Tushare Data
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求,转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
Multi-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confiden Generate trading signals using technical…
$ npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team generating-trading-signals --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/crypto-signal-generator .claude/skills/generating-trading-signals && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "generating-trading-signals" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generator into .claude/skills/generating-trading-signals/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "generating-trading-signals", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generatorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team generating-trading-signals --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/crypto-signal-generator .agents/skills/generating-trading-signals && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "generating-trading-signals" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generator into .agents/skills/generating-trading-signals/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "generating-trading-signals", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team generating-trading-signals --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/crypto-signal-generator .cursor/skills/generating-trading-signals && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "generating-trading-signals" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generator into .cursor/skills/generating-trading-signals/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "generating-trading-signals", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aAAaqwq/AGI-Super-Team.git --path skills/crypto-signal-generator--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team generating-trading-signals --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/crypto-signal-generator .gemini/skills/generating-trading-signals && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "generating-trading-signals" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generator into .gemini/skills/generating-trading-signals/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "generating-trading-signals", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aAAaqwq/AGI-Super-Team generating-trading-signalsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/crypto-signal-generator .github/skills/generating-trading-signals && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "generating-trading-signals" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generator into .github/skills/generating-trading-signals/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "generating-trading-signals", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team generating-trading-signals --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/crypto-signal-generator .opencode/skills/generating-trading-signals && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "generating-trading-signals" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/crypto-signal-generator into .opencode/skills/generating-trading-signals/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "generating-trading-signals", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
generating-trading-signalsMulti-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confiden Generate trading signals using technical…
Generating Trading Signals is an agent skill from aAAaqwq/AGI-Super-Team. Multi-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confiden Generate trading signals using technical indicators (RSI, MACD, Bollinger Bands, etc.). Combines multiple indicators into composite signals with confidence scores. Use when analyzing assets for trading opportunities or checking technical indicators. Trigger with phrases like "get trading signals", "check indicators", "analyze for entry", "scan for opportunities"…
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `config/settings.yaml`, `references/errors.md` and `references/examples.md`).
It sits in Business, Finance & HR, covering Trading and backtesting. The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditGrepGlobBash(python:*)From allowed-tools in the SKILL.md frontmatter.
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonpipFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Generating Trading Signals loads about 1.6k tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 149 tokens; SKILL.md has 284 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 284 words, ~1,618 tokens.
.claude/skills/generating-trading-signals/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Multi-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confidence scores and risk management levels.
Indicators Used:
Install required dependencies:
pip install yfinance pandas numpyOptional for visualization:
pip install matplotlibScan multiple assets for trading opportunities:
python {baseDir}/scripts/scanner.py --watchlist crypto_top10 --period 6mOutput shows signal type (STRONG_BUY/BUY/NEUTRAL/SELL/STRONG_SELL) and confidence for each asset.
Get full indicator breakdown for a specific symbol:
python {baseDir}/scripts/scanner.py --symbols BTC-USD --detailShows each indicator's contribution:
Find the best opportunities:
# Only buy signals with 70%+ confidence
python {baseDir}/scripts/scanner.py --filter buy --min-confidence 70 --rank confidence
# Rank by most bullish
python {baseDir}/scripts/scanner.py --rank bullish
# Save results to JSON
python {baseDir}/scripts/scanner.py --output signals.jsonAvailable predefined watchlists:
python {baseDir}/scripts/scanner.py --list-watchlists
python {baseDir}/scripts/scanner.py --watchlist crypto_defiWatchlists: crypto_top10, crypto_defi, crypto_layer2, stocks_tech, etfs_major
================================================================================
SIGNAL SCANNER RESULTS
================================================================================
Symbol Signal Confidence Price Stop Loss
--------------------------------------------------------------------------------
BTC-USD STRONG_BUY 78.5% $67,234.00 $64,890.00
ETH-USD BUY 62.3% $3,456.00 $3,312.00
SOL-USD NEUTRAL 45.0% $142.50 N/A
