> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sxth.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Sales Adapter

> Pipeline tracking and outreach pattern detection

# Sales Adapter

The Sales adapter models a sales rep working deals through a pipeline.

## Installation

```python theme={null}
from sxth_mind import Mind
from sxth_mind.adapters import SalesAdapter

mind = Mind(adapter=SalesAdapter())
```

## Identity Types

| Type         | Description          | Traits                            |
| ------------ | -------------------- | --------------------------------- |
| `hunter`     | New logo acquisition | Aggressive outreach, cold calling |
| `farmer`     | Account growth       | Relationship building, retention  |
| `consultant` | Solution selling     | Discovery, advisory               |
| `closer`     | Deal mechanics       | Negotiation, urgency              |

## Journey Stages

```
prospecting → qualifying → presenting → negotiating → closing
                                                    ↘ nurturing
```

| Stage         | Tone      | Focus                          |
| ------------- | --------- | ------------------------------ |
| `prospecting` | Energetic | Outreach, research             |
| `qualifying`  | Curious   | Discovery, decision makers     |
| `presenting`  | Confident | Demos, value prop              |
| `negotiating` | Strategic | Pricing, terms                 |
| `closing`     | Decisive  | Signatures, commitment         |
| `nurturing`   | Patient   | Long-term, staying top of mind |

## Pattern Detection

The Sales adapter detects:

* **Follow-up frequency** — How often the rep follows up
* **Outreach themes** — Email vs. phone vs. meeting
* **Objection patterns** — Common pushback topics
* **Deal velocity** — How fast deals move through stages

## Nudge Templates

| Nudge                | Priority | Trigger                    |
| -------------------- | -------- | -------------------------- |
| `stalled_deal`       | 7        | No activity for 7+ days    |
| `follow_up_reminder` | 6        | Mentioned follow-up intent |
| `momentum_drop`      | 8        | Activity decreased         |
| `pattern_detected`   | 5        | Recurring pattern noticed  |

## Example Usage

```python theme={null}
import asyncio
from sxth_mind import Mind
from sxth_mind.adapters import SalesAdapter

async def main():
    mind = Mind(adapter=SalesAdapter())

    # Working a deal
    await mind.chat("rep_1", "Just had a great call with Acme Corp", project_id="deal_acme")
    await mind.chat("rep_1", "Sent them a proposal yesterday", project_id="deal_acme")
    await mind.chat("rep_1", "No response yet, should I follow up?", project_id="deal_acme")

    # Check state
    state = await mind.get_state("rep_1", project_id="deal_acme")
    print(f"Stage: {state['project_mind']['journey_stage']}")
    print(f"Patterns: {state['user_mind']['patterns']}")

asyncio.run(main())
```

## System Prompt

The adapter builds context-aware prompts:

```
You are a Sales AI assistant helping a sales rep work their deals.

## Your Role
You help with deal strategy, outreach, objection handling, and pipeline management.

## Current Deal Stage: Qualifying
Tone: curious
Focus: Ask probing questions to help them qualify effectively.

## Patterns & History
Follow-up pattern: high
Common themes: pricing, timeline
Total interactions: 15
Deal interactions: 8
```