Agent skill

Grand Slam Offer

by Affitor in Affitor/affiliate-skills

Design irresistible affiliate offers using the Hormozi Grand Slam framework.

MITAuto-check passedMarketing & SEO

Install Grand Slam Offer

skills CLI
$ npx skills add Affitor/affiliate-skills --skill grand-slam-offer -a claude-code

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

GitHub CLI
$ gh skill install Affitor/affiliate-skills grand-slam-offer --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/Affitor/affiliate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/landing/grand-slam-offer .claude/skills/grand-slam-offer && 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
grand-slam-offer
GitHub stars
701
Token cost
~2.7k tokens
SKILL.md length
905 words
Files
1
Skills in repo
50
Repo updated
First seen
Licence
MIT

At a glance

Design irresistible affiliate offers using the Hormozi Grand Slam framework.

  • Works in 6 steps: Gather Context → Apply Value Equation → Design the Offer Stack → …
  • : create an offer for
  • SKILL.md covers Stage, When to Use, Input Schema and Workflow, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grand Slam Offer is an agent skill from Affitor/affiliate-skills. Design irresistible affiliate offers using the Hormozi Grand Slam framework. Triggers on: "create an offer for", "design my offer", "grand slam offer", "make an irresistible offer", "why should someone buy through my link", "offer framework", "value proposition for", "Hormozi offer", "offer stack", "make my offer irresistible", "craft an offer", "what makes my offer different", "offer design", "increase perceived value".

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

It sits in Marketing & SEO, covering Positioning and messaging and Influencer and creator marketing. The repository describes itself as: 50 AI agent skills for affiliate marketing. Research trending content, write data-backed posts, generate infographics, build landing pages, deploy — full flywheel with social… The licence is MIT.

When your agent uses it

  • : create an offer for
  • Design my offer
  • Grand slam offer
  • Make an irresistible offer

Example prompts

  • “create an offer for”
  • “design my offer”
  • “grand slam offer”
  • “/grand-slam-offer”

Requirements

  • Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Gather Context
  2. Apply Value Equation
  3. Design the Offer Stack
  4. Write Offer Copy
  5. Output
  6. Self-Validation

What it can do on your machine

Read from SKILL.md and the folder at commit e43bfae. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    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.

  • Compatibility

    Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

    From compatibility in the SKILL.md frontmatter.

Context cost

Grand Slam Offer loads about 2.7k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 905 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~110
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from Affitor/affiliate-skills at commit e43bfae, republished under its MIT licence (© Affitor). 905 words, ~2,691 tokens.

Download SKILL.mdSave it as .claude/skills/grand-slam-offer/SKILL.md (or your agent's skills folder).
name
grand-slam-offer
description
Design irresistible affiliate offers using the Hormozi Grand Slam framework. Triggers on: "create an offer for", "design my offer", "grand slam offer", "make an irresistible offer", "why should someone buy through my link", "offer framework", "value proposition for", "Hormozi offer", "offer stack", "make my offer irresistible", "craft an offer", "what makes my offer different", "offer design", "increase perceived value".
compatibility
Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
license
MIT
version
1.0.0
tags
affiliate-marketing, landing-pages, conversion, offers, hormozi
metadata.author
affitor
metadata.version
1.0
metadata.stage
S4-Landing

Grand Slam Offer

Design affiliate offers so good people feel stupid saying no. Uses the Hormozi Value Equation: Value = Dream Outcome × Perceived Likelihood ÷ Time Delay ÷ Effort & Sacrifice. Deconstructs why someone should click YOUR link over any other affiliate's.

Stage

S4: Landing — The offer IS the landing page's job. Before writing HTML or copy, you need an offer framework that makes the conversion inevitable.

