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。
Paper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later.
$ npx skills add krakenfx/kraken-cli --skill kraken-playground -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install krakenfx/kraken-cli kraken-playground --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/krakenfx/kraken-cli.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/kraken-playground .claude/skills/kraken-playground && 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 "kraken-playground" agent skill from https://github.com/krakenfx/kraken-cli/tree/main/skills/kraken-playground into .claude/skills/kraken-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kraken-playground", 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/krakenfx/kraken-cli/tree/main/skills/kraken-playgroundType 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 krakenfx/kraken-cli --skill kraken-playground -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install krakenfx/kraken-cli kraken-playground --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/krakenfx/kraken-cli.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/kraken-playground .agents/skills/kraken-playground && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "kraken-playground" agent skill from https://github.com/krakenfx/kraken-cli/tree/main/skills/kraken-playground into .agents/skills/kraken-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kraken-playground", 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 krakenfx/kraken-cli --skill kraken-playground -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install krakenfx/kraken-cli kraken-playground --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/krakenfx/kraken-cli.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/kraken-playground .cursor/skills/kraken-playground && 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 "kraken-playground" agent skill from https://github.com/krakenfx/kraken-cli/tree/main/skills/kraken-playground into .cursor/skills/kraken-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kraken-playground", 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/krakenfx/kraken-cli.git --path skills/kraken-playground--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 krakenfx/kraken-cli --skill kraken-playground -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install krakenfx/kraken-cli kraken-playground --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/krakenfx/kraken-cli.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/kraken-playground .gemini/skills/kraken-playground && 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 "kraken-playground" agent skill from https://github.com/krakenfx/kraken-cli/tree/main/skills/kraken-playground into .gemini/skills/kraken-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kraken-playground", 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 krakenfx/kraken-cli kraken-playgroundInstalls 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 krakenfx/kraken-cli --skill kraken-playground -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/krakenfx/kraken-cli.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/kraken-playground .github/skills/kraken-playground && 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 "kraken-playground" agent skill from https://github.com/krakenfx/kraken-cli/tree/main/skills/kraken-playground into .github/skills/kraken-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kraken-playground", 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 krakenfx/kraken-cli --skill kraken-playground -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install krakenfx/kraken-cli kraken-playground --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/krakenfx/kraken-cli.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/kraken-playground .opencode/skills/kraken-playground && 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 "kraken-playground" agent skill from https://github.com/krakenfx/kraken-cli/tree/main/skills/kraken-playground into .opencode/skills/kraken-playground/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kraken-playground", 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.
kraken-playgroundPaper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later.
Kraken Playground is an agent skill from krakenfx/kraken-cli. Paper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Stock and market analysis and Trading and backtesting. The repository describes itself as: The first AI-native CLI for trading crypto, stocks, forex, and derivatives. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit aa56e59. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
jqFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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.
Kraken Playground loads about 2.1k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 1,075 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); files beside SKILL.md are not scanned.
The full file from krakenfx/kraken-cli at commit aa56e59, republished under its MIT licence (© krakenfx). 1,075 words, ~2,077 tokens.
.claude/skills/kraken-playground/SKILL.md (or your agent's skills folder).A session ties a market recorder and the workspace's paper account to one window. Live prices stream in and get recorded as the session's tape, paper orders fill against those prices on the shared account journal, and every decision is logged, so the window can be replayed and analyzed later. No real order is ever placed inside a paper workspace.
Use this skill for:
kraken playground is the fastest way in: it creates (or reuses, never re-funding) a paper workspace named playground with 10,000 USD, prints how to watch it, and starts a recorded, self-stopping demo session:
kraken playground --symbols BTC/USD --for 1h 2>/dev/null &
export KRAKEN_WORKSPACE=playgroundEverything it makes is a plain workspace plus a session — the commands below drive it like any other scope.
