Agent skill

Kraken Playground

by krakenfx in 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.

MITAuto-check passedBusiness, Finance & HR

Install Kraken Playground

skills CLI
$ npx skills add krakenfx/kraken-cli --skill kraken-playground -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install krakenfx/kraken-cli kraken-playground --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
kraken-playground
GitHub stars
751
Token cost
~2.1k tokens
SKILL.md length
1,075 words
Files
1
Skills in repo
59
Repo updated
First seen
Licence
MIT

At a glance

Paper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later.

  • Works in 3 steps: READ: pull the market state the decision… → THINK: apply the numeric gates from… → ACT: order buy / order sell on a…
  • Tasks that involve Stock and market analysis
  • SKILL.md covers The One-Command Demo, What a Session Is, Start a Session and Paper Trades, plus 6 more sections
  • Calls jq

What it does

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.

When your agent uses it

  • Tasks that involve Stock and market analysis
  • Tasks that involve Trading and backtesting

Example prompts

  • “/kraken-playground”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. READ: pull the market state the decision needs (price, an average, spread).
  2. THINK: apply the numeric gates from --strategy-params.
  3. ACT: order buy / order sell on a trigger, session note on a skip, always with a numeric reason.

What it can do on your machine

Read from SKILL.md and the folder at commit aa56e59. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from krakenfx/kraken-cli at commit aa56e59, republished under its MIT licence (© krakenfx). 1,075 words, ~2,077 tokens.

Download SKILL.mdSave it as .claude/skills/kraken-playground/SKILL.md (or your agent's skills folder).
name
kraken-playground
description
Paper-trading sandbox over workspace sessions: record live market data and agent decisions inside a session window, replay and score it later.
version
2.0.0

kraken-playground

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:

  • running a paper-trading hypothesis on live prices with no real money
  • recording ticker, trade, and book data alongside paper fills and decision reasons
  • driving an agent hypothesis over a window at a fixed cadence
  • replaying a session and computing P&L after the fact

The One-Command Demo

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:

bash
kraken playground --symbols BTC/USD --for 1h 2>/dev/null &
export KRAKEN_WORKSPACE=playground

Everything it makes is a plain workspace plus a session — the commands below drive it like any other scope.

What a Session Is

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).

Start a Session

Work inside a paper workspace (create one once with kraken workspace create <name> --capital 10000 --mode paper), then:

bash
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 market

Paper Trades

Buy 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:

bash
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/null

Log a non-trade decision (a skip, a gate, an alert) so the log records rounds where nothing traded:

bash
kraken session note --kind skip --symbol BTC/USD --reason "<why>" -o json 2>/dev/null

Recording

Data lands under the session directory of the active scope:

bash
# 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 json
  • session.json: the session's contract — window, opening equity anchor, strategy, experiment
  • decisions.jsonl: one line per decision (kind, symbol, reason, timestamp, order id)
  • tape.duckdb / tape.jsonl: the raw tape for replay and P&L

Pacing

Pacing is external to the CLI. Two mechanisms, one per hypothesis shape:

  • Time-gated: /loop owns the schedule. Set its interval to the decision spacing and it fires one round per interval.
  • Event-gated: a WebSocket stream's event rate owns the schedule. The loop acts on qualifying events (see 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.

Show full SKILL.md (425 more words)Show less

Running over a Window

A session over many rounds is interventional: one visit per interval, paced from outside. Pick the mechanism by what triggers a decision.

  • "Act every N minutes on the current price": time-gated. /loop N fires the round, each round takes one REST snapshot (kraken ticker, kraken ohlc), decides, acts. See recipe-playground-dca.
  • "Act the instant a condition trips": event-gated. Subscribe to a stream and act on each qualifying tick, rate-limited so you do not act faster than intended. See 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.

Driving Your Own Hypothesis

A driver is a recipe that turns a hypothesis into recorded rounds. The shape of every round:

  1. READ: pull the market state the decision needs (price, an average, spread).
  2. THINK: apply the numeric gates from --strategy-params.
  3. ACT: 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.

Show, Stop, and Score

bash
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.

Hard Rules

  • A session inside a paper workspace never places a live order. It records and fills paper only.
  • Paper results may overstate live performance: fees and slippage are simulated and there are no partial fills (see kraken-paper-strategy).
  • No daemon, no shared memory between rounds. State lives on disk under the workspace and its sessions.
  • Pace from outside the CLI: /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.
  • Always pass a reason on every trade and skip, so the decision log carries the full "why".
  • The session directory (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.
  • If you hit a mismatch between what you are trying to do and the CLI's interface or responses — including a mismatch between this skill and the installed CLI version's contract — feel free to submit feedback with 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

Files

Just SKILL.md in skills/kraken-playground of krakenfx/kraken-cli.

Open the folder on GitHubat commit aa56e59

Compare with similar skills

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.

Kraken Playground compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Kraken Playground this skillkrakenfx/kraken-cli751—~2.1kAutomated safety check: PassMIT
Tushare Datazillionare/zillionare3222 repos~2.3kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT
Digital Oraclekomako-workshop/digital-oracle878—~5.9kAutomated safety check: PassMIT
Worth Buy Stocksstarriv/worth-buy-stocks175—~4.5kAutomated safety check: NotesNone
Regimejackson-video-resources/markov-hedge-fund-method484—~1.6kAutomated safety check: PassCustom licence

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Questions about Kraken Playground

What does Kraken Playground do?

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.

When should I use Kraken Playground?

Kraken Playground fits situations like: tasks that involve Stock and market analysis; tasks that involve Trading and backtesting.

How do I install Kraken Playground in Claude Code?

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.

How do I install Kraken Playground in Codex?

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.

Can I use Kraken Playground in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Kraken Playground need to run?

Going by SKILL.md and its folder, Kraken Playground needs the command-line tools its instructions call (jq).

Does Kraken Playground access the network?

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.

Is Kraken Playground safe to install?

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.

What licence does Kraken Playground use?

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.

How many tokens does Kraken Playground use?

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.

What are the alternatives to Kraken Playground?

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.

Who maintains Kraken Playground?

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.