When to Use

  • User wants to differentiate their affiliate promotion from every other affiliate
  • User asks "why would someone buy through MY link?"
  • User is about to create a landing page and needs the offer angle first
  • User wants to increase conversion rates on an existing promotion
  • User says anything like "offer", "value proposition", "irresistible", "Hormozi"
  • User has a product from S1 and wants to craft the positioning before S4 landing page

Input Schema

yaml
product:                    # REQUIRED — the affiliate product
  name: string              # Product name
  description: string       # What it does
  reward_value: string      # Commission (e.g., "30% recurring")
  url: string               # Affiliate link URL
  pricing: string           # Product price or pricing page URL
  tags: string[]            # e.g., ["ai", "video", "saas"]

target_audience: string     # OPTIONAL — who you're targeting
                            # Default: inferred from product tags

bonuses: string[]           # OPTIONAL — bonuses you're already offering
                            # Default: none (will suggest bonuses)

competitors: string[]       # OPTIONAL — competing products
                            # Default: auto-researched

Chaining from S1: If affiliate-program-search was run earlier, automatically pick up recommended_program as the product input.

Chaining from S1 purple-cow-audit: If purple-cow-audit was run, use remarkability_score and remarkable_angles to inform the offer.

Workflow

Step 1: Gather Context

If product data is available from S1 chaining, use it directly. Otherwise:

  1. Use web_search to research: "[product name] features pricing review"
  2. Gather: name, pricing tiers, key features, target audience, top 3 competitors
  3. If target_audience not provided, infer from product positioning and tags
Step 2: Apply Value Equation

Read shared/references/offer-frameworks.md for the Hormozi framework.

For each component of the Value Equation, score the product 1-10 and identify leverage points:

Dream Outcome (maximize)

  • What is the #1 transformation the audience wants?
  • What does life look like AFTER using this product?
  • Frame in terms of identity: "Become the person who..."

Perceived Likelihood (maximize)

  • What proof exists? (case studies, user count, reviews)
  • What specific numbers can you cite?
  • What demonstration can you offer? (your own results, screenshots)

Time Delay (minimize)

  • How fast can they see first results?
  • What quick wins does the product offer?
  • Can you accelerate with your bonuses? (templates, setup guide)

Effort & Sacrifice (minimize)

  • What's the learning curve?
  • What do they have to give up?
  • Can you reduce effort with done-for-you assets?
Step 3: Design the Offer Stack

Build the complete offer:

  1. Core product — the affiliate product itself with reframed positioning
  2. Your unique angle — why YOU are the right person to recommend this
  3. Bonus suggestions — 3-5 bonuses that address the weakest Value Equation components
  4. Guarantee suggestion — your personal guarantee on top of the product's
  5. Urgency element — ethical, real urgency (if applicable)
Step 4: Write Offer Copy

Create ready-to-use copy blocks:

  • Headline: One sentence that captures the dream outcome
  • Sub-headline: Addresses the biggest objection
  • Value stack: Bullet list of everything they get (product + bonuses + guarantee)
  • CTA: Action-oriented, specific, urgent
Step 5: Output

Present the complete Grand Slam Offer framework.

Step 6: Self-Validation

Before presenting output, verify:

  • Value Equation is complete (all 4 components scored and addressed)
  • Offer is differentiated from a generic "buy through my link" promotion
  • Bonuses are specific and deliverable (not vague promises)
  • Guarantee is realistic and scoped to what YOU can deliver
  • Copy is specific to this product (not generic template fill)
  • FTC-compliant — no income claims, no fake urgency

If any check fails, fix before delivering.

Output Schema

yaml
output_schema_version: "1.0.0"
grand_slam_offer:
  product_name: string        # Product being promoted
  value_equation:
    dream_outcome: string     # The transformation promise
    dream_outcome_score: number  # 1-10
    likelihood: string        # Proof points
    likelihood_score: number  # 1-10
    time_delay: string        # Speed to results
    time_delay_score: number  # 1-10 (lower = better, inverted in output)
    effort: string            # Ease of use
    effort_score: number      # 1-10 (lower = better, inverted in output)
    total_value_score: number # Calculated composite

