Agent skill

Channel Economics

by borghei in borghei/Claude-Skills

Channel economics: design and analyze the financial structure of go-to-market channels.

MITAuto-check passedMarketing & SEO

Install Channel Economics

skills CLI
$ npx skills add borghei/Claude-Skills --skill channel-economics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills channel-economics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/business-growth/channel-economics .claude/skills/channel-economics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
channel-economics
GitHub stars
891
Token cost
~4.2k tokens
SKILL.md length
1,710 words
Files
7 (incl. scripts, references)
Skills in repo
354
Repo updated
First seen
Licence
MIT

At a glance

Channel economics: design and analyze the financial structure of go-to-market channels.

  • Works in 5 steps: Outcome-based, not effort-based. Reward… → Achievable but stretching. Each tier… → Differentiable benefits. Each tier needs… → …
  • Picking a channel mix
  • SKILL.md covers When to use this skill, The channel model decision tree, Margin and TCO framework and Partner tier economics, plus 8 more sections
  • Runs Python scripts from its folder

What it does

Channel Economics is an agent skill from borghei/Claude-Skills. Channel economics: design and analyze the financial structure of go-to-market channels. Use when picking a channel mix, modeling partner margin or TCO, designing partner tiers and rebates, or analyzing channel conflict.

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/channel-conflict-resolution.md`, `references/channel-models-direct-partner-marketplace.md` and `references/margin-and-tco-frameworks.md`).

It sits in Marketing & SEO, covering Go-to-market strategy. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Picking a channel mix
  • Modeling partner margin
  • Designing partner tiers and rebates
  • Analyzing channel conflict

Example prompts

  • “/channel-economics”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Outcome-based, not effort-based. Reward revenue + retention, not training hours or marketing event count.
  2. Achievable but stretching. Each tier should be a 12-18 month stretch from the prior.
  3. Differentiable benefits. Each tier needs benefits a partner actively wants (not just "more support").
  4. Renewable status. Tiers re-evaluated annually. Partners can move down if they don't maintain.
  5. Anti-gaming protection. Discount-stacking, registration gaming, transfer pricing — design out.

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Channel Economics loads about 4.2k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 1,710 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 1,710 words, ~4,201 tokens.

Download SKILL.mdSave it as .claude/skills/channel-economics/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
channel-economics
description
Channel economics: design and analyze the financial structure of go-to-market channels. Use when picking a channel mix, modeling partner margin or TCO, designing partner tiers and rebates, or analyzing channel conflict.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
commercial
metadata.domain
business-growth
metadata.updated
2026-05-27
metadata.tags
channel-economics, channel-strategy, partner-program, margin-analysis, gtm, reseller, distributor, marketplace, msp

Channel Economics

End-to-end financial modeling and design of go-to-market channels: direct sales economics, reseller / distributor margin structures, marketplace fees, partner tier economics, channel conflict resolution, and the TCO frameworks that compare channel options apples-to-apples.

This skill provides the financial backbone for channel strategy. For strategic partnership design (which channel to invest in, how to structure the partnership), see business-growth/partnerships-architect. For partner-deal-level approval mechanics, see business-growth/deal-desk.


When to use this skill

SituationSkill applies
Deciding direct vs partner-led for a new productYes — start with channel model decision tree
Designing a partner tier structure (silver/gold/platinum)Yes — see partner tier economics
Modeling a specific partner deal's margin / paybackYes — scripts/channel_margin_calculator.py
Analyzing channel conflict (overlapping direct + partner deals)Yes — see channel conflict + scripts/channel_mix_optimizer.py
Building a partner program rebate / SPIFF structureYes — see rebate design
Comparing AWS Marketplace vs direct list-price economicsYes — scripts/channel_margin_calculator.py --channel marketplace
Negotiating a specific partner contractUse business-growth/contract-and-proposal-writer for the contract; this for the economics
Strategic partnership design (joint go-to-market, OEM, white-label)Use business-growth/partnerships-architect first

The channel model decision tree

Six core channel models. Most companies use a mix.

What's the product's complexity + price point?

Low complexity, low price (< $10k ACV):
├── Self-serve / PLG → no channel
├── E-commerce → direct via web
└── Marketplace (AWS / Azure / GCP / Salesforce AppExchange) → if buyer already there

Medium complexity, mid-market price ($10k - $250k ACV):
├── Inside sales / SDR-led direct → if buyer journey is well-understood
├── Reseller / VAR (Value-Added Reseller) → if local presence / language matters
├── Marketplace → if buyer prefers procurement via existing relationship
└── Embedded / OEM → if your product is a component in someone else's offering

High complexity, enterprise ($250k+ ACV):
├── Direct field sales → standard for high-touch enterprise
├── Strategic SI / Integrator (Accenture, Deloitte, etc.) → if implementation is a substantial project
├── ISV / Embedded → if you're a feature in a larger platform
└── Reseller / Distributor → for regional or vertical specialty

Operational / managed-service buyer:
└── MSP (Managed Service Provider) → if customer wants outsourced operations

See references/channel-models-direct-partner-marketplace.md for each model in depth: economic structure, typical margin splits, when each works / fails, contract patterns.


