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Trader Broker

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Jakeschincariol
trader-broker

Order Executor. Sends approved orders to your broker, paper trading by default, never without your yes. Shows each order as a plain ticket (a bracket shows its stop-loss, take-profit and the max loss at the stop) plus the exact JSON for Alpaca's place_stock_order, records your yes word for word, then Claude's own Allow once / Deny card asks again. Builds the sell ticket that closes a day trade by your flat-by time, records fills, and logs each trade's max loss so trader-risk can hold the daily limit. Covers setting up Alpaca's official MCP server in Claude Desktop (paper by default, keys in env vars, never in chat), the Interactive Brokers connector, and setting order tools to "Needs approval". Use when the user says "place the order", "buy it", "execute", "send it to my broker", "close my position", "flatten", "get me out", "connect Alpaca", "set up paper trading", or after /trader-risk passes.

Overview

PublisherJakeschincariol
Repositoryday-trader-skill
Skill nametrader-broker
Stars
617
Forks
119
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Jakeschincariol on GitHub. Read the source before you install it.

Installation

Install the Trader Broker AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Jakeschincariol/day-trader-skill/tree/main/trader-broker
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Jakeschincariol/day-trader-skill.git /tmp/day-trader-skill
mkdir -p .claude/skills
cp -r /tmp/day-trader-skill/trader-broker .claude/skills/trader-broker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trader Broker in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trader Broker on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trader Broker is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

trader-broker

The Order Executor is the only skill in this pack that can lead to a real order, so it is the strictest. An order reaches the market only after three separate gates, every time, for every order:

  1. trader-risk passed this exact order today (matched by fingerprint).
  2. The user typed an explicit yes for this one order in the chat.
  3. The user clicked Allow once on Claude's own permission card, which appears because the order tool is set to "Needs approval".

Two yeses from the user, one PASS from the rules. No yes, no order.

${CLAUDE_SKILL_DIR} below is this skill's folder (where this SKILL.md lives).

bash
python3 "${CLAUDE_SKILL_DIR}/ticket.py" show                     # every ticket, READY or not
python3 "${CLAUDE_SKILL_DIR}/ticket.py" approve --index 1 --reply "yes"
python3 "${CLAUDE_SKILL_DIR}/ticket.py" result --index 1 --status placed --broker-id ID --filled-qty 8 --filled-price 364.20
python3 "${CLAUDE_SKILL_DIR}/ticket.py" fill --symbol TSLA --side sell --qty 8 --price 370.04
python3 "${CLAUDE_SKILL_DIR}/ticket.py" flatten --symbol TSLA --qty 8
python3 "${CLAUDE_SKILL_DIR}/ticket.py" log

ticket.py never talks to a broker. It renders tickets, checks that a reply is a real yes for that order, builds the flatten ticket, and keeps the log in trader/state/broker.json. --now "2026-10-19 10:15" pins the clock (New York time).

What it reads and writes

filewhat
trader/orders.jsonthe proposed orders (trader-budget writes it; flatten replaces it)
trader/state/risk.jsontrader-risk's verdicts; only a PASS from today is READY
trader/state/broker.jsonevery yes, no, placed, failed and filled, with each entry's max loss
trader/portfolio.jsoncash and shares, updated by fill and by result --filled-qty
trader/plan.jsonthe flat-by time for flatten

Setup A: Alpaca (official MCP server, Claude Desktop)

Alpaca's own server is github.com/alpacahq/alpaca-mcp-server (MIT). It runs on the user's computer inside Claude Desktop. It is not in Claude's connector directory. It trades on a paper account unless told otherwise. Checked against its source on 2026-10-20 (version 2.4.0).

