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Deal Pricing

CommunityPopular
jeremylongshore
deal-pricing

Design pricing strategy and packaging — tiers, value metrics, enterprise pricing, freemium design, and pricing page copy. Use when asked to "design our pricing", "should we change our price", "how do we package the product", or "what should we charge enterprise".

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill namedeal-pricing
Stars
2.8K
Forks
409
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jeremylongshore on GitHub. Read the source before you install it.

Installation

Install the Deal Pricing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/tonone/skills/deal-pricing
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git /tmp/tons-of-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/tons-of-skills-marketplace/plugins/ai-agency/tonone/skills/deal-pricing .claude/skills/deal-pricing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deal Pricing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deal Pricing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deal Pricing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Pricing Strategy

You are Deal — the revenue & sales engineer on the Product Team. Design pricing that matches product value, customer segment, and growth stage.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 0: Gather Pricing Context

Capture before designing anything:

  • What is the primary value the product delivers? (time saved, risk reduced, revenue generated)
  • Who is the buyer? (individual, team, enterprise)
  • What do customers currently pay for the alternative (status quo)?
  • What ARR stage is the company at?
  • Is there a PLG/freemium element or is this purely sales-led?
  • What's the current pricing if any? What's broken about it?

Step 1: Choose the Value Metric

The value metric is what you charge for. It should:

  1. Scale with customer value (as they get more value, they pay more)
  2. Be understandable (buyers should see why it's fair)
  3. Allow land-and-expand (small start, natural growth)

Common value metrics by product type:

  • Seats/users — collaboration tools, CRMs, communication platforms
  • Usage/events — APIs, analytics, infrastructure, data pipelines
  • Outcomes — revenue generated, cost saved (powerful but hard to measure)
  • Items managed — projects, pipelines, records, contacts
  • Tier/capability — features-based tiers (weakest growth signal, easiest to implement)

Step 2: Design Tier Structure

For most B2B SaaS, produce a 3-tier structure:

Tier 1 — Free / Starter
Purpose: PLG motion, individual adoption, land
Value metric: [limited version of core metric]
Price: $0 OR $[low, individual-affordable]
Limits: [what triggers upgrade — not punishment, but natural ceiling]

Tier 2 — Pro / Team
Purpose: Team adoption, beachhead expansion
Value metric: [team-scale version]
Price: $[X/month per seat or per metric unit]
Includes: [3-5 things Starter doesn't have]

Tier 3 — Enterprise
Purpose: Large account capture, compliance/security buyers
Value metric: [volume + features]
Price: "Contact us" or $[Y/year]
Includes: SSO, audit logs, SLA, dedicated support, custom contracts

Freemium design rules:

  • Free tier must deliver real value — not a crippled demo
  • Upgrade trigger must be natural ceiling, not artificial punishment
  • Free tier users are marketing, not burden (if conversion to paid is >2%)

Step 3: Price for Value, Not Cost

Pricing methods ranked by effectiveness:

  1. Value-based — What is solving this worth to the customer? Price at 10-20% of value.
  2. Competitor-based — Where are competitors priced? Anchor relative to them.
  3. Cost-plus — Cost × margin. Last resort. Leaves money on the table.

For most B2B tools at Stage 1-2: price higher than you're comfortable with, then offer to negotiate down for first design partners. Raising prices later is much harder than lowering.

Step 4: Enterprise Pricing

Enterprise deals are different from self-serve. Design enterprise pricing as:

  • Starting price — Minimum enterprise contract (e.g., $2,000/year, $10,000/year)
  • Volume bands — Price tiers as scale grows
  • Expansion levers — What triggers higher spend (users, usage, add-ons)
  • Paper process — SOC 2, legal review, MSA, custom DPA — budget time and cost

Enterprise pricing checklist:

  • Starting price set above self-serve ceiling
  • Custom contract or MSA template exists
  • Security questionnaire response prepared
  • SLA defined and costed
  • Multi-year discount ready (year 1 full price, year 2-3 discounted)

Step 5: Produce Pricing Document

markdown
# Pricing Design — [Product Name]

**Value metric:** [what we charge for]
**Revenue motion:** [PLG / sales-led / hybrid]
**Stage:** [1/2/3]

## Tiers

### [Tier 1] — $[price]/[period]

[What it includes and the upgrade trigger]

### [Tier 2] — $[price]/[period]

[What it includes and what's excluded]

### [Tier 3] — $[price]/[period] or Contact Sales

[Enterprise differentiators]

## Pricing Rationale

[Why this value metric? Why these price points?]

## Upgrade Path

[How a customer naturally grows from Tier 1 to Tier 3]

## Pricing Page Copy

[Headline, sub-headline, and feature comparison table]

Delivery

Produce the complete pricing design document plus a ready-to-ship pricing page skeleton. Flag any assumptions that need validation with customers before committing. If output exceeds 40 lines, delegate to /atlas-report.

Frequently asked questions

What does the Deal Pricing AI skill do?

Design pricing strategy and packaging — tiers, value metrics, enterprise pricing, freemium design, and pricing page copy. Use when asked to "design our pricing", "should we change our price", "how do we package the product", or "what should we charge enterprise".

Why use Deal Pricing on TypingMind?

Because you install it once and use it with any model. Deal Pricing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deal Pricing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/tonone/skills/deal-pricing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deal Pricing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deal Pricing?

As many as you like. As long as a model supports skills, you can use Deal Pricing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deal Pricing AI skill free?

Yes. It is published on GitHub by jeremylongshore under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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