Openclaw Data China Stock
Install this when your OpenClaw agent needs unified A-share, ETF, and listed-option market data fetch and optional Parquet cache reads for China markets.
Overview
openclaw-data-china-stock is an agent skill most often used in Validate (also Idea research and Grow analytics) that collects unified A-share, ETF, and option market data for OpenClaw agents.
Install
npx skills add https://github.com/shaoxing-xie/openclaw-data-china-stock --skill openclaw-data-china-stockWhat is this skill?
- `tool_fetch_market_data` as the recommended cross-asset unified entry
- Dedicated fetch aliases for index, ETF, and option data plus `tool_get_option_contracts` by underlying
- Read tools for cached Parquet when local persistence is enabled
- OpenClaw/ClawHub-compatible toolset with packaging ignores for data, logs, and local DB artifacts
- Pairs with a 7-skill suite (macro, technical, scanner, sentinel, fund-flow, backtester MVP, fundamental)
- Documents 7 paired analyst skills in the suite (macro, technical, scanner, sentinel, fund-flow, backtester MVP, fundamen
- Exposes unified fetch plus index/ETF/option alias tools and contract lookup by underlying
Adoption & trust: 1 installs on skills.sh; 39 GitHub stars; 0/3 security scanners passed (skills.sh audits); trending (+100% hot-view momentum).
What problem does it solve?
You are building China-market agent workflows but lack one OpenClaw-native tool entry to fetch and reuse index, equity, ETF, and option data consistently.
Who is it for?
OpenClaw users prototyping or running China equity, ETF, and option research stacks with cached reads enabled.
Skip if: Builders outside OpenClaw who only need a one-off curl to a public API without agent tool integration or local cache governance.
When should I use this skill?
OpenClaw workflows need cross-asset China market fetch or cached Parquet reads before macro, technical, or scanner skills run.
What do I get? / Deliverables
Your agent calls a single fetch surface (plus optional Parquet reads) so downstream paired analyst skills can run on normalized market snapshots.
- Fetched market datasets returned to the agent session
- Optional local Parquet or DB cache reads when persistence is enabled
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Canonical shelf is Validate because solo builders use fresh market pulls to scope trading ideas, ETFs, and option underlyings before committing capital or automation. Scope is where you define what to track and which assets matter; this plugin is the data layer that bounds those decisions with cross-asset fetch tools.
Where it fits
Pull index and sector ETFs to map what liquid China exposure exists before picking a strategy theme.
Fetch option chains for an underlying to see whether hedging instruments exist before automating a signal bot.
Re-read cached Parquet snapshots on a schedule so sentinel or fund-flow skills compare fresh versus prior sessions.
How it compares
Use as the OpenClaw data plugin layer, not as a full fundamental or backtest methodology skill on its own.
Common Questions / FAQ
Who is openclaw-data-china-stock for?
Solo and indie builders using OpenClaw to automate China A-share, ETF, and option data collection inside agent workflows.
When should I use openclaw-data-china-stock?
During Validate when scoping instruments and data needs, during Idea when researching market structure, and during Grow when refreshing analytics pipelines—any time your agent must fetch or read cached China market series.
Is openclaw-data-china-stock safe to install?
Review the Security Audits panel on this Prism page and inspect packaging excludes; the skill touches network APIs and may write local Parquet or DB caches on disk.
