offer

name: offer description: Generate commercial proposals with pricing packages, benefits, risks, and timeline. Use /offer to create sales proposals for IT projects. allowed-tools: Read, Write, WebSearch

Generate commercial proposals for IT projects. The skill provides a framework — the model thinks about specifics (team, benefits, risks) for each unique project.

Output

File: docs/offers/{project-slug}.md

Example: docs/offers/treejar-ai-sales-bot.md

When to Use

Creating commercial proposals for client projects
Generating estimates for any IT project (web, mobile, AI, integrations, etc.)
Building multi-package pricing structures
Documenting project scope with timeline

Core Principle

DO NOT use rigid templates. Each project is unique. The model should:

Analyze the project requirements
Think about what team composition fits THIS project
Generate benefits relevant to THIS client's business
Identify risks specific to THIS tech stack and integrations

Instructions

Step 1: Understand the Project

Gather from user:

Project name and description
Target audience / client business
Key features and integrations
Budget constraints (if any)

Step 2: Design Packages

Create 2-4 pricing packages (e.g., MVP → Business → Enterprise):

Each package builds on the previous
Define modules with hour estimates
Think: what makes sense for THIS project?

Step 3: Calculate Costs

For each package:

Sum module hours
Apply hourly rate (ask user or use default ~1500 ₽/h)
Estimate timeline based on team size

Step 4: Generate Business Benefits

Think fresh for each project. Consider:

What problems does this solve for the client?
What's the ROI / payback potential?
How does each package level add value?
What competitive advantages does it provide?

Write 4-5 compelling benefits per package in business language.

Step 5: Compose the Team

Think about what THIS project needs:

What roles are required? (Backend, Frontend, DevOps, QA, PM, Designer, etc.)
What seniority levels?
How many hours per role?

Don't use a fixed template — a simple API integration doesn't need the same team as a complex AI platform.

Step 6: Identify Risks

Analyze THIS project's specific risks:

What integrations might be problematic?
What are the technical unknowns?
What depends on the client?
What could affect timeline?

Include mitigation strategies for each risk.

Step 7: Add Operating Costs (if applicable)

For projects with ongoing costs (LLM APIs, hosting, SaaS):

Load current pricing from data/llm-models.json
Calculate monthly costs for different usage scenarios
Provide recommendations

Step 8: Create Mermaid Diagrams

Include visual diagrams to make the offer more compelling:

Timeline (Gantt)

gantt
    title Project Timeline
    dateFormat YYYY-MM-DD
    section Phase 1
    Architecture     :a1, 2026-02-10, 1w
    section Phase 2
    Development      :a2, after a1, 3w
    section Phase 3
    Testing & Deploy :a3, after a2, 1w

System Architecture (for complex projects)

flowchart LR
    Client[📱 WhatsApp] --> Bot[🤖 AI Bot]
    Bot --> LLM[🧠 LLM API]
    Bot --> CRM[📊 Zoho CRM]
    Bot --> KB[(📚 Knowledge Base)]

Package Comparison (optional)

graph TD
    A[Старт] --> B[Бизнес]
    B --> C[Премиум]

    A --- A1[Базовые консультации]
    B --- B1[+ Голосовые + КП]
    C --- C1[+ Аналитика + Контроль]

Step 9: Assemble & Save Document

Generate beautiful markdown with sections:

# Коммерческое предложение: {Project Name}

**Дата:** {date}
**Версия:** 1.0

---

## О проекте
{description}

---

## Архитектура решения
{mermaid architecture diagram}

---

## Пакеты услуг

### Пакет "Старт" — {subtitle}
{table with modules and hours}

**Результат:** {what client gets}

**Выгода для бизнеса:**
- **{benefit 1}** — {description}
- **{benefit 2}** — {description}
...

**Стоимость:** {price} ₽
**Срок:** {weeks} недель

---

## Сравнение пакетов
{comparison table with ✓/—}

---

## Команда проекта
{table: Role | Responsibilities | Hours | Rate | Sum}

---

## Timeline
{mermaid gantt diagram}

---

## Ежемесячные расходы (if applicable)
{infrastructure + LLM costs table}

---

## Риски и митигация
{table: Risk | Probability | Impact | Mitigation}

---

## Что не входит
- {exclusion 1}
- {exclusion 2}

---

## Гарантии
- {guarantee 1}
- {guarantee 2}

---

## Следующие шаги
1. {step 1}
2. {step 2}
3. {step 3}

---

*Предложение действительно 14 дней.*

Save to: docs/offers/{project-slug}.md

Reference Data

LLM Models (for AI projects)

Load from data/llm-models.json — contains current OpenRouter pricing for:

DeepSeek V3.2 (recommended for cost efficiency)
Gemini 2.5 Flash
Kimi K2
GPT-4.1 / GPT-4.1-mini
Claude 4 Sonnet
Xiaomi MiMo-V2-Flash

Examples

Example 1: AI Sales Bot

Input: "AI bot for WhatsApp sales automation, furniture store, Arabic/English"

Model thinks:

Team: Architect, Backend (LLM integration), DevOps
Benefits: 24/7 availability, instant responses, multilingual support, CRM integration
Risks: WhatsApp API changes, LLM quality for Arabic, voice message handling
Packages: Basic (text only) → Business (voice + proposals) → Premium (analytics)
Diagrams: Architecture (WhatsApp → Bot → LLM → CRM), Gantt timeline

Saves to: docs/offers/treejar-ai-sales-bot.md

Example 2: E-commerce Platform

Input: "Online store with AI recommendations, 10K products"

Model thinks:

Team: Backend, Frontend, DevOps, QA, Designer
Benefits: Increased average order, personalization, inventory optimization
Risks: Data migration, recommendation quality, performance at scale
Packages: MVP (catalog + cart) → Growth (recommendations) → Enterprise (full analytics)
Diagrams: Architecture (Frontend → API → DB → ML), Package flow

Saves to: docs/offers/ecommerce-ai-recommendations.md

Example 3: Simple API Integration

Input: "Connect CRM with accounting system"

Model thinks:

Team: Backend developer only, maybe part-time QA
Benefits: No manual data entry, real-time sync, error reduction
Risks: API limitations, data format mismatches
Packages: Maybe just one package — it's a simple project
Diagrams: Simple flowchart (CRM ↔ Integration ↔ Accounting)

Saves to: docs/offers/crm-accounting-integration.md

Validation

Project understood correctly
Packages make sense for this project type
Benefits are specific to client's business (not generic)
Team composition fits the project scope
Risks are relevant to the tech stack
Calculations are correct
Mermaid diagrams render correctly
Document saved to docs/offers/
Document is complete and professional

Anti-Patterns

DON'T:

Copy-paste same benefits for every project
Use identical team for all projects
List generic risks that don't apply
Over-engineer simple projects
Under-scope complex projects
Skip diagrams — they add huge value

DO:

Think fresh about each project
Adapt structure to project complexity
Write benefits in client's business language
Be honest about risks and uncertainties
Include relevant Mermaid diagrams
Save the file automatically