Margin and TCO framework

Apples-to-apples channel comparison requires a consistent TCO model. The naive comparison ("direct gets 100%, reseller gets 70%") misses critical costs.

True channel TCO formula
Channel Contribution Margin
  = Channel-attributed Revenue
  − COGS
  − Partner Discount/Commission
  − Channel-specific Sales Cost (allocated)
  − Channel-specific Marketing Cost (MDF, co-marketing)
  − Partner Enablement Cost (training, certification)
  − Channel Operations Cost (channel manager headcount)
  − Channel-specific Support Cost (T1 partner support)
Side-by-side comparison

For a $100k ACV deal:

ComponentDirectReseller (30% off)AWS Marketplace
Customer payment$100,000$100,000$100,000
Reseller / marketplace fee$0-$30,000 (30% discount)-$3,000 (3% AWS fee)
Revenue to us$100,000$70,000$97,000
COGS (15%)-$15,000-$10,500-$14,550
Sales cost (allocated CAC)-$25,000-$5,000-$8,000
Marketing cost (MDF / listing)-$2,000-$8,000-$5,000
Partner enablement (amortized)$0-$3,000-$1,500
Channel ops (amortized)$0-$2,000-$1,000
Support cost-$5,000-$3,000-$5,000
Net contribution$53,000$38,500$61,950
% of ACV53%38.5%62%

The "30% discount" reseller deal is more like 14.5% margin difference once everything's counted. Marketplace can look better than direct on per-deal basis (Amazon's sales team brings the buyer) — but volume varies.

Use scripts/channel_margin_calculator.py --deal deal.yaml --channel <type> to model this for any deal.

See references/margin-and-tco-frameworks.md for the full TCO framework, per-cost-line guidance, and how to allocate "fully-loaded" sales / marketing / ops costs.


Partner tier economics

Multi-tier partner programs (Authorized → Silver → Gold → Platinum) are common. Designed badly, they reward effort that isn't valuable; designed well, they reward outcomes that drive growth.

Standard tier structure
TierAnnual revenue thresholdDiscount %Other benefitsRequirements
AuthorizedNone10%Standard supportSign partner agreement; 1 certified person
Silver$100k15%Co-marketing eligible (limited MDF)$100k achieved; 3 certified people; 2 customer wins
Gold$500k20% + 5% rebate at thresholdDedicated channel manager; MDF; deal registration; lead sharing$500k achieved; 5 certified; 5 wins; 80% renewal rate
Platinum$2M25% + 7% rebate at thresholdTop-tier support; joint roadmap; preferred status; press release rights$2M achieved; 10 certified; 10 wins; 90% renewal; participation in advisory board
Tier design principles
  1. Outcome-based, not effort-based. Reward revenue + retention, not training hours or marketing event count.
  2. Achievable but stretching. Each tier should be a 12-18 month stretch from the prior.
  3. Differentiable benefits. Each tier needs benefits a partner actively wants (not just "more support").
  4. Renewable status. Tiers re-evaluated annually. Partners can move down if they don't maintain.
  5. Anti-gaming protection. Discount-stacking, registration gaming, transfer pricing — design out.

Use scripts/partner_tier_economics.py --tiers tiers.yaml to model tier economics: gross margin per tier, partner-side incentive, break-even revenue per partner per tier.


Rebate / SPIFF design

Three common reward structures, each with trade-offs:

Front-end discount

Partner buys from you at a discount; sells to customer at list (or close). Margin = the spread.

Pros: Simple. Cash flow goes to partner immediately. Cons: Hard to incentivize specific behaviors. Discount is locked in regardless of performance.

Back-end rebate

Partner pays full price (or near it); earns rebate quarterly / annually based on revenue / tier achievement.

Pros: Ties reward to actual achievement; behaviors can be incentivized (e.g., bonus for selling new products). Cons: Cash-flow burden on partner. Complex to administer.

MDF (Marketing Development Funds) / SPIFF

Per-deal or per-period bonuses for specific actions: bring leads, attend events, certify staff.

Pros: Highly targetable. Rewards specific behaviors you want. Cons: Easy to game; admin overhead high; partners often expect it without producing.

