/cs-commercial-policy¶
Run the commercial-policy skill on this input:
$ARGUMENTS
Three-tool workflow¶
-
discount_matrix_builder.py— Data-backed discount bands (by ARR band × term length × payment terms × strategic value). Outputs the matrix + the approver tier per cell. Industry tuning--profile {saas,enterprise-software,api,marketplace,services}. -
exception_router.py— Exception flow: when a deal asks for terms outside the matrix, who approves and what compensating commitments are required (multi-year + prepay + named expansion path). -
policy_linter.py— Consistency check across the matrix: no contradictions (e.g., "Manager approves up to 25%" but "VP approves up to 20%"), no gaps (deal band with no defined approver), no obvious gaming surface (cliff at 99 ARR vs 100 ARR).
Hard rule¶
No discount band without data backing. Pull win-rate and NRR by current band before recommending changes.
Distinct from¶
- Sibling
commercial/skills/deal-desk— applies the policy to individual deals. Commercial-policy designs the policy. - Sibling
commercial/skills/pricing-strategist— sets the pricing model + tier list price. Commercial-policy governs discounts off list. c-level-advisor/cro-advisor— strategicc-level-advisor/cfo-advisor— financial guardrails (margin floor); commercial-policy operationalizes those