--------------------------------------------------------------------------------
Summary: 2 Buy | 1 Neutral | 0 Sell
Scanned: 3 assets | [timestamp]
======================================================================================================================================================
BTC-USD - STRONG_BUY
Confidence: 78.5% | Price: $67,234.00
======================================================================
Risk Management:
Stop Loss: $64,890.00
Take Profit: $71,922.00
Risk/Reward: 1:2.0
Signal Components:
----------------------------------------------------------------------
RSI | STRONG_BUY | Oversold at 28.5 (< 30)
MACD | BUY | MACD above signal, positive momentum
Bollinger Bands | BUY | Price near lower band (%B = 0.15)
Trend | BUY | Uptrend: price above key MAs
Volume | STRONG_BUY | High volume (2.3x) on up move
Stochastic | STRONG_BUY | Oversold (%K=18.2, %D=21.5)
ADX | BUY | Strong uptrend (ADX=32.1)
----------------------------------------------------------------------| Signal | Score | Meaning |
|---|---|---|
| STRONG_BUY | +2 | Multiple strong buy signals aligned |
| BUY | +1 | Moderate buy signals |
| NEUTRAL | 0 | No clear direction |
| SELL | -1 | Moderate sell signals |
| STRONG_SELL | -2 | Multiple strong sell signals aligned |
| Confidence | Interpretation |
|---|---|
| 70-100% | High conviction, strong signal |
| 50-70% | Moderate conviction |
| 30-50% | Weak signal, mixed indicators |
| 0-30% | No clear direction, avoid trading |
Edit {baseDir}/config/settings.yaml:
indicators:
rsi:
period: 14
overbought: 70
oversold: 30
signals:
weights:
rsi: 1.0
macd: 1.0
bollinger: 1.0
trend: 1.0
volume: 0.5See {baseDir}/references/errors.md for common issues:
See {baseDir}/references/examples.md for detailed examples:
Test signals historically:
# Generate signal
python {baseDir}/scripts/scanner.py --symbols BTC-USD --detail
# Backtest the strategy that generated the signal
python {baseDir}/../trading-strategy-backtester/skills/backtesting-trading-strategies/scripts/backtest.py \
--strategy rsi_reversal --symbol BTC-USD --period 1y| File | Purpose |
|---|---|
scripts/scanner.py | Main signal scanner |
scripts/signals.py | Signal generation logic |
scripts/indicators.py | Technical indicator calculations |
config/settings.yaml | Configuration |
© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 7 other files (scripts, references) in skills/crypto-signal-generator of aAAaqwq/AGI-Super-Team.
Open the folder on GitHubat commit 7cefd81
Generating Trading Signals next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Generating Trading Signals this skillaAAaqwq/AGI-Super-Team | 105 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Tushare Datazillionare/zillionare | 322 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 878 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Polyclawchainstacklabs/polyclaw | 359 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Markdownfacioquo/stock-indicators-dotnet | 1.2k | — | ~812 | Automated safety check: Pass | Apache-2.0 |
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求,转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
atilaahmettaner/tradingview-mcp
AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and…
komako-workshop/digital-oracle
Answer prediction questions using market trading data, not opinions.
chainstacklabs/polyclaw
Trade on Polymarket via split + CLOB execution. An agent skill from chainstacklabs/polyclaw.
facioquo/stock-indicators-dotnet
Format and lint Markdown in this repository against GitHub Flavored Markdown and its markdownlint-cli2 configuration — headers, lists, code fences, callouts (VitePress containers on docs-site pages…
MobiusQuant/OpenMobius-skill
Provides multi-school trading Q&A, chart/OHLCV analysis, annotation, and fresh-market workflows covering ICT/SMC, ChanLun, Wyckoff, Price Action, Order Flow, VSA, and Elliott Wave.
aAAaqwq/AGI-Super-Team
Create SEO-optimized marketing content with consistent brand voice.
aAAaqwq/AGI-Super-Team
Advanced financial calculator with future value tables, present value, discount calculations, markup pricing, and compound interest.
aAAaqwq/AGI-Super-Team
Transaction-verified trading signals on Base blockchain. An agent skill from aAAaqwq/AGI-Super-Team.
aAAaqwq/AGI-Super-Team
Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents).
aAAaqwq/AGI-Super-Team
Create distinctive, production-grade static sites with React, Tailwind CSS, and shadcn/ui — no mockups needed.
aAAaqwq/AGI-Super-Team
Publish and manage content on 知识星球 (zsxq.com). An agent skill from aAAaqwq/AGI-Super-Team.
Categories
Multi-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confiden Generate trading signals using technical…. Generating Trading Signals is an agent skill from aAAaqwq/AGI-Super-Team.).
Generating Trading Signals fits situations like: analyzing assets for trading opportunities; checking technical indicators; with phrases like get trading signals; check indicators.
Run `npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a claude-code`. Or copy the skill folder (skills/crypto-signal-generator in aAAaqwq/AGI-Super-Team) into .claude/skills/generating-trading-signals in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a codex`. Or copy the skill folder (skills/crypto-signal-generator in aAAaqwq/AGI-Super-Team) into .agents/skills/generating-trading-signals in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aAAaqwq/AGI-Super-Team --skill generating-trading-signals -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/generating-trading-signals, .gemini/skills/generating-trading-signals, .github/skills/generating-trading-signals and .opencode/skills/generating-trading-signals in your project.
Going by SKILL.md and its folder, Generating Trading Signals needs Python for the scripts in its folder and the command-line tools its instructions call (python and pip). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(python:*).
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Generating Trading Signals is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Generating Trading Signals: Tushare Data (zillionare/zillionare, 322 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 878 stars) and Polyclaw (chainstacklabs/polyclaw, 359 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.
Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.