Typical mix
Partner typeFront-endBack-endMDF/SPIFF
Reseller (transactional)70-80% of total comp10-20%5-10%
VAR (consultative selling)50-60%20-30%10-20%
Distributor (volume play)80-90%5-15%5%
ISV / Embeddedn/a (rev share)100%0
MSP40-60%20-30%10-30%

Channel conflict

Channel conflict happens when multiple sales paths chase the same customer. Common forms:

Direct-vs-partner conflict
ScenarioResolution pattern
Direct rep finds opportunity also touched by partnerDeal registration: first to register wins; partner gets credit if they brought it
Partner finds direct customerIf direct is already engaged: partner deferred (with consolation MDF perhaps); if not: partner leads
Customer asks for direct after partner-led pilotHonor partner relationship for term; transition at next renewal if appropriate
Partner-vs-partner conflict
ScenarioResolution pattern
Two resellers both pursuing same accountFirst-registered wins; second is offered alternative leads / regional swap
Vertical specialist vs geographicVertical wins (customer values vertical expertise more)
New partner pursues incumbent partner's customerIncumbent has right of first refusal for 90 days
Marketplace-vs-direct conflict

Customer can buy via AWS Marketplace OR direct. If price is lower direct, customer feels gamed. If price is same, why not just use marketplace? Common resolution:

  • Same price direct vs marketplace (customer doesn't get punished for procurement choice)
  • Quota credit to the direct rep when customer chooses marketplace (so rep isn't disincentivized)
  • Marketplace listing visibility as a value-add, not as a different pricing channel

See references/channel-conflict-resolution.md for the full conflict-resolution playbook including deal registration process, neutral arbitration, conflict-of-interest disclosure.


Clarify First

Before modeling the channel economics, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Channel model(s) in scope — direct, reseller/VAR, distributor, marketplace, OEM, or MSP (sets which decision-tree branch and TCO comparison to run)
  • Target ACV / price point — sub-$10k vs mid-market vs enterprise (selects the viable channel branch and sizes per-deal margin)
  • Fully-loaded cost lines — COGS %, allocated sales/marketing/ops/support costs (drives the TCO contribution-margin model, not just the headline discount)
  • Partner contribution + tier intent — what the partner does (lead, sell, implement) and whether you're designing tiers/rebates (drives tier economics + rebate/SPIFF mix)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the model.

Show full SKILL.md (632 more words)Show less

End-to-end workflows

Workflow: Design a new partner program
  1. Pick channel models — direct + reseller? marketplace? OEM? — using the decision tree
  2. Model the economics — scripts/channel_margin_calculator.py per channel option at expected ACV
  3. Design tier structure — scripts/partner_tier_economics.py to size the gates and benefits
  4. Define rebate / SPIFF mix — per tier and partner type
  5. Write the partner agreement (with business-growth/contract-and-proposal-writer)
  6. Build channel ops — deal registration, MDF approval, certification tracking
  7. Hire channel manager(s) — usually 1 manager per 10-15 active partners
  8. Pilot with 3-5 partners — measure, iterate, then scale
Workflow: Evaluate a specific partner deal
  1. Inputs: ACV, partner discount %, expected close, partner's contribution (lead source? sales effort? implementation?)
  2. Calculate net contribution — scripts/channel_margin_calculator.py --deal deal.yaml --channel partner
  3. Compare to direct alternative — would this deal have closed direct? at what cost?
  4. Decide: approve / counter / decline (often via deal desk if it's a non-standard partner discount)
Workflow: Channel mix analysis
  1. Inputs: actual revenue by channel for last 4 quarters
  2. Run mix optimizer — scripts/channel_mix_optimizer.py --revenue revenue.csv examines contribution margin per channel + identifies under-/over-invested channels
  3. Recommend rebalancing — e.g., "Reseller channel: 20% of revenue, 8% of contribution margin — reduce investment; marketplace: 15% of revenue, 25% of contribution — increase listing visibility"
  4. Quarterly review: present to CRO / CFO
Workflow: Resolve a channel conflict
  1. Document the conflict — accounts involved, parties, history
  2. Apply the registration rule — first-registered partner wins absent overriding facts
  3. Consider exceptions — strategic logo, customer preference, vertical expertise
  4. Communicate decision — both parties, with reasoning, in writing
  5. Compensate the loser — alternative leads, MDF, regional swap; preserve the relationship