SKILL.md
READMESKILL.md - Openclaw Data China Stock
# Ignore local artifacts & caches during ClawHub packaging data/ logs/ # Cursor / local code graph artifacts (must never ship) .code-review-graph/ .code-review-graphignore # Disk caches / artifacts (parquet/jsonl/sql) *.parquet *.jsonl *.db *.sqlite3 # Python environments .venv/ venv/ __pycache__/ *.pyc *.pyo *.pyd .pytest_cache/ # Node node_modules/ # Editor / OS .DS_Store .idea/ .vscode/ # Large local reports / release artifacts tool_test_report*.json *.tgz --- name: openclaw-data-china-stock description: A-share/ETF/Option market data collection plugin for OpenClaw. tags: [data, china, etf, option, openclaw] --- # OpenClaw Data China Stock This plugin provides a ClawHub/OpenClaw compatible toolset for collecting A-share, ETF, and listed option data. ## Key tools - `tool_fetch_market_data`: Cross-asset unified entry (recommended). - `tool_fetch_index_data` / `tool_fetch_etf_data` / `tool_fetch_option_data`: Compatibility/alias unified entries. - `tool_get_option_contracts`: Fetch option contracts by underlying. - `tool_read_market_data` / `tool_read_*`: Read previously cached Parquet data (when enabled). ### Paired skill suite - `skills/china-macro-analyst/SKILL.md` - `skills/technical-analyst/SKILL.md` - `skills/market-scanner/SKILL.md` - `skills/market-sentinel/SKILL.md` - `skills/fund-flow-analyst/SKILL.md` - `skills/strategy-backtester/SKILL.md` (MVP mode) - `skills/fundamental-analyst/SKILL.md` ### China macro analyst tools - **Primary**: `tool_fetch_macro_data` / `tool_fetch_macro_snapshot` - **Compatibility wrappers**: `tool_fetch_macro_*` (21 tools; kept for backward compatibility) - **Skill**: `skills/china-macro-analyst/SKILL.md` (institutional 4-section narrative template; rules in `macro_config.yaml`) ### Multi-factor equity screening (A-share) - **`tool_screen_equity_factors`**: Single entry for oscillation/trend templates (e.g. `reversal_5d`, `fund_flow_3d`, `sector_momentum_5d`) over `hs300|zz500|zz1000|a_share|custom`; returns `quality_score`, `degraded`, `config_hash`, optional `sw_mapping` stats. Implemented in `plugins/analysis/equity_factor_screening.py`; registered in `tool_runner.py` / `config/tools_manifest.yaml` (+ JSON). JSON Schema: `docs/schemas/tool_screen_equity_factors.schema.json`. - **`tool_batch_fetch`**: Batch runner includes `tool_screen_equity_factors` (see `plugins/merged/tool_batch_fetch.py` whitelist). - **申万一级映射**：`config/sw_industry_level1_mapping.json`，由 `scripts/update_sw_industry_level1_mapping.py` 生成（默认乐咕乐股 `sw_index_first_info` + `sw_index_third_cons`；可选 `SW_MAP_USE_EM_SPOT=1` 走东财快照）。消费侧：`plugins/analysis/sw_industry_mapping.py`。 助手侧夜盘落盘、质量门禁与熔断工具（`tool_finalize_screening_nightly` / `tool_set_screening_emergency_pause`）在 **etf-options-ai-assistant** 仓库注册；规程 Skill **`ota_equity_factor_screening_brief`** 仅在该助手仓维护并同步到 Gateway。 ### Fund-flow tools (pick one job, do not duplicate) - **`tool_capital_flow`**: Single-stock **summary** for workflows that need `flow_judgement` / `risk_flags` style outputs (e.g. limit-up strategies). - **`tool_fetch_a_share_fund_flow`**: **Tabular / ranking / history** for onshore A-share money flow (`query_kind` selects market/sector/stock tables, big deals, main-force ranks, sector drill-down). Uses Eastmoney/Tonghuashun-style AkShare routes with an explicit attempt chain; raw data is not investment advice. - **`tool_fetch_northbound_flow`**: **Stock Connect northbound** flows (cross-border), separate from onshore A-share flow tools—keep narratives and citations distinct. - **`tool_fetch_a_share_technical_screener`**: Tonghuashun-style **technical stock screeners** (new highs, consecutive up days, volume patterns, MA breakouts, etc.) via AkShare `stock_rank_*_ths`—**not** the same as locally computed MACD/RSI from OHLC (use `tool_stock_data_fetcher` / `tool_calculate_technical_indicators` for those). ## Safety and independence The plugin is designe