portfolio-distribution

Name: portfolio-distribution
Author: Drakkar-Software

AI Community

Repo stars 6,018
Author updated Live
Author repo OctoBot

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: AI
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 88 / 100 · community maintained
Author / version / license: @Drakkar-Software · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Not required
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: No special requirements
Permissions: Read-only
Shell exec
Write / modify
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview portfolio-distribution.preview

---
name: portfolio-distribution
description: Use this skill for making final portfolio allocation decisions, determining optimal position siz…
category: ai
runtime: no special runtime
---

# portfolio-distribution output preview

## PART A: Task fit
- Use case: Use this skill for making final portfolio allocation decisions, determining optimal position sizing, and providing actionable trading recommendations based on risk assessments. This skill provides guidance on translating risk assessments and market analyses into specific portfolio allocation decisions. Your role is to determine optimal position sizes whil….
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Overview / Instructions / 1. Position Sizing Framework” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Use this skill for making final portfolio allocation decisions, determining optimal position sizing, and providing actionable trading recommendations based on risk assessments. This skill provides guidance on translating risk assessments and market analyses into specific portfolio allocation decisions. Your role is to determine optimal position sizes whil…”.
- **02** When the source has headings, the agent prioritizes “Overview / Instructions / 1. Position Sizing Framework” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: portfolio-distribution
description: Use this skill for making final portfolio allocation decisions, determining optimal position siz…
category: ai
source: Drakkar-Software/OctoBot
---

# portfolio-distribution

## When to use
- Use this skill for making final portfolio allocation decisions, determining optimal position sizing, and providing act…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “Overview / Instructions / 1. Position Sizing Framework” and keep inference separate from source facts.
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "portfolio-distribution" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> Overview / Instructions / 1. Position Sizing Framework
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> no special runtime | read files, run shell commands, write/modify files | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Use this skill for making final portfolio allocation decisions, determining optimal position sizing, and providing actionable tr…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Overview”, “Instructions”, “1. Position Sizing Framework”, “2. Portfolio Risk Management”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name portfolio-distribution directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Overview / Instructions / 1. Position Sizing Framework” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / shell-exec / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

portfolio-distribution

Overview

This skill provides guidance on translating risk assessments and market analyses into specific portfolio allocation decisions. Your role is to determine optimal position sizes while respecting risk management constraints.

Instructions

1. Position Sizing Framework

Base Position Size Calculation

Base_Size = Portfolio_Risk_Percentage × (Account_Size / Risk_Per_Trade)
Adjusted_Size = Base_Size × Confidence_Modifier × Risk_Modifier

Confidence Modifiers

Very high confidence (>0.85): 1.5x
High confidence (0.70-0.85): 1.0x
Medium confidence (0.50-0.70): 0.75x
Low confidence (<0.50): 0.25x or skip

Risk Modifiers (from Risk Judge)

Low overall risk: 1.2x
Medium overall risk: 1.0x
High overall risk: 0.5x

2. Portfolio Risk Management

Total Exposure Limits

Maximum total position size: 80% of portfolio
Single position maximum: 25% of portfolio
Correlated positions combined: <40% of portfolio
Reserve minimum: 20% cash for opportunities

Diversification Rules

Don't concentrate >40% in one sector
Consider correlation between positions
Balance long and short exposure when appropriate
Maintain liquidity for rebalancing

3. Action Determination

Buy Actions

Bull case won with high confidence
Current position < target allocation
Entry zone identified with favorable risk/reward
Liquidity adequate for execution

Sell Actions

Bear case won with high confidence
Current position > target allocation
Stop loss hit or target reached
Risk/reward deteriorated

Hold Actions

Unclear winner or low confidence
Current allocation within target range
Waiting for better entry/exit
Preserving capital for better opportunities

4. Execution Planning

Priority Ordering

Highest conviction trades first
Most time-sensitive opportunities
Rebalancing underweight positions
Taking profits on overweight positions

Timing Recommendations

Immediate: High confidence, favorable conditions
Limit Order: Medium confidence, specific entry target
Wait: Low confidence or better setup expected
Scale In/Out: Uncertainty about timing, reduce entry/exit risk

5. Trade Structuring

Entry Strategy

Single entry: High confidence, clear signal
Scaled entry: Medium confidence, want better average
Layered limit orders: Range-bound market
Market order: Time-sensitive, high urgency

Exit Strategy

Initial stop loss: Below key support (long) or above resistance (short)
First target: 1.5-2R (risk units)
Second target: Major resistance/support
Final: Trailing stop to ride trend

Output Format

{
  "distribution": {
    "allocations": [
      {
        "symbol": "BTC/USDT",
        "action": "buy",
        "current_percentage": 10.0,
        "target_percentage": 18.0,
        "quantity_change": 0.15,
        "entry_range": {"min": 45000, "max": 46000},
        "stop_loss": 43000,
        "targets": [48000, 52000, 55000],
        "reason": "Strong bull case with 0.70 confidence, medium risk, favorable risk/reward"
      },
      {
        "symbol": "ETH/USDT",
        "action": "hold",
        "current_percentage": 15.0,
        "target_percentage": 15.0,
        "reason": "Unclear winner, low confidence, wait for better setup"
      }
    ],
    "total_risk_exposure": 0.65,
    "cash_reserve": 0.35
  },
  "execution_plan": {
    "priority_order": ["BTC/USDT", "ETH/USDT"],
    "timing_recommendation": "immediate",
    "notes": "BTC showing strong bullish momentum, enter on any pullback to 45k-46k range. Set stops below 43k. Scale out at targets."
  },
  "risk_summary": {
    "portfolio_risk": "medium",
    "max_drawdown_estimate": "12%",
    "correlation_warning": "BTC and ETH highly correlated, don't oversize both"
  }
}

Best Practices

Never overleverage - Respect maximum position sizes
Always define stops - Know your exit before entry
Scale positions by conviction - Higher confidence = larger size
Consider correlation - Don't concentrate risk
Maintain reserves - Keep cash for opportunities
Document decisions - Save to /memories/distributions/ for review
Review regularly - Rebalance as conditions change
Risk first, returns second - Preserve capital above all

Common Mistakes to Avoid

Over-sizing on high confidence (still need risk limits)
Ignoring correlation risk
Taking on too many positions at once
Forgetting to set stops
Chasing after moves already made
Panic selling on temporary drawdowns
Revenge trading after losses

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add Drakkar-Software/OctoBot/packages/tentacles/Trading/Mode/ai_trading_mode/resources/skills/distribution_agent -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

88 / 100

Community

未声明 license/许可。
未声明 version。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
Drakkar-Software/OctoBot
中文

More by @Drakkar-Software

A trading-strategy 88

Category & tags

Category AI

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

portfolio-distribution

Overview

Instructions

1. Position Sizing Framework

2. Portfolio Risk Management

3. Action Determination

4. Execution Planning

5. Trade Structuring

Output Format

Best Practices

Common Mistakes to Avoid

Discussion