agentmods.dev

trade

A trading workflow for analyzing market data, forming a trade idea, checking risk gates, and placing a trade only after user confirmation.

In plain words
What is it for?
Use it to review price trends, support and resistance, volume, technical signals, risk and reward, portfolio state, and approved buy or sell orders.
Why use it?
It organizes the steps between seeing market information and executing an order, while keeping the final decision with the user.

Skill for Claude CodeCodex

5 3mo ago A scan 14 tokens original Apache-2.0
View the source file OZmasterAI/Torus-Framework
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/ozmasterai/torus-framework/trade
Any agent
npx skills add OZmasterAI/Torus-Framework --skill trade
Clone the repo
git clone --depth 1 https://github.com/OZmasterAI/Torus-Framework

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 559 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.00559
Opus 5 $0.00007 $0.00280
Sonnet 5 $0.00003 $0.00112
Haiku 4.5 $0.00001 $0.00056

Measured 2d ago against content hash 331824324bc3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

trade scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

dormant/skills/trade/SKILL.md · 54 lines

What it actually says

/trade — Trading Workflow

You are the trading brain. Analyze data, form a thesis, run gates, and execute trades with user confirmation.

Workflow

  1. Memory check: search_knowledge("trading <symbol>") for prior trades and insights on this symbol.

  2. Gather state: Run these in parallel:

    ~/projects/trading-claude/.venv/bin/python3 ~/projects/trading-claude/scripts/fetch_data.py --symbol <SYMBOL> --limit 30
~/projects/trading-claude/.venv/bin/python3 ~/projects/trading-claude/scripts/portfolio.py --format json

  3. Analyze: You ARE the analyst. Review candle data, identify:

    • Trend direction and strength
    • Support/resistance levels
    • Volume patterns
    • Key technical signals
    • Risk/reward ratio

  4. Decision: If recommending a trade, state your thesis clearly, then run gates:

    ~/projects/trading-claude/.venv/bin/python3 ~/projects/trading-claude/scripts/check_gates.py --symbol <SYMBOL> --side <BUY|SELL> --quantity <QTY> --thesis "<your thesis>"

  5. Present to user: Show gate results and your thesis. Ask for explicit confirmation before executing.

  6. Execute (only after user confirms):

    ~/projects/trading-claude/.venv/bin/python3 ~/projects/trading-claude/scripts/execute_order.py --symbol <SYMBOL> --side <BUY|SELL> --quantity <QTY> --thesis "<thesis>" --skip-gates

    Use --skip-gates because gates were already checked in step 4.

  7. Show result: Run portfolio.py --format text to show updated portfolio state.

  8. Save to memory: remember_this() with trade details, thesis, outcome. Tags: type:trade,area:trading,ticker:<SYMBOL>

Rules

  • NEVER execute a trade without explicit user confirmation
  • ALWAYS run gates before proposing a trade
  • ALWAYS provide a thesis with your recommendation
  • ALWAYS show gate results to the user
  • Paper mode by default — warn if connector is not "paper"
  • If all gates fail, explain why and suggest adjustments
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 54 lines · 14 tokens per session scan A 331824324bc3

Subscribe to this mod's changes

trade is a skill published in the GitHub repository OZmasterAI/Torus-Framework (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 14 tokens to every session and 559 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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