  offer_stack:
    unique_angle: string      # Your differentiator
    bonuses: object[]         # Suggested bonuses
    guarantee: string         # Your personal guarantee
    urgency: string           # Ethical urgency element

  offer_copy:
    headline: string          # Main headline
    sub_headline: string      # Objection-addressing sub-headline
    value_stack: string[]     # Bullet list of everything included
    cta: string               # Call to action text

chain_metadata:
  skill_slug: "grand-slam-offer"
  stage: "landing"
  timestamp: string
  suggested_next:
    - "landing-page-creator"
    - "bonus-stack-builder"
    - "guarantee-generator"
    - "email-drip-sequence"

Output Format

## Grand Slam Offer: [Product Name]

### Value Equation Analysis

| Component | Score | Leverage Point |
|---|---|---|
| Dream Outcome | X/10 | [key insight] |
| Perceived Likelihood | X/10 | [key insight] |
| Time Delay | X/10 | [key insight] |
| Effort & Sacrifice | X/10 | [key insight] |
| **Total Value Score** | **X/40** | |

### Your Unique Angle
[Why YOUR recommendation matters]

### Offer Stack
**They get:**
1. [Product] — [reframed benefit] ($XX/mo value)
2. BONUS: [Bonus 1] — [what it solves] ($XX value)
3. BONUS: [Bonus 2] — [what it solves] ($XX value)
4. BONUS: [Bonus 3] — [what it solves] ($XX value)
5. YOUR GUARANTEE: [guarantee statement]

**Total value: $XXX — they pay: $XX/mo**

### Ready-to-Use Copy

**Headline:** [headline]
**Sub-headline:** [sub-headline]

**Value Stack:**
[bullet list]

**CTA:** [call to action]

### Next Steps
- Run `bonus-stack-builder` to flesh out bonus details
- Run `guarantee-generator` to craft your guarantee copy
- Run `landing-page-creator` to build the page with this offer
Show full SKILL.md (373 more words)Show less

Error Handling

  • No product provided: "I need a product to design an offer for. Run affiliate-program-search first, or tell me the product name."
  • No pricing found: Use web_search for "[product] pricing". If unavailable, use "Check current pricing" and frame value around ROI instead.
  • Product too generic: "This product competes in a crowded space. Let me find your unique angle..." → focus on YOUR differentiators (bonuses, expertise, guarantee).
  • No competitive data: Design the offer based on the product alone. Note: "Run competitor-spy for competitive intelligence to sharpen this offer."

Examples

Example 1: "Design a grand slam offer for HeyGen" → Research HeyGen features/pricing, score Value Equation, identify unique angle (e.g., "AI video for non-creators"), suggest bonuses (script templates, avatar setup guide, prompt library), write offer copy.

Example 2: "I promote Semrush but my conversion rate is low" → Analyze why: likely weak differentiation. Score Value Equation, identify weakest component (probably Effort — steep learning curve), design bonuses that reduce effort (done-for-you audit template, keyword research spreadsheet, setup walkthrough).

Example 3: "Create an offer for this product" (after S1 + purple-cow-audit) → Pick up product data from S1, remarkability angles from purple-cow-audit, design offer that amplifies the most remarkable aspects.

Flywheel Connections

Feeds Into
  • landing-page-creator (S4) — offer copy becomes the page's core messaging
  • bonus-stack-builder (S4) — offer analysis identifies which bonuses to create
  • guarantee-generator (S4) — value equation reveals what to guarantee
  • email-drip-sequence (S5) — offer framing drives email copy
  • value-ladder-architect (S4) — offer positioning informs ladder design
Fed By
  • affiliate-program-search (S1) — product data to build the offer around
  • purple-cow-audit (S1) — remarkability angles to emphasize
  • competitor-spy (S1) — competitive gaps to exploit in the offer
  • content-moat-calculator (S3) — authority gaps inform what to emphasize
Feedback Loop
  • Conversion rate from conversion-tracker (S6) reveals which Value Equation components resonated → improve weak components on next offer

Quality Gate

Before delivering output, verify:

  1. Would I share this on MY personal social?
  2. Contains specific, surprising detail? (not generic)
  3. Respects reader's intelligence?
  4. Remarkable enough to share? (Purple Cow test)
  5. Irresistible offer framing? (Grand Slam formula applied)

Any NO → rewrite before delivering. Do not flag this checklist to the user.

