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SKILL verified MIT Self-run

Offer Design

skill-infinite-labs-ai-infinite-skills-offer-design · by Infinite-Labs-AI

Use when designing or improving an offer, package, pricing page argument, plan structure, guarantee, bonus, trial, annual discount, service bundle, or upgrade path.

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Install

$ agentstack add skill-infinite-labs-ai-infinite-skills-offer-design

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
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4d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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How agent discovery & health will work →
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About

Offer Design

Shape the offer around buyer anxiety, adoption path, fulfillment constraints, and plan boundaries.

Understand The Sale

Identify:

  • Buyer and user.
  • Desired outcome.
  • Current alternative.
  • Price or expected budget.
  • Purchase anxiety.
  • Fulfillment cost and margin risk.
  • Proof available.
  • Sales motion: self-serve, sales-led, product-led, service-led, marketplace.

If the user asks for copy before the offer is clear, define the offer first.

Inspect Offer Fit

Break it into fit dimensions:

  • Buyer anxiety: what makes the purchase feel risky.
  • Adoption path: what has to happen after purchase for value to appear.
  • Fulfillment constraint: what the business must deliver reliably.
  • Support burden: where customers will need help.
  • Abuse risk: how guarantees, trials, discounts, or unlimited use can be misused.
  • Plan boundary: what separates small, growing, and high-value customers.
  • Proof threshold: what evidence the buyer needs before paying.
  • Price logic: how price maps to value, usage, or urgency.

Flag weak spots: vague deliverables, fake urgency, unpriced complexity, guarantees that create abuse, discounts that train waiting, support promises the team cannot honor, or plan tiers that punish the best customers.

Redesign

Offer 2-3 structures:

  • Simple offer: easiest to understand and buy.
  • Proof-heavy offer: best when trust is the barrier.
  • Expansion offer: best when land-and-expand matters.

For each, define the promise, included pieces, exclusions, price logic, risk reversal, and reason to act now.

Watch Outs

  • Do not invent scarcity.
  • Do not recommend a guarantee the business cannot honor.
  • Tie bonuses to purchase anxiety, not random perceived value.
  • Use a value metric customers can understand and the business can support.
  • Keep plan differences based on customer maturity or usage, not arbitrary feature hiding.

Output

Offer fit diagnosis:
[what is clear, what is weak]

Purchase anxiety:
- [fear]
- [fear]

Recommended offer:
Name:
For:
Promise:
Includes:
Excludes:
Price logic:
Adoption support:
Risk handling:
Abuse boundary:
Plan boundary:

Alternative structures:
1. [option] - [when to use]
2. [option] - [when to use]

Copy-ready bullets:
- [bullet]
- [bullet]
- [bullet]

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.