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Documentation Index

Fetch the complete documentation index at: https://docs.getcargo.ai/llms.txt

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The instructions (also called the “prompt”) tell your Agent who it is, what it should do, and what it should avoid. A well-crafted prompt is the difference between an Agent that delivers consistent, high-quality results and one that produces unpredictable outputs.

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The three components

Every Agent prompt consists of three sections:

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1. Role / Purpose

Defines who the Agent is and what it’s trying to achieve. This sets the primary context for the LLM.
Keep this concise and focused on the end goal. One or two sentences is ideal.
Example: 
You are a lead qualification specialist for Cargo. Your job is to evaluate
LinkedIn company URLs and determine if they match our Ideal Customer Profile.

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2. Behavior

Outlines how the Agent should work—the steps it takes, actions it uses, and the format of its output. This directly guides the Agent’s planning phase. Example: 
1. Use the "Company-Lookup" action to retrieve company data from the URL
2. Check the company against our ICP criteria in the Knowledge Base
3. Assign a qualification score: "High Fit", "Medium Fit", or "No Fit"
4. Provide a 2-3 sentence explanation of your reasoning
Action selection tip: Give each action a specific name and clear description. The Agent uses these to decide which action to call and when.

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3. Avoidances

Establishes what the Agent must NOT do. These guardrails prevent undesired actions and ensure compliance. Example: 
- Never share proprietary ICP criteria with external parties
- Do not make up information if a lookup fails—report the failure instead
- Avoid overly casual language; maintain a professional tone
Avoidances are critical for security, compliance, and maintaining trust. Be explicit about sensitive data handling and edge cases.

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Best practices

PracticeWhy it matters
Be specificVague instructions lead to inconsistent results. Say “assign a score of 1-10” instead of “rate the lead”
Define output formatSpecify exactly what the Agent should return (JSON, bullet points, a score, etc.)
List actions by nameReference the exact action names so the Agent knows what’s available
Handle edge casesTell the Agent what to do when data is missing or an action fails
Test iterativelyRun test queries and refine the prompt based on actual outputs

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Example: Complete prompt

Here’s a full prompt for a lead qualification Agent: 
ROLE:
You are a lead qualification specialist for Cargo. Evaluate inbound leads
and determine their fit based on our ICP criteria.

BEHAVIOR:
1. Extract the company domain from the lead's email address
2. Use "Enrichment-Action" to gather company data (size, industry, funding)
3. Query the "ICP-Guidelines" resource to retrieve qualification criteria
4. Score the lead as "High", "Medium", or "Low" fit
5. Return a JSON object with: score, reasoning, and recommended next step

AVOIDANCES:
- Do not qualify leads from personal email domains (gmail, yahoo, etc.)
- Never fabricate company data—if enrichment fails, mark as "Needs Review"
- Do not recommend sales outreach for "Low" fit leads