References

  • shared/references/offer-frameworks.md — Hormozi Value Equation, bonus stack rules, guarantee types, pricing psychology
  • shared/references/ftc-compliance.md — FTC disclosure requirements (no income claims, no fake urgency)
  • shared/references/affiliate-glossary.md — Affiliate terminology
  • shared/references/flywheel-connections.md — Master connection map

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

Files

Just SKILL.md in skills/landing/grand-slam-offer of Affitor/affiliate-skills.

Open the folder on GitHubat commit e43bfae

Compare with similar skills

Grand Slam Offer 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.

Grand Slam Offer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Grand Slam Offer this skillAffitor/affiliate-skills701—~2.7kAutomated safety check: PassMIT
Creator Profile TeardownScrapeCreators/social-media-research-skills3.4k—~550Automated safety check: NotesMIT
Running MarketingGTM-Strategist/gtm-strategist-skills264—~7.8kAutomated safety check: PassMIT
Creator Profile Teardowngooseworks-ai/goose-skills1.2k—~578Automated safety check: PassMIT
Marketing OsYuzzyuk/marketing-os540—~2.5kAutomated safety check: PassMIT
Revenue Centric Designheliocosta-dev/revenue-centric-design740—~1.6kAutomated safety check: PassCustom licence

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Categories

Questions about Grand Slam Offer

What does Grand Slam Offer do?

Design irresistible affiliate offers using the Hormozi Grand Slam framework. Grand Slam Offer is an agent skill from Affitor/affiliate-skills. Design irresistible affiliate offers using the Hormozi Grand Slam framework.

When should I use Grand Slam Offer?

Grand Slam Offer fits situations like: : create an offer for; design my offer; grand slam offer; make an irresistible offer.

How do I install Grand Slam Offer in Claude Code?

Run `npx skills add Affitor/affiliate-skills --skill grand-slam-offer -a claude-code`. Or copy the skill folder (skills/landing/grand-slam-offer in Affitor/affiliate-skills) into .claude/skills/grand-slam-offer in your project. Claude Code loads it when a task matches its description.

How do I install Grand Slam Offer in Codex?

Run `npx skills add Affitor/affiliate-skills --skill grand-slam-offer -a codex`. Or copy the skill folder (skills/landing/grand-slam-offer in Affitor/affiliate-skills) into .agents/skills/grand-slam-offer in your project. Codex loads it when a task matches its description.

Can I use Grand Slam Offer 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 Affitor/affiliate-skills --skill grand-slam-offer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/grand-slam-offer, .gemini/skills/grand-slam-offer, .github/skills/grand-slam-offer and .opencode/skills/grand-slam-offer in your project.

What does Grand Slam Offer need to run?

SKILL.md names no scripts, command-line tools or credentials: Grand Slam Offer is instructions for the agent only. Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent.

Does Grand Slam Offer 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 Grand Slam Offer 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. Review the folder before installing.

What licence does Grand Slam Offer use?

Grand Slam Offer 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 Grand Slam Offer use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Grand Slam Offer?

Skills that share tags, products or a category with Grand Slam Offer: Creator Profile Teardown (ScrapeCreators/social-media-research-skills, 3.4k stars), Running Marketing (GTM-Strategist/gtm-strategist-skills, 264 stars), Creator Profile Teardown (gooseworks-ai/goose-skills, 1.2k stars) and Marketing Os (Yuzzyuk/marketing-os, 540 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grand Slam Offer?

Affitor (a GitHub organization) maintains it in Affitor/affiliate-skills, which has 701 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on September 15, 2026.

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