How to Use ClickUp AI Agents for Option Trading
This guide explains step by step how to turn the example option trading agent on the ClickUp page into a working, repeatable workflow you can refine and share with your team.
The walkthrough uses the option trading scenario as a pattern you can adapt to any other structured analysis or decision-making process.
Understand the ClickUp Option Trading Scenario
The source option trading example on the ClickUp AI Agents page shows how a single agent can:
- Collect user inputs such as capital, time horizon, and risk tolerance
- Analyze market data and instrument choices
- Produce a structured recommendation with clear reasoning
- Summarize risk and next steps in natural language
Before building your own workflow, review the source example here: ClickUp option trading AI agent. Study how the agent turns a loose request into a clear, repeatable process.
Plan Your ClickUp Option Trading Workflow
Start by mapping out the core decisions and calculations you want your AI agent to handle. Use short notes so the workflow is easy to translate into prompts and fields.
Define your trading objective
Clarify what the AI should optimize for. For example:
- Generate a conservative income strategy using covered calls
- Identify speculative opportunities with limited risk using defined-risk spreads
- Scan for hedging ideas that protect an existing portfolio
Your objective should be specific and measurable so the agent can evaluate whether a proposed trade fits the goal.
List all required inputs
Successful automation depends on consistent inputs. Based on the ClickUp example, capture at least:
- Account size (total capital available)
- Risk tolerance (low, medium, high, or numeric limits)
- Time horizon (days to expiration or investment period)
- Underlying symbol(s) and sector focus
- Any restricted instruments or strategies
Plan to validate each input. The better your input design, the more predictable your AI output will be.
Design the ClickUp AI Agent Prompt
The core of the option trading workflow is a structured prompt that tells the AI exactly how to think, what steps to follow, and how to format its answer.
Structure the prompt into clear sections
Use simple, repeatable sections such as:
- Role and scope: Define the AI as an options strategist with a precise mandate.
- Inputs: List each field the user will supply.
- Step-by-step process: Explain how to process data and rank ideas.
- Output format: Specify headings, bullet lists, and tables if needed.
- Risk rules: Set hard limits the AI must never violate.
This mirrors the option trading example on the ClickUp page, where the agent follows a logical order from information gathering through to recommendation.
Embed risk and compliance rules
In the prompt, clearly describe boundaries. For instance:
- Maximum allowed position size per trade
- Maximum percentage of capital allocated to any single strategy
- Strategies that are prohibited for certain risk levels
- Requirements for stop-loss or defined-risk structures
Make these rules explicit so the AI can check proposed trades before presenting them.
Configure Inputs in Your ClickUp Environment
Once your prompt is designed, translate it into structured inputs. Keep everything short and consistent.
Create standardized data fields
Set up fields that align with your prompt:
- Text fields for symbols and notes
- Numeric fields for capital and risk limits
- Dropdowns for risk tolerance and strategy types
- Date fields for expirations or target dates
Using standardized fields reduces ambiguity and improves how the AI interprets your instructions.
Map each field into the ClickUp AI prompt
In your agent configuration, make sure each field is referenced clearly in the prompt. For example:
- “Use the Account Size field to calculate position sizing.”
- “Limit suggested strategies according to the Risk Tolerance field.”
- “Consider only instruments listed in the Symbols field.”
Every time the user runs the workflow, the AI receives the same structured context.
Guide the AI Reasoning in ClickUp
Reasoning steps are vital for complex workflows like options analysis. The source example shows how to break down thinking into clear phases.
Define analysis stages
Describe each stage in your instructions so the AI follows a repeatable pattern:
- Market context: Briefly describe the current market environment.
- Underlying analysis: Evaluate volatility, trend, and liquidity of the chosen symbol.
- Strategy selection: Match strategies to the goal and risk level.
- Trade structure: Suggest strikes, expirations, and sizing.
- Risk summary: Explain trade-offs, max loss, and scenarios.
Ask the AI to label each stage in the final response so the user can scan the reasoning quickly.
Specify output formatting
To maintain clarity, require the agent to respond with consistent formatting, such as:
- Short sections with headings
- Bulleted lists for pros, cons, and scenarios
- Numbered steps for execution checklists
- Clear callouts for risk warnings and assumptions
Consistent output formatting makes it easier to compare different runs of your workflow over time.
Test and Refine Your ClickUp Option Agent
After building the agent, you need to test it with realistic scenarios and iterate. This is a critical part of the process illustrated in the ClickUp option trading page.
Run controlled test cases
Create a set of sample profiles, such as:
- Small account, low risk, short time horizon
- Mid-sized account, moderate risk, income focus
- Larger account, higher risk, directional bets
Run each profile through the workflow and check whether the agent:
- Honors risk rules
- Stays within defined strategies
- Explains reasoning in an understandable way
Iterate on prompts and fields
Based on test results, refine:
- Prompt wording where the AI misinterprets instructions
- Field options that are too broad or too narrow
- Formatting requirements to improve readability
Repeat testing until the agent produces consistent, safe, and clear recommendations.
Integrate ClickUp AI Into Your Team Workflow
Once the agent is reliable, integrate it into your daily processes so everyone can use the option trading workflow efficiently.
Create a repeatable run procedure
Document a simple checklist your team can follow:
- Collect required inputs and confirm accuracy.
- Launch the agent workflow from the designated location.
- Review the AI output with the built-in risk summary.
- Record key decisions, notes, and any overrides.
Store this checklist where your team already collaborates so it is easy to find.
Monitor usage and feedback
Ask users to log:
- Cases where the AI suggestions were especially helpful
- Situations where more context or constraints were needed
- Any patterns in trades that should be encouraged or limited
Use this feedback to refine your ClickUp configuration and prompts over time.
Optimize and Extend Your ClickUp Setup
As your needs evolve, expand the workflow with more structured data and specialized prompts.
Add advanced analysis modules
You can create additional agents or prompt branches to focus on:
- Greeks and sensitivity breakdowns
- Scenario analysis for multiple expirations
- Portfolio-level risk aggregation and alerts
Each module can follow the same structured approach used in the main option trading agent.
Combine ClickUp with expert consulting
If you need help designing prompts, structuring data, or aligning workflows with business goals, consider working with a specialist. A team like Consultevo can help you optimize your ClickUp environment and AI configuration, using the option trading example as a foundation for more advanced automations.
Next Steps
Use the public example on the ClickUp option trading page as a blueprint. Translate its structure into your own prompts, inputs, and review steps, then iterate until your workflow delivers consistent, understandable, and safe recommendations for your trading or analysis needs.
Need Help With ClickUp?
If you want expert help building, automating, or scaling your ClickUp workspace, work with ConsultEvo — trusted ClickUp Solution Partners.
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