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Trader Budget

Community
Jakeschincariol
trader-budget

Budget Manager. Sizes every position to your budget and your max loss per trade. Reads the trade plan from trader-exit (entry, stop, target), finds the whole shares that fit inside four limits (max loss per trade, position cap, max order, cash after your buffer), says which limit decided it, and writes ONE bracket order (entry, stop-loss, take-profit) to trader/orders.json in the exact shape of Alpaca's place_stock_order. A stop too far away for your max loss is a plain refusal, not a smaller order. Nothing is placed. Use when the user says "how many shares", "size this trade", "how much should I buy", "I have $5,000", "I only want to risk $50 a trade", "set my rules", "keep 10% in cash", or after /trader-exit writes a plan.

Overview

PublisherJakeschincariol
Repositoryday-trader-skill
Skill nametrader-budget
Stars
617
Forks
119
Bundled files
3
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.

  • 3 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 Budget 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-budget
  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-budget .claude/skills/trader-budget
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trader Budget 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 Budget 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 Budget 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-budget

The Budget Manager turns a plan ("buy TSLA at 364.18, stop 358.32") into an exact order ("buy 8 shares"), inside rules the user sets once. The stop decides the size: the further away the stop, the fewer shares. It writes a proposal only. trader-risk checks it and trader-broker asks the user yes or no. Day trading loses most people money. Sizing to a max loss keeps each loss small; it does not make a trade win.

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

bash
python3 "${CLAUDE_SKILL_DIR}/size.py"                        # trader/plan.json + trader/config.json
python3 "${CLAUDE_SKILL_DIR}/size.py" --write                # write trader/orders.json
python3 "${CLAUDE_SKILL_DIR}/size.py" --limit --write        # a limit order at the plan's entry
python3 "${CLAUDE_SKILL_DIR}/size.py" --limit 364.00 --json  # a limit order at 364.00
python3 "${CLAUDE_SKILL_DIR}/size.py" --weights AAPL=40,KO=60 --config split.json   # weights mode, below

--now "2026-10-19 10:15" pins the clock (New York time). A plan for another day is refused: make a new one with trader-exit.

What it reads and writes

filewhat
trader/config.jsonthe rules (start from config.example.json in this folder)
trader/plan.jsonthe trade: entry, stop, target, setup, flat-by time (trader-exit writes it)
trader/prices.jsonoptional: a fresh price above the plan's entry means a bigger risk (trader-alerts writes it)
trader/portfolio.jsonoptional: its cash caps the size (trader-broker keeps it)
trader/orders.jsonthe one proposed bracket order it writes with --write

Step 1: set the rules once

If trader/config.json does not exist, copy config.example.json into trader/config.json and ask the user for each value in plain words:

  • budget: how much money this is for. Only money they can afford to lose.
  • cash_buffer_pct: how much always stays in cash (default 10).
  • max_loss_per_trade_usd: the most one trade may lose if the stop fills at the stop (default 50).
  • max_position_pct, max_order_usd, min_order_usd: the biggest position (75% of the budget), the biggest order ($4,000) and the smallest order ($5).
  • The day limits trader-risk enforces: max_daily_loss_usd (150), max_trades_per_day (3), min_reward_risk (1.0), require_stop (true), no_entries_before / no_entries_after ("09:45" / "15:30") and flat_by ("15:55"), all New York time.
  • blocked: tickers they never want to trade.
  • Keep paper true until they have watched it work on a paper account.

Step 2: size the trade

bash
python3 "${CLAUDE_SKILL_DIR}/size.py" --write

Whole shares only: Alpaca takes no fractions in a bracket order. The size is the smallest of four limits:

limitshares
max lossmax_loss_per_trade_usd / risk a share (entry minus stop)
position capbudget x max_position_pct / entry
max ordermax_order_usd / entry
cash(budget minus the cash buffer) / entry, never more than the cash in trader/portfolio.json

The entry it sizes at: the limit price with --limit. For a market order, the plan's entry, or the price in trader/prices.json if it is fresh (under 15 minutes old) and higher. A price that ran up since the plan means a bigger loss at the same stop, so fewer shares. A lower price never shrinks the risk.