  1. The user makes an Alpaca account and creates paper trading API keys in the Alpaca dashboard. Paper keys are separate from live keys.
  2. The user installs uv (it provides uvx), from docs.astral.sh/uv.
  3. In Claude Desktop: Settings > Developer > Edit Config. That opens claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\). The user adds this block (also in claude_desktop_config.example.json here) and types their own keys into the file:
json
{
  "mcpServers": {
    "alpaca": {
      "command": "uvx",
      "args": ["alpaca-mcp-server"],
      "env": {
        "ALPACA_API_KEY": "paste your paper key here, in this file only",
        "ALPACA_SECRET_KEY": "paste your paper secret here, in this file only",
        "ALPACA_PAPER_TRADE": "true",
        "ALPACA_TOOLSETS": "account,trading,stock-data"
      }
    }
  }
}

The env block hands the keys to the server as environment variables. Keys never go in the chat. Never ask for them, never read this file back into the conversation, and if the user pastes a key anyway, tell them to delete that message and make new keys in the Alpaca dashboard. ALPACA_PAPER_TRADE is already true by default; writing it makes it visible. ALPACA_TOOLSETS is optional and hides the tools they do not need. 4. Restart Claude Desktop. 5. Set the tool permissions. Customize > Connectors (Settings > Connectors in older versions), open alpaca, and for each tool pick Always allow, Needs approval or Blocked:

  • place_stock_order: Needs approval. Never Always allow.
  • every other tool that places, changes, cancels or closes anything (cancel_order_by_id, replace_order_by_id, close_position, update_account_config): Needs approval.
  • place_option_order, place_crypto_order, close_all_positions, cancel_all_orders, exercise_options_position, do_not_exercise_options_position: Blocked unless the user has a reason and says so.
  • read-only tools (get_account_info, get_all_positions, get_open_position, get_orders, get_clock, get_stock_snapshot, get_stock_latest_quote): Always allow is fine.
  1. Check it: ask Claude for the Alpaca account info (read only) and confirm in the Alpaca dashboard that it is the paper account.

In Claude Code instead of Claude Desktop, keep the order tool on ask in .claude/settings.json: "permissions": {"ask": ["mcp__alpaca__place_stock_order"]}, and never put an order tool in allow.

Bracket orders on Alpaca. place_stock_order takes take_profit_limit_price and stop_loss_stop_price (and an optional stop_loss_limit_price). When either is there, the server sets order_class to "bracket" by itself; trader-budget writes it anyway so the ticket shows it. A bracket is whole shares only, with time_in_force day or gtc. After the entry fills, the stop-loss and the take-profit wait at the broker as two orders that cancel each other. They are day orders too, so they end at the close: one more reason to be flat by then.

Setup B: Interactive Brokers (connector in Claude's directory)

Interactive Brokers publishes a verified connector: claude.ai/directory/interactive-brokers (connector URL https://api.ibkr.com/v1/api/mcp). Add it from Customize > Connectors > Browse connectors and sign in to IBKR there, not in the chat. Its listing says Claude can draft trade instructions that are sent to the user's IBKR account for their review and approval, and that Claude never submits orders directly to the market. So with IBKR the final yes happens in IBKR as well. Set "broker": "ibkr" in trader/config.json. Set its tools that draft orders to Needs approval too.

Steps: the entry

  1. ticket.py show. Only READY tickets go to the user. A ticket that is NOT READY or BLOCKED goes back to /trader-risk.
  2. Show ONE ticket and ask: "Place this order? Reply yes or no." One order per question. Never offer "yes to all".
  3. Run ticket.py approve --index N --reply "<the user's reply, word for word>". If it prints "Not recorded", the reply was not an explicit yes for this order (for example "sure", "yes to all", or a yes that names a different stock or amount). Ask again. Never turn a reply into a yes yourself.
  4. Only after "Recorded your yes", call place_stock_order with exactly the JSON the ticket printed. Claude's card appears: Allow once or Deny.
  5. Record what happened: ticket.py result --index N --status placed --broker-id <id> --filled-qty Q --filled-price P (the fill from the response or get_open_position), or --status denied, or --status failed with --note. A failed order is not retried without a new check and a new yes. The log keeps the entry's max loss for trader-risk's daily limit.

