations standard readable output (default) + optional full evidence trace (--evidence)
Key Advantages
Deterministic tool routing via references/tool-chains.json Evolution v2 parameter-template memory to reduce recurring parameter errors Strong fallback strategy across providers and markets US/HK/CN market-aware symbol handling Structured outputs for both analyst reading and machine ingestion Safety-first handling of secrets and runtime state
Core Workflow
Resolve 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. For CN/HK sentiment, prioritize caidazi channels (report/news/wechat). For CN/HK fundamentals, prioritize THS financial statements (income/balance sheet/cash flow), then fallback to company basics. Before execution, try evolution parameter templates; if unavailable, use default param builder. Run quality checks: Missing key fields Data recency Cross-source inconsistency Produce analyst report with: composite score safety margin event-driven vs pullback-risk timing classification structured thesis (driver/risk/scenario/KPI) event radar (timeline/theme) and candidate ideas style-specific execution playbooks market scenario suggestions optional parsed/raw evidence sections when --evidence is enabled Preference routing (public audience default): If no preference flags are provided, script returns a questionnaire first. You can skip this with --skip-questionnaire.
Command Surface
Primary script: scripts/stock_copilot_pro.mjs Analyze one symbol: node scripts/stock_copilot_pro.mjs analyze --symbol AAPL --market US --mode comprehensive node scripts/stock_copilot_pro.mjs analyze --symbol "<company-name>" --mode comprehensive Compare multiple symbols: node scripts/stock_copilot_pro.mjs compare --symbols AAPL,MSFT --market US --mode comprehensive Manage watchlist: node scripts/stock_copilot_pro.mjs watch --action list node scripts/stock_copilot_pro.mjs watch --action add --bucket holdings --symbol AAPL --market US node scripts/stock_copilot_pro.mjs watch --action remove --bucket watchlist --symbol 0700.HK --market HK Generate brief: node scripts/stock_copilot_pro.mjs brief --type morning --format chat node scripts/stock_copilot_pro.mjs brief --type evening --format markdown Run industry radar: node scripts/stock_copilot_pro.mjs radar --market GLOBAL --limit 10
OpenClaw scheduled tasks (morning/evening brief and radar)
To 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. Reference: the 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). Example (morning brief): 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>. Incorrect: using the legacy example format (e.g. schedule as string, command, delivery.channels array) or pasting the example into jobs.json will cause Gateway parse failure or crash.
CN/HK Coverage Details
Company-name input is supported and auto-resolved to market + symbol for common names. Sentiment path prioritizes caidazi (research reports, news, wechat/public-account channels). Fundamentals path prioritizes THS financial statements endpoints, and always calls THS company basics for profile backfill: revenue netProfit totalAssets totalLiabilities operatingCashflow industry mainBusiness tags
Output Modes
markdown (default): human-readable report json: machine-readable merged payload chat: segmented chat-friendly output for messaging apps summary-first: compact output style via --summary-only
Preference & Event Options
Preference 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
Dynamic Evolution
Runtime learning state is stored in .evolution/tool-evolution.json. One successful execution can update tool parameter templates. Evolution stores param_templates and sample_successful_params for reuse. Evolution does not decide tool priority; tool priority is controlled by tool-chains.json. Use --no-evolution to disable loading/saving runtime learning state.
Safety and Disclosure
Uses only QVERIS_API_KEY. Calls only QVeris APIs over HTTPS. full_content_file_url fetching is kept enabled for data completeness, but only HTTPS URLs under qveris.ai are allowed. Does not store API keys in logs, reports, or evolution state. Runtime persistence is limited to .evolution/tool-evolution.json (metadata + parameter templates only). Watchlist state is stored at config/watchlist.json (bootstrap from config/watchlist.example.json). OpenClaw scheduled tasks: see 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). External source URLs remain hidden by default; only shown when --include-source-urls is explicitly enabled. No package installation or arbitrary command execution is performed by this skill script. Research-only output. Not investment advice.
Single Stock Analysis Guide
When analyzing analyze output, act as a senior buy-side analyst and deliver a professional but not overlong report.
Required Output (7 Sections)
Data Snapshot (required) Start with a compact metrics table built from data fields. Include at least: price/change, marketCap, PE/PB, profitMargin, revenue, netProfit, RSI, 52W range. Example format: | 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) One-line conclusion: buy/hold/avoid + key reason. Investment thesis Bull case: 2 points (growth driver, moat/catalyst) Bear case: 2 points (valuation/risk/timing) Final balance: what dominates now. Valuation and key levels PE/PB vs peer or history percentile (cheap/fair/expensive) Key levels: current price, support, resistance, stop-loss reference Recommendation (required) Different advice by position status: No position Light position Heavy position / underwater Each suggestion must include concrete trigger/price/condition. Risk monitor Top 2-3 risks + invalidation condition (what proves thesis wrong). Data Sources (required) End with a source disclosure line showing QVeris attribution and data channels actually used. Include generation timestamp and list of source/tool names from payload metadata such as dataSources, meta.sourceStats, or data.*.selectedTool. Example format: > 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
Quality Bar
Avoid data dumping; each key number must include interpretation. Every numeric claim must be grounded in actual payload values; do not fabricate numbers. Keep concise but complete (target 250-500 characters for narrative). Must include actionable guidance and time window. Ticker and technical terms in English.
Daily Brief Analysis Guide
When analyzing brief output, generate an actionable morning/evening briefing for OpenClaw conversation.
Morning Brief
Market overview: risk-on/off + key overnight move + today's tone, plus an index snapshot table from marketOverview.indices (index name, price, % change, timestamp) Holdings check: holdings that need action first, with per-holding price/% change/grade when available Radar relevance: which radar themes impact holdings Today's plan (required): specific watch levels / event / execution plan Data Sources (required): one-line QVeris attribution and channels used in this brief
Evening Brief
Session recap: index + sector + portfolio one-line recap, with key index close/% change Holdings change: biggest winners/losers and why, with quantized move (%) where available Thesis check: whether thesis changed Tomorrow's plan (required): explicit conditions and actions Data Sources (required): one-line QVeris attribution and channels used in this brief
Quality Bar
Prioritize user holdings, not generic market commentary. Quantify changes when possible (%, levels, counts). Keep concise and decision-oriented. Include a short source disclosure line at the end to improve traceability and credibility.
Hot Topic Analysis Guide
When analyzing radar output, cluster signals into investable themes and provide concise actionable conclusions.
Required Output (per theme)
Theme: clear, investable label Driver: what changed and why now Impact: beneficiaries/losers + magnitude + duration Recommendation (required): concrete trigger or level Risk note: key invalidation or monitoring signal Source tag (required): include source label for each theme (for example: caidazi_report, alpha_news_sentiment, x_hot_topics)
Execution Rules
Cluster into 3-5 themes max. Cross-verify sources; lower confidence for social-only signals. Distinguish short-term trade vs mid-term allocation. Keep each theme concise (<200 characters preferred). End with a QVeris source disclosure line listing channels that contributed to this radar run.
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs3 Config
- SKILL.md
- README.md
- references/metrics-and-signals.md
- config/openclaw-cron.example.json
- config/watchlist.example.json
- config/watchlist.json