/partnerships-architect

name: partnerships-architect
description: "Use when deciding whether to sign a partner, at which tier (referral, reseller, OEM, SI, alliance), with what joint GTM and revshare. Runs partner_tier_classifier.py, revshare_modeler.py and joint_gtm_planner.py."
license: MIT
metadata:
  version: 2.8.0
  author: claude-code-skills
  tags: [commercial, partnerships, channel-partners, joint-gtm, revshare, oem, reseller, strategic-alliance]
  compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]

partnerships-architect

Purpose

Help Head of Partnerships, Head of BD, and Founder-CEOs answer four questions when a prospective partner shows up:

1. **Is this a real partner, or someone hunting preferential terms without independent demand?** 2. **At what tier should we sign them?** (Referral / Reseller / OEM / SI-Consulting / Strategic Alliance) 3. **What's the 90-day joint GTM plan that proves the partnership works?** 4. **What revshare makes economic sense — and at what point does the partnership beat direct sale?**

The skill emits a tier verdict + GTM plan + revshare band with explicit kill criteria. It does **not** sign the deal. The human, after running this skill, decides.

When to use

• A prospective partner has approached and asked for reseller / OEM / "strategic" terms
• You're designing a new partner program tier structure
• You're reviewing an existing partnership that's underperforming and need to decide: re-tier, restructure GTM, or unwind
• A Big Logo wants a "strategic alliance" — and you need to validate it's real, not vendor-lock theatre
• A consulting firm or SI wants services revshare on your product
• A platform vendor offers OEM / white-label and you need to model the math
• You suspect "partner-sourced" deals are actually your own pipeline being skimmed for margin

**Do not use for:**

• Technical demos and POCs → `business-growth/sales-engineer`
• Cost-to-serve and ROI math on existing channel → sibling `channel-economics`
• Whole-company revenue strategy → `c-level-advisor/cro-advisor`
• Acquiring a company instead of partnering → `c-level-advisor/ma-playbook`
• Per-deal discount approval inside a signed partner contract → `deal-desk`

Workflow

Step 1 — Intake (≈ 20 min)

Fill `assets/partnership_intake_template.md`. Capture: partner_name, partner_type, evidence of independent demand (named accounts they've sourced, end-customer relationships, their sales team size), strategic value (geo / product / brand / channel economics), commitments they've offered (joint marketing spend, dedicated headcount, certification, sales targets).

If the intake template can't be honestly filled out, the prospective partner has not demonstrated enough substance to evaluate. Stop. Go back to them.

Step 2 — Tier classify

Run `scripts/partner_tier_classifier.py --input intake.json --profile saas --output markdown`. Output ranks the partner into 1 of 5 tiers — REFERRAL / RESELLER / OEM / SI-CONSULTING / STRATEGIC — with deterministic floors. STRATEGIC requires named_accounts ≥ 5 AND multi-year commit AND dedicated resources. Skill emits rationale + kill criteria.

Step 3 — Joint GTM plan

Run `scripts/joint_gtm_planner.py --input gtm.json --profile saas --output markdown`. Output: 90-day plan with pre-launch milestones (training, certification, materials), launch motion (target accounts, sales play, MDF allocation), mid-quarter checkpoint, and 90-day success criteria. Validates: cannot plan channel-led GTM for REFERRAL tier; cannot plan white-label for non-OEM tier.

Step 4 — Revshare model

Run `scripts/revshare_modeler.py --input revshare.json --output markdown`. Computes margin per deal direct vs. via partner, recommended revshare % band based on partner contribution depth (sourced > influenced > delivered), break-even partner ROI, and long-term economics — at projected scale, does partner economics beat direct?

Step 5 — Decide

Take tier + GTM plan + revshare band into the partnership committee. Skill does not sign the partner — you do. Document kill criteria in the contract so the unwind is mechanical when triggered.

Scripts

• `scripts/partner_tier_classifier.py` — 5-tier classifier with deterministic floors per tier
• `scripts/joint_gtm_planner.py` — 90-day joint GTM plan generator with tier-validated motion
• `scripts/revshare_modeler.py` — revshare band + break-even ROI + long-term economics

All scripts: stdlib only. `--help` and `--sample` work on all three.

Quick example

# Emits a 5-tier partner classification with deterministic floors per tier for the built-in sample partner
cd commercial/skills/partnerships-architect && python3 scripts/partner_tier_classifier.py --sample

References

• `references/channel_partner_canon.md` — Caro on HP indirect channels, Chintagunta on channel economics, Hessling on partner programs, Forrester channel software stack, IDC channel research, Tien Tzuo subscription-channel models, Geoffrey Moore whole-product partnerships
• `references/joint_gtm_canon.md` — Aaron Ross *Predictable Revenue* (cold-source vs partner), Winning by Design, Jay McBain on co-sell, Microsoft Partner Network playbook, AWS Partner Network research, SiriusDecisions partner benchmarks, Bridge Group SaaS partner data
• `references/partnership_anti_patterns.md` — Forrester partner-led-from-your-pipeline research, Tom Tunguz on channel conflict, Hessling failure analyses, MIT Sloan on disproportionate strategic revshare, HP channel post-mortems, IBM channel-conflict cases, Salesforce AppExchange research

Assumptions

• A partner who cannot produce evidence of independent demand (named accounts, end-customer

relationships, their own sales team) is hunting preferential terms, not a partner.

• Industry profiles (`--profile`) tune defaults — they don't override your data.
• Revshare % bands are recommendations; the contract negotiation, MDF policy, and

exclusivity terms are human commerc