Anti-patterns

  • Direct + partner at same price. Customer feels punished for not using direct (or vice versa); kills partner motivation. Price-to-customer must be consistent across channels.
  • Discount-only partner program. Partners that only get a discount have no skin in your success; treat you as another vendor; switch easily.
  • Endless partner expansion without enablement. Signing 200 partners that don't sell anything; channel manager headcount can't scale; partners stale.
  • Marketplace as afterthought. Listing on AWS Marketplace without dedicated investment (listing optimization, co-sell programs) = marketplace generates nothing.
  • Channel manager as glorified email forwarder. CM should drive partner pipeline, not just relay leads.
  • Rebates with no audit. Partner self-reports revenue; you trust it; reality is 20% off. Build verification.
  • MDF spent on activities that don't drive pipeline. Partner runs a great event, generates no pipeline. MDF should require pipeline outcome.
  • Channel conflict policy that isn't followed. Policy says first-registered wins, but exec overrides every time → policy is theater.
  • Different commission per channel for same deal. Direct rep gets 8% on $100k deal, channel rep gets 6% on $100k deal — direct rep refuses partner help; channel rep undercut.
  • OEM / embedded deals priced like resale. OEM = customer doesn't see you at all; ASP can be 50-80% of list. Resale = customer sees you. Different economics; different price points.

Tooling outputs

ScriptInputOutput
scripts/channel_margin_calculator.pyDeal spec YAML + channel typePer-channel net contribution margin, cost line breakdown, comparison vs direct baseline
scripts/partner_tier_economics.pyTier definitions YAMLPer-tier: gross margin to us, gross margin to partner, partner break-even, tier graduation incentive analysis
scripts/channel_mix_optimizer.pyRevenue CSV (by channel + quarter)Per-channel revenue contribution, per-channel margin contribution, recommended rebalancing

All scripts: stdlib only, argparse CLI, JSON or markdown output.


References


  • business-growth/partnerships-architect — strategic partnership design (this skill = the economics; that one = the strategy)
  • business-growth/deal-desk — approval mechanics for partner deals (this skill = "what does it cost"; deal desk = "should we approve")
  • business-growth/pricing-strategy — sets list pricing that channel economics deviates from
  • business-growth/revenue-operations — channel revenue is segmented in RevOps reporting
  • business-growth/contract-and-proposal-writer — drafts partner agreements
  • sales-success/sales-operations — runs channel ops (deal registration, MDF approval, certification tracking)
  • c-level-advisor/cs-cro-advisor — strategic channel-mix decisions are CRO-level

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in business-growth/channel-economics of borghei/Claude-Skills.

  • SKILL.md
  • references/channel-conflict-resolution.md
  • references/channel-models-direct-partner-marketplace.md
  • references/margin-and-tco-frameworks.md
  • scripts/channel_margin_calculator.py
  • scripts/channel_mix_optimizer.py
  • scripts/partner_tier_economics.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Channel Economics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Revenue Centric Designheliocosta-dev/revenue-centric-design740—~1.6kAutomated safety check: PassCustom licence
Startup Designferdinandobons/startup-skill1.2k—~8.1kAutomated safety check: PassMIT
Jaredrhod Marketingjaredrhod/ai-marketing-skills282—~584Automated safety check: PassCC-BY-SA-4.0
Traffic Acquisitionvivy-yi/xiaohongshu-skills4811 repos~4kAutomated safety check: PassNone

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Categories

Questions about Channel Economics

What does Channel Economics do?

Channel economics: design and analyze the financial structure of go-to-market channels. Channel Economics is an agent skill from borghei/Claude-Skills. Channel economics: design and analyze the financial structure of go-to-market channels.

When should I use Channel Economics?

Channel Economics fits situations like: picking a channel mix; modeling partner margin; designing partner tiers and rebates; analyzing channel conflict.

How do I install Channel Economics in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill channel-economics -a claude-code`. Or copy the skill folder (business-growth/channel-economics in borghei/Claude-Skills) into .claude/skills/channel-economics in your project. Claude Code loads it when a task matches its description.

How do I install Channel Economics in Codex?

Run `npx skills add borghei/Claude-Skills --skill channel-economics -a codex`. Or copy the skill folder (business-growth/channel-economics in borghei/Claude-Skills) into .agents/skills/channel-economics in your project. Codex loads it when a task matches its description.

Can I use Channel Economics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill channel-economics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/channel-economics, .gemini/skills/channel-economics, .github/skills/channel-economics and .opencode/skills/channel-economics in your project.

What does Channel Economics need to run?

Going by SKILL.md and its folder, Channel Economics needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Channel Economics access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Channel Economics safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Channel Economics use?

Channel Economics is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Channel Economics use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Channel Economics?

Skills that share tags, products or a category with Channel Economics: Marketing Plan (Nexus-JPF/note-companion, 870 stars), Revenue Centric Design (heliocosta-dev/revenue-centric-design, 740 stars), Startup Design (ferdinandobons/startup-skill, 1.2k stars) and Jaredrhod Marketing (jaredrhod/ai-marketing-skills, 282 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Channel Economics?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 891 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.