commercial-skills

Routes commercial inquiries to seven sub-skills covering pricing, deal desk, partnerships, and forecasting.

25.3k|3.6k|Updated Oct 19, 2025
One-click install
npx skills add https://github.com/alirezarezvani/claude-skills --skill commercial-skills
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: commercial-skills
Source: https://github.com/alirezarezvani/claude-skills/tree/main/commercial/skills/commercial-skills
Command: npx skills add https://github.com/alirezarezvani/claude-skills --skill commercial-skills

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Commercial teams face recurring decisions about pricing models, discount approvals, partner economics, RFP responses, and bookings forecasts, but lack a structured way to route each question to the right analytical framework with consistent, canon-anchored reasoning.

Core Features & Use Cases

  • Deterministic routing: A keyword signal table classifies inquiries into seven lanes (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and forks context to the matching sub-skill.
  • Grill-with-docs workflow: Explores the workspace first, asks one forcing question per turn with a recommended answer, and walks multi-lane decisions depth-first before invoking any sub-skill.
  • Digest output with canon citations: Returns a digest of top findings, next actions with named approvers, artifact paths, and one challenge anchored to SaaS pricing and deal-desk references.
  • Use Case: A sales lead asks whether to approve a 40% discount on an Enterprise deal; the skill routes to deal-desk, produces a deal scorecard and discount approval routing JSON, and flags margin benchmarks for human review.

Quick Start

Ask the commercial skill to review this deal and recommend whether the proposed discount should be approved.

Frequently Asked Questions about commercial-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I decide whether to approve a discount on a SaaS deal?

The deal-desk sub-skill generates a deal scorecard and discount approval routing JSON that scores margin at full discount and routes exceptions above policy thresholds to a named human approver. It never auto-approves; every output is a score plus recommendation.

How does the skill route a commercial question to the right sub-skill?

A deterministic signal table maps keywords like pricing, discount, partner, RFP, or forecast to one of seven sub-skills. Single-signal inquiries route directly, ambiguous ones trigger one clarifying question with a recommended lane, and multi-lane cases are walked depth-first.

What artifacts does the commercial skill produce?

Each sub-skill writes a Markdown analysis plus a structured JSON file, such as pricing_model.md with wtp_analysis.json, deal_scorecard.md with discount_approval_routing.json, or forecast.md with pipeline_math.json.

Can the skill respond to an RFP automatically?

The rfp-responder sub-skill drafts an rfp_response.md plus a winrate_estimate.json, but it requires proof points the user can verify. It does not fabricate claims and keeps heavy RFP documents in the forked context.

What are the limitations of this commercial orchestrator?

It is not a CRM, CPQ system, or contract repository, and it does not store deal history across sessions. It recommends price ranges and models rather than specific prices, and all approvals remain with humans.

How is this different from a CRO advisor or sales engineering skill?

This skill handles tactical per-deal economics like discount approval and pricing models, while cro-advisor covers strategic judgment and sales-engineer covers demos and POCs. The SKILL.md explicitly documents these boundaries to avoid overlap.