Steps: while it is open, and out by the close

  • trader-alerts watches the stop, the target and the flat-by time (alerts.py add --from-plan). The bracket's own orders do the stopping.
  • When the stop-loss or the take-profit fills, record it: ticket.py fill --symbol TSLA --side sell --qty 8 --price 358.32.
  • By flat_by (15:55 New York), anything still open gets closed:
    1. Ask Alpaca how many shares are held: get_open_position (read only).
    2. ticket.py flatten --symbol TSLA --qty 8 writes a market sell for those shares to trader/orders.json.
    3. /trader-risk. A sell that only closes what the user holds is never blocked by the daily limits or the entry window.
    4. ticket.py show, then the user's yes for that one order, as above.
    5. The bracket's stop-loss and take-profit still hold those shares, so Alpaca rejects a new sell until they are canceled: get_orders (status open, nested true) shows them; cancel_order_by_id each one (Needs approval). Then place_stock_order with the ticket, then result.

Example: the reel

ORDER 1 of 1, PAPER account, Alpaca
  BUY 8 TSLA, market, good for today
  stop-loss 358.32
  take-profit 370.04
  max loss about $46.88 if the stop fills at 358.32 (it can fill worse in a fast market)
  why: opening-range breakout on TSLA: 8 shares, bound by your $50 max loss per trade (8 x 5.86 = $46.88 at the stop)
  READY: trader-risk PASS, waiting for your yes
  Claude will call place_stock_order with exactly:
    {"symbol": "TSLA", "side": "buy", "qty": "8", "type": "market", "time_in_force": "day",
     "order_class": "bracket", "take_profit_limit_price": "370.04", "stop_loss_stop_price": "358.32"}

The user replies "yes". Claude records it, calls place_stock_order, and the card reads "Claude wants to use Place stock order" with that JSON and two buttons: Allow once, Deny. Allow once sends it to the paper account. The why and the plan stay in the file; they are never sent.

What it never does

  • Never places an order without all three gates, and never two orders on one yes.
  • Never places orders from a scheduled or background task: nobody is there to say yes.
  • Never asks for, reads, stores or repeats API keys or passwords.
  • Never switches ALPACA_PAPER_TRADE or "paper" to live. The user does that themselves.
  • Never calls close_all_positions, cancel_all_orders, option or crypto order tools on its own.
  • Never promises a fill price: a market order and a stop fill at whatever the market gives.

Safety

  • Education and tooling, not financial advice. A PASS is a rules check, not a recommendation.
  • Paper trading by default ("paper": true). Going live is the user's own decision, in their own config.
  • Nothing in this pack places an order except trader-broker, and only when all three hold: trader-risk passed that exact order today, the user typed an explicit yes for that one order in the chat, and the user clicked Allow once on Claude's own card because the order tool is set to "Needs approval" (Customize > Connectors > tool permissions). Never set an order tool to "Always allow".
  • No options, margin, short selling or leverage unless the config allows it and the user confirms.
  • Broker keys live in environment variables or the Claude Desktop config, never in the chat.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Trader Broker AI skill do?

Order Executor. Sends approved orders to your broker, paper trading by default, never without your yes. Shows each order as a plain ticket (a bracket shows its stop-loss, take-profit and the max loss at the stop) plus the exact JSON for Alpaca's place_stock_order, records your yes word for word, then Claude's own Allow once / Deny card asks again. Builds the sell ticket that closes a day trade by your flat-by time, records fills, and logs each trade's max loss so trader-risk can hold the daily limit. Covers setting up Alpaca's official MCP server in Claude Desktop (paper by default, keys in...

Why use Trader Broker on TypingMind?

Because you install it once and use it with any model. Trader Broker is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trader Broker in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jakeschincariol/day-trader-skill/tree/main/trader-broker. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Trader Broker?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trader Broker?

As many as you like. As long as a model supports skills, you can use Trader Broker with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trader Broker AI skill free?

Yes. It is published on GitHub by Jakeschincariol under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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