Installs just this skill. Get the whole plugin for auto-invocation.
โก How it fires
How this skill gets triggered: by you, by Claude, or both.
Fires itselfClaude auto-loads it when your prompt matches the work.
You can call itInvoke it directly when you want it.
Slash command/commercial-skills
๐๏ธ Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when reviewing, approving, or designing commercial motion โ pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on "review this deal", "should we discount", "pricing model",
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Stars23,062
Forks3,139
LanguagePython
LicenseMIT
๐ฆ Ships with claude-skills
</> SKILL.md
commercial-skills.SKILL.md
---name: commercial-skills
description: Use when reviewing, approving, or designing commercial motion โ pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on "review this deal", "should we discount", "pricing model", "partner economics", "RFP response", "bookings forecast", "channel mix". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth (sales execution) and c-level-advisor/cro-advisor (strategic CRO judgment).
context: fork
version: 2.8.0
author: claude-code-skills
license: MIT
tags: [commercial, pricing, deal-desk, partnerships, channel, rfp, forecast, cro, orchestrator]
compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---# Commercial โ Domain Orchestrator
The Commercial surface is **per-deal economics and packaging**: how the company prices, packages, approves, and forecasts revenue. This orchestrator forks its context, routes your inquiry to one of seven sub-skills, then returns a digest. Heavy intake (RFP PDFs, pipeline exports, partner agreements) stays in the forked context.
## When to invoke
| Symptom | Sub-skill |
|---|---|
| "What should our standard discount matrix look like?" | `commercial-policy` |
| "Help me respond to this 60-page RFP" | `rfp-responder` |
| "What's our Q4 bookings forecast at current conversion?" | `commercial-forecaster` |
## Routing logic (deterministic)
Same two-signal threshold pattern as `business-operations-skills`. Single-signal โ clarifying question. Mixed signals โ highest-confidence first, chain second in follow-up turn.
### Signal table
| Signal class | Keywords | Sub-skill |
|---|---|---|
| **PRICING** | pricing, price, packaging, tier, WTP, willingness to pay, Van Westendorp, value pricing | `pricing-strategist` |
Derived from Matt Pocock's `grill-with-docs` pattern: **explore-then-ask, one question per turn with a recommended answer, walk the decision tree depth-first, track dependencies, anchor every challenge in the SaaS pricing / deal desk canon** (`references/`).
### Step 1 โ Explore before asking
Check the user's working directory first:
- Is there a deal record, pricing comp table, RFP doc, or pipeline export already in the workspace?
- Does the inquiry already disambiguate the lane (e.g., "review this 60-page RFP" โ that's `rfp-responder`, no question needed)?
- Is there an artifact filename that resolves the lane (`pipeline-Q4.csv` โ forecast; `MSA-redline.docx` โ deal)?
If the workspace resolves the lane, **route silently**.
### Step 2 โ If still ambiguous, ONE forcing question with a recommended answer
Matt's rule: never bundle. Always recommend.
Pattern:
```
Q1/1: [precise question naming the two candidate lanes]
Recommended: [Lane X, because <signal-table rationale>]
(Confirm, or override?)
```
### Step 3 โ Decision-tree walk for multi-lane inquiries
If the inquiry legitimately crosses two lanes (e.g., "this RFP wants a discount we don't normally give" = RFP + DEAL + maybe POLICY), walk depth-first:
1. Highest-confidence lane first โ run sub-skill in forked context โ digest
2. Ask: "Now run [second lane]? Recommended: yes, because [dependency]."
### Step 5 โ Return digest with cited canon challenge
โค 200 words: analyzed, top 3 findings (anchored to canon citation), top 3 next actions (named approver where applicable), artifact path, and **one grill challenge** for the user. Examples:
- "Your deal scorecard shows 38% margin after discount. Skok's For Entrepreneurs benchmark says SaaS deals < 70% gross margin pre-discount need scrutiny. Did you model fulfillment cost or just COGS?"
- "Your packaging has 14 features in Better and 16 in Best. Madhavan Ramanujam (Monetizing Innovation): tiers with no clear differentiator make 70% of customers pick the cheapest. What's the one feature that forces an upgrade?"
Grill the user on lane-defining decisions before invoking the sub-skill. One per turn, recommended answer, canon citation:
- **PRICING lane**: "Before picking a model: is your customer paying for outcomes, seats, or usage? Recommended: outcomes (value-based) if you can measure them. Anti-pattern (Ramanujam 2016 *Monetizing Innovation*): seat-based pricing on a usage-variable product caps your TAM at 20% of WTP."
- **DEAL lane**: "Before approving: what's the gross margin at full discount, **and** what does next quarter's pipeline look like at the same terms? Recommended: model both. Anti-pattern (Tunguz benchmarks): one 40% precedent reshapes 3 quarters of pipeline."
- **FORECAST lane**: "Before forecasting: are you using stage-conversion rates from the last 4 quarters, or the last 12? Recommended: last 4 weighted heavier. Anti-pattern (Skok, OpenView): equal-weighting 12 months hides the recent slowdown."
- **PARTNERSHIP lane**: "Before signing: does the partner have **independent demand**, or are they reselling our pipeline? Recommended: insist on indep demand evidence. Anti-pattern (Forrester channel research): channel-led deals from your own pipeline cost more than direct."
Never run a sub-skill until the lane-defining decision is locked.
## Assumptions
1. User has commercial authority OR is preparing analysis for someone who does.
2. User wants **deterministic decision support**, not the final answer โ the human approves the deal, sets the price, signs the partner.
3. Inputs may be partial โ every sub-skill ships templated dummy data so the user can see the shape before filling in their own.
## Non-goals
- Not a CRM, CPQ system, or contract repository.
- Does not auto-approve deals. Every output is **a score + recommendation + human-approver routing**.
- Does not store deal history across sessions.
## Distinct from
- **`business-growth/sales-engineer`** โ that's the **technical sale** (demos, POCs). Commercial is **economic shape** of the deal.