A session is a recorded window over the active scope's account journal. One session id (s1, s2, …) binds three things: the recorder (live market data to sessions/s<n>/tape.*), the window markers on the account journal (which trades belong to the session), and the session's decision log (the "why" behind each action). There is no daemon and no shared memory between rounds. State lives on disk, and each round reads what it needs.
The CLI has no scheduler and runs no strategy. It records, fills paper orders, and logs. The agent decides, and something external holds the pace (see Pacing).
Work inside a paper workspace (create one once with kraken workspace create <name> --capital 10000 --mode paper), then:
export KRAKEN_WORKSPACE=<name>
kraken session start \
--symbols BTC/USD --channels ticker,trade --to duckdb,jsonl \
--label my-hypothesis-r1 \
-o json 2>/dev/null &The session_started JSON line on stdout carries the session id ("session":"s<n>"). Print it to the user as soon as the session starts, and again in the final report. It is the handle for everything after: kraken session show --session s<n>, resuming a /loop, and locating the artifacts under sessions/s<n>/.
--symbols: instruments to record and trade against--channels: which feeds to record (e.g., ticker,trade, add book for depth)--to: recording sinks (duckdb for query, jsonl for raw replay)--label: a human handle, usable anywhere a --session ref is--strategy / --strategy-params: name and JSON knobs of the driver, recorded in session.json so two sessions compare knob-for-knob--for: auto-stop after a window (e.g. 1h) — the session closes itself cleanly--from tape:<name> --speed 10: replay a recorded tape instead of the live marketBuy or sell against recorded prices — the order verbs are mode-routed, so inside a paper workspace they fill on the paper account. Always pass a reason; it lands in the active session's decision log:
kraken order buy BTC/USD <volume> --type market --reason "<why>" -o json 2>/dev/null
kraken order sell BTC/USD <volume> --type market --reason "<why>" -o json 2>/dev/nullLog a non-trade decision (a skip, a gate, an alert) so the log records rounds where nothing traded:
kraken session note --kind skip --symbol BTC/USD --reason "<why>" -o json 2>/dev/nullData lands under the session directory of the active scope:
# Read the decision log (evidence) and the typed state cell (the loop's
# cursor: round, legs_done, zone, last_action_at) through the CLI —
# no layout knowledge needed:
kraken session decisions --session s<n> -o json
kraken session state get --session s<n> -o jsonsession.json: the session's contract — window, opening equity anchor, strategy, experimentdecisions.jsonl: one line per decision (kind, symbol, reason, timestamp, order id)tape.duckdb / tape.jsonl: the raw tape for replay and P&LPacing is external to the CLI. Two mechanisms, one per hypothesis shape:
/loop owns the schedule. Set its interval to the decision spacing and it fires one round per interval.kraken-ws-streaming).For time-gated runs, the interval is a floor. A round may start late (the scheduler adds jitter), never early. Do not add a second pacing gate inside the round; /loop already enforces spacing.
The scheduler floor is 60 seconds. /loop, cron, and ScheduleWakeup all clamp to a one-minute minimum, so interval_s must be >= 60 and a sub-minute cadence is impossible. If the user asks for "every 30 seconds", clamp to 60s and say so — never set a sub-minute interval_s, and never let the report claim a cadence the harness cannot run.
A session over many rounds is interventional: one visit per interval, paced from outside. Pick the mechanism by what triggers a decision.
/loop N fires the round, each round takes one REST snapshot (kraken ticker, kraken ohlc), decides, acts. See recipe-playground-dca.recipe-playground-dca-triggered.Time-gated misses conditions that appear and resolve between visits. Event-gated catches them but runs as a long-lived process and is blind during reconnect gaps. Choose per hypothesis.
