skill
ai-ecosystem-partnerships
Partner ecosystem toolkit: score partner fit, tier the portfolio, map account overlap, and attribute co-sell pipeline. Tested Python CLI plus skills for Claude Code and GitHub Copilot. Synthetic data.
Set up
Skills are installed by placing their folder where your agent loads skills.
The download comes from github.com/varunk130/ai-ecosystem-partnerships itself, not from our server, so what you get is exactly what its author published.
Install instructions come from the README
README
synced Oct 26, 2026AI Ecosystem Partnerships
A small, tested toolkit for running a partner ecosystem on evidence instead of anecdote: score partner fit, tier the portfolio, map account overlap, and attribute pipeline to partners. It ships as a dependency-free Python CLI plus six skills for Claude Code and GitHub Copilot, with playbooks for product partnerships, ecosystem leadership, and co-sell.
Created and maintained by Varun Kulkarni
All data in this repository is synthetic.
Contents
How it fits together
flowchart LR
P[partners.csv] --> S[score]
A[our accounts +<br/>partner accounts] --> O[overlap]
D[opportunities.csv] --> T[attribution]
S --> Q[Partner QBR brief]
O --> Q
T --> Q
S --> R[Portfolio review]
O --> C[Co-sell action list]
Quickstart
Requires Python 3.10 or newer. There is nothing to install.
git clone https://github.com/varunk130/ai-ecosystem-partnerships.git
cd ai-ecosystem-partnerships
python -m partner_ecosystem score data/partners.csv
partner type score tier borderline weakest motion
--------------------- -------- ----- --------- ---------- ----------- ----------------------------------------------------
Northwind Data isv 94.6 Strategic icp_fit Joint business plan, exec cadence, dedicated co-sell
Halcyon Cloud cloud 92.2 Strategic icp_fit Joint business plan, exec cadence, dedicated co-sell
Brightline Consulting si 75.8 Strategic yes integration Joint business plan, exec cadence, dedicated co-sell
Kestrel AI isv 59.0 Growth traction Targeted account mapping and co-marketing
...
What it answers
| Question | Command |
|---|---|
| Which partners deserve investment, and what holds each back? | python -m partner_ecosystem score data/partners.csv |
| Which shared accounts should we work with a partner, and how? | python -m partner_ecosystem overlap data/our_accounts.csv data/partner_accounts.csv |
| What did partners source and influence, and do attached deals win more? | python -m partner_ecosystem attribution data/opportunities.csv |
Every command takes --format table|json|csv and --partner NAME. score also takes --weights FILE for custom weights, and overlap takes --opportunities FILE to rank plays by open amount.
Playbooks
How to run partnerships, written as decisions rather than theory.
| Playbook | Covers |
|---|---|
| Product partnerships | Build, buy, or partner; integration depth; scope; commercial models |
| Leading a partner ecosystem | Purpose, tiers, cadence, metrics, ownership, and the first 90 days |
| Co-sell | Preconditions, plays by account situation, rules of engagement, running a joint deal |
Skills
| Skill | Use it for |
|---|---|
| partner-fit-scorecard | Portfolio reviews and tiering decisions |
| co-sell-account-mapping | Turning account overlap into an owned action list |
| partner-qbr-brief | A one-page brief for a partner review |
| product-partnership-evaluator | Build, buy, or partner decisions and integration scoping |
| joint-business-plan | Shared goals, target accounts, and investments with a strategic partner |
| integration-launch-plan | Launching a partner integration and reviewing adoption at 90 days |
Install one with cp -r skills/partner-fit-scorecard ~/.claude/skills/.
Documentation
- How to use: commands, input formats, skill installation
- Scoring methodology: weights, caps, tiers, and a worked example
- Contributing: how changes land on the protected
mainbranch - Changelog
Related work
- ai-partner-ecosystem-analysis: research any ISV or partner from its public site
- ai-gtm-skill-library: GTM skills, including partner strategy
- ai-revops: multi-agent runtime across GTM, Partnerships, and RevOps