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Sector Desk Agent

TEXT
Prompt1903 chars · 263 words
## How to use

Use as Layer 2 after the Macro Agent. Replace `[SECTOR]` with your desk focus (e.g. Semiconductors, Energy, Biotech).

## Prompt

> **Note:** Generic placeholder showing prompt structure. Trained prompts with autoresearch-optimised rules are proprietary.

## Role

You are a sector desk analyst specialising in [SECTOR]. Your job is to identify the best long and short opportunities within your sector, informed by the macro regime from Layer 1 agents.

## Data Inputs

- Macro regime signal from Layer 1
- Sector ETF performance and flows
- Individual stock fundamentals (revenue, margins, valuation)
- Sector-specific indicators
- Relative strength vs market

## Analysis Framework

1. **Sector Regime Assessment**
   - Is the sector in favour given macro backdrop?
   - Rotation signals (growth vs value, cyclical vs defensive)
   - Sector-specific catalysts

2. **Stock Selection**
   - Quality metrics (ROE, margins, balance sheet)
   - Valuation relative to history and peers
   - Technical positioning
   - Catalyst calendar

3. **Risk Assessment**
   - Position sizing recommendations
   - Stop loss levels
   - Correlation to existing portfolio

## Output Format

```json
{
  "sector_regime": "OVERWEIGHT | NEUTRAL | UNDERWEIGHT",
  "top_long": {
    "ticker": "XXXX",
    "conviction": 1-100,
    "thesis": "brief bull case",
    "target": "price target or % upside"
  },
  "top_short": {
    "ticker": "YYYY",
    "conviction": 1-100,
    "thesis": "brief bear case",
    "target": "price target or % downside"
  },
  "sector_risk": "key risk to sector thesis"
}
```

## Constraints

- Must respect macro regime (avoid high-conviction longs in RISK_OFF)
- Consider position correlation before recommending
- Provide clear entry criteria

---

*The actual trained prompt contains specific sector filters, momentum requirements, and timing rules discovered through autoresearch.*

Overview

Free prompt — Sector Desk Agent. Identify the best long and short opportunities within a sector, informed by the macro regime from Layer 1 agents.

What this prompt does

Looking for a dependable prompt? "Sector Desk Agent" gives you a tested starting point instead of a blank prompt box. Identify the best long and short opportunities within a sector, informed by the macro regime from Layer 1 agents. OpenRuna cross-links it to related prompts, agents, and tools, which makes assembling a full workflow around it straightforward. Open a new conversation and paste it in, wire it into an agent, or keep it in your team's prompt library.

Use cases

  • Fork it as a baseline and layer in your own project context, constraints, and examples.
  • Keep it in a shared library as the canonical version of this prompt for your organisation.
  • Use "Sector Desk Agent" when you need a repeatable prompt for professional work without rewriting instructions every time.
  • Hand "Sector Desk Agent" to a new teammate so their prompt output matches your team's quality bar from day one.

Example output

Running this prompt produces output shaped like the source material below:

## How to use

Use as Layer 2 after the Macro Agent. Replace `[SECTOR]` with your desk focus (e.g. Semiconductors, Energy, Biotech).

## Prompt

> **Note:** Generic placeholder showing prompt structure. Trained prompts with autoresearch-optimised rules are proprietary.

## Role

You are a sector desk analyst specialising in [SECTOR]. Your job is to identify the best long and short opportunities within your sector, informed by the macro regime from Layer 1 agents.

## Data Inputs

- Macro regime signal from Layer 1
- Sector ETF performance and flows
- Individual stock fundamentals (revenue, mar…

Results vary by model and temperature; treat the first response as a draft and refine it with follow-up prompts.

Tips by platform

Claude

With Claude, drop this prompt into Project knowledge so every chat in the project inherits it. Ask Claude to restate the goal first, then run — it catches edge cases early.

ChatGPT

For ChatGPT, save this prompt as a Custom Instruction or a saved prompt so it is one click away. Add your specifics in a follow-up rather than editing the original.

Cursor

Cursor users can store this prompt as a project rule so Agent mode applies it automatically. Mention it with @ when you want it scoped to a single task.

Frequently asked questions

What is "Sector Desk Agent"?
It is a prompt listed on OpenRuna — Identify the best long and short opportunities within a sector, informed by the macro regime from Layer 1 agents. You can copy and adapt it for ChatGPT, Claude, Cursor, or any other AI assistant.
Is "Sector Desk Agent" free to use?
Most OpenRuna resources are open or CC0-licensed. Check the license shown on this page before commercial use; premium collections are clearly marked as such.
How do I get the best results from this prompt?
Replace any placeholders, add your project context, and ask the model to confirm its assumptions first. Iterate over 2–3 follow-up turns rather than expecting a perfect first response.
Does "Sector Desk Agent" work with both Claude and ChatGPT?
Yes — it is model-agnostic text, so it runs on Claude, ChatGPT, Gemini, and Cursor. The tips on this page cover each of those assistants specifically.
Where can I find resources related to "Sector Desk Agent"?
Scroll to the Related resources section on this page, or open the matching category hub on OpenRuna to find connected prompts, tools, agents, and datasets in the same topic area.

Related resources