stock-copilot-pro: Скилл анализа рынка акций

--- name: stock-copilot-pro description: OpenClaw stock analysis skill for US/HK/CN markets. Combines QVeris data sources (THS, Caidazi, Alpha Vantage, Finnhub, X sentiment) for quote, fundamentals, technicals, news radar, morning/evening brief, and actionable investment insights. env: - QVERIS_API_KEY requirements: env_vars: - QVERIS_API_KEY credentials: required: - QVERIS_API_KEY primary: QVERIS_API_KEY scope: read-only endpoint: https://qveris.ai/api/v1 runtime: { language: nodejs, node: ">=18" } install: { mechanism: local-skill-execution, external_installer: false, package_manager_required: false } persistence: { writes_within_skill_dir: [config/watchlist.json, .evolution/tool-evolution.json], writes_outside_skill_dir: false } security: { full_content_file_url: { enabled: true, allowed_hosts: [qveris.ai], protocol: https } } network: outbound_hosts: - qveris.ai metadata: {"openclaw":{"requires":{"env":["QVERIS_API_KEY"]},"primaryEnv":"QVERIS_API_KEY","homepage":"https://qveris.ai"}} auto_invoke: true source: https://qveris.ai examples: - "Analyze AAPL with a comprehensive report" - "Technical analysis for 0700.HK" - "Compare AAPL, MSFT, NVDA" - "Give me fundamentals and sentiment for 600519.SS" --- # 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: 1. Market quote / trading context 2. Fundamental metrics 3. Technical signals (RSI/MACD/MA) 4. News and sentiment 5. 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 1. Resolve user input to symbol + market (supports company-name aliases, e.g. Chinese name -> `600089.SH`). 2. Search tools by capability (quote, fundamentals, indicators, sentiment, X sentiment). 3. 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. 4. Before execution, try evolution parameter templates; if unavailable, use default param builder. 5. Run quality checks: - Missing key fields - Data recency - Cross-source inconsistency 6. 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 7. 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) 0. **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: ```markdown | 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 | ``` 1. **Key view (30 seconds)** - One-line conclusion: buy/hold/avoid + key reason. 2. **Investment thesis** - Bull case: 2 points (growth driver, moat/catalyst) - Bear case: 2 points (valuation/risk/timing) - Final balance: what dominates now. 3. **Valuation and key levels** - PE/PB vs peer or history percentile (cheap/fair/expensive) - Key levels: current price, support, resistance, stop-loss reference 4. **Recommendation (required)** - Different advice by position status: - No position - Light position - Heavy position / underwater - Each suggestion must include concrete trigger/price/condition. 5. **Risk monitor** - Top 2-3 risks + invalidation condition (what proves thesis wrong). 6. **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: ```markdown > 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 1. **Market overview**: risk-on/off + key overnight move + today's tone, plus an index snapshot table from `marketOverview.indices` (index name, price, % change, timestamp) 2. **Holdings check**: holdings that need action first, with per-holding price/% change/grade when available 3. **Radar relevance**: which radar themes impact holdings 4. **Today's plan (required)**: specific watch levels / event / execution plan 5. **Data Sources (required)**: one-line QVeris attribution and channels used in this brief ### Evening Brief 1. **Session recap**: index + sector + portfolio one-line recap, with key index close/% change 2. **Holdings change**: biggest winners/losers and why, with quantized move (%) where available 3. **Thesis check**: whether thesis changed 4. **Tomorrow's plan (required)**: explicit conditions and actions 5. **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.