It refuses, and writes no order, when: the size is zero shares, the order is under the minimum, reward:risk is under min_reward_risk, the stop is not below the entry, the target is not above it (the move already happened), the plan is for another day, the ticker is blocked, or the plan is a short. Say the reason to the user in one line.

Step 3: show the user

Show the four limits, which one decided the size, the shares, the dollars and the max loss at the stop. Say plainly that a stop is an order, not a promise: in a fast market it can fill below the stop. Then hand over to /trader-risk.

Example: the reel

TSLA on Monday 2026-10-19. Opening-range breakout: entry 364.18 at 10:15 AM, stop 358.32 (the opening-range midpoint), target 370.04 (1R). Risk 5.86 a share. The example config: $5,000 budget, 10% cash buffer, $50 max loss.

limitthe mathshares
max loss$50 / 5.868 (decides it)
position cap75% of $5,000 = $3,750 / 364.1810
max order$4,000 / 364.1810
cash$5,000 minus $500 = $4,500 / 364.1812

8 shares = $2,913.44. Max loss at the stop: 8 x 5.86 = $46.88. It writes:

json
{"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",
 "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)",
 "plan": {"entry": 364.18, "stop": 358.32, "target": 370.04, "risk_per_share": 5.86, "max_loss": 46.88,
          "setup": "orb", "entry_time": "10:15 AM", "flat_by": "15:55"}}

why and plan are notes for trader-risk and trader-broker. They are never sent to Alpaca. With the stop at 300.00 instead, one share would risk 64.18, more than the $50 max loss: no order. At 10:52 the real quote was 366.48, so the same plan sizes to 6 shares at 8.16 a share, and reward:risk falls to 0.44: refused, because the move it was waiting for has mostly happened.

Weights mode (kept from v1)

--weights AAPL=22.04,KO=10.86 or --targets FILE (targets.example.json here) splits a budget across a list by weight: the cash buffer comes off the top, weights are renormalised to 100, any stock over max_position_pct is pinned at the cap and its excess shared out, slices under the minimum order are dropped, and amounts round to whole dollars so nothing is left idle by accident. With "max_position_pct": 25 and "fractional": true, the example file gives AAPL $1,250 (capped), AXP $1,119, GOOGL $823, KO $708, BAC $600. With "fractional": false (the example config) it buys whole shares and needs prices (--prices trader/prices.json). These are plain buys with no stop: trader-risk blocks them while require_stop is true and counts each one against max_trades_per_day. Use a separate config (--config) for a long-term split.

Rules

  • Proposals only. This skill never calls a broker tool.
  • Never size money the user has not said is for this. Ask for the budget and the max loss.
  • Every number comes from the config, the plan or the prices. Nothing is guessed.
  • No projections: never say what a trade will make. A target is a plan, not a forecast.
  • Free Yahoo prices are unofficial and can lag. The broker's price is the one that fills.

What it never does

It never places, approves or schedules an order, never raises a limit on its own, never shrinks a stop to fit more shares, and never sizes options, margin or short positions.

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 Budget AI skill do?

Budget Manager. Sizes every position to your budget and your max loss per trade. Reads the trade plan from trader-exit (entry, stop, target), finds the whole shares that fit inside four limits (max loss per trade, position cap, max order, cash after your buffer), says which limit decided it, and writes ONE bracket order (entry, stop-loss, take-profit) to trader/orders.json in the exact shape of Alpaca's place_stock_order. A stop too far away for your max loss is a plain refusal, not a smaller order. Nothing is placed. Use when the user says "how many shares", "size this trade", "how much sh...

Why use Trader Budget on TypingMind?

Because you install it once and use it with any model. Trader Budget 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 Budget in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jakeschincariol/day-trader-skill/tree/main/trader-budget. 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 Budget?

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 Budget?

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

Is the Trader Budget 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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