A driver is a recipe that turns a hypothesis into recorded rounds. The shape of every round:
--strategy-params.order buy / order sell on a trigger, session note on a skip, always with a numeric reason.Keep every number that gates a buy or skip in --strategy-params, not only in prose reasons. That is what makes two sessions comparable. Keep the arithmetic deterministic (compute in jq/bc, do not eyeball it) so a rerun on the same tape reaches the same decisions.
kraken session show -o json 2>/dev/null | jq '.window, .valuation'
kraken session stop -o json 2>/dev/null
kraken explain pnl --session latest -o json 2>/dev/null
kraken lab score --session latest -o json 2>/dev/null--session accepts latest (the default everywhere), an ordinal (s3), or a label.
kraken-paper-strategy)./loop for time-gated, a stream's event rate for event-gated. Never add a redundant pacing gate inside a round. The scheduler floor is 60s — no sub-minute cadence.session.json, decisions.jsonl, and the tape sinks) is owned by the CLI recorder. The agent only reads it, and only for status and the stop-time summary. Never write, edit, mkdir, or append inside it — every decision goes through kraken order buy / kraken session note, so the recorder stays the single writer.kraken feedback.© krakenfx, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/kraken-playground of krakenfx/kraken-cli.
Open the folder on GitHubat commit aa56e59
Kraken Playground 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 |
|---|---|---|---|---|---|---|
| Kraken Playground this skillkrakenfx/kraken-cli | 751 | — | ~2.1k | 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 | |
| Worth Buy Stocksstarriv/worth-buy-stocks | 175 | — | ~4.5k | Automated safety check: Notes | None | |
| Regimejackson-video-resources/markov-hedge-fund-method | 484 | — | ~1.6k | Automated safety check: Pass | Custom licence |
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.
starriv/worth-buy-stocks
Evaluate US stocks under an Alpaca trend and relative-strength framework, and prioritize defined-risk net-credit income spreads: Bull Put/Bear Call first, Iron Condor second.
jackson-video-resources/markov-hedge-fund-method
Detect the market regime (Bull / Bear / Sideways) for ANY asset and turn it into a tradeable signal or a risk filter.
Oft3r/agentic-trading-desk
Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP.
krakenfx/kraken-cli
Price alerts, threshold monitoring, and notification triggers for agents.
krakenfx/kraken-cli
Progress from manual trading to full agent autonomy with controlled risk at each level.
krakenfx/kraken-cli
Capture the spot-futures price spread with delta-neutral basis trades.
krakenfx/kraken-cli
Dollar cost averaging with scheduled buys and performance tracking.
krakenfx/kraken-cli
Discover staking strategies, allocate funds, and track earn positions.
krakenfx/kraken-cli
Handle order failures, network errors, and duplicate submissions safely.
Categories
Paper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later. Kraken Playground is an agent skill from krakenfx/kraken-cli. Paper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later.
Kraken Playground fits situations like: tasks that involve Stock and market analysis; tasks that involve Trading and backtesting.
Run `npx skills add krakenfx/kraken-cli --skill kraken-playground -a claude-code`. Or copy the skill folder (skills/kraken-playground in krakenfx/kraken-cli) into .claude/skills/kraken-playground in your project. Claude Code loads it when a task matches its description.
Run `npx skills add krakenfx/kraken-cli --skill kraken-playground -a codex`. Or copy the skill folder (skills/kraken-playground in krakenfx/kraken-cli) into .agents/skills/kraken-playground 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 krakenfx/kraken-cli --skill kraken-playground -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kraken-playground, .gemini/skills/kraken-playground, .github/skills/kraken-playground and .opencode/skills/kraken-playground in your project.
Going by SKILL.md and its folder, Kraken Playground needs the command-line tools its instructions call (jq).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. 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. Review the folder before installing.
Kraken Playground is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Kraken Playground: Tushare Data (zillionare/zillionare, 322 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 878 stars) and Worth Buy Stocks (starriv/worth-buy-stocks, 175 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
krakenfx (a GitHub organization) maintains it in krakenfx/kraken-cli, which has 751 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on August 7, 2026.
Source: krakenfx/kraken-cli on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.