Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add varunk130/ai-gtm-skill-library --skill loyalty-lifecyclegit clone --depth 1 https://github.com/varunk130/ai-gtm-skill-libraryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/loyalty-lifecycle)<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/loyalty-lifecycle"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/loyalty-lifecycle/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/loyalty-lifecycle"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/loyalty-lifecycle.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.01213 |
| Opus 5.5 | $0.00028 | $0.00485 |
| Sonnet 5.5 | $0.00014 | $0.00243 |
| Haiku 4.5 | $0.00007 | $0.00121 |
Grade A, and why
loyalty-lifecycle scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loyalty & Lifecycle (BOND Framework)
Design a loyalty and lifecycle program that produces measurable retention lift - not a tier ladder for its own sake. BOND forces clarity on what behaviors loyalty is supposed to reinforce, what evidence the customer sees, and how the program economics actually pay back.
Core Principle
A loyalty program is a behavior contract, not a points system. Most loyalty programs fail because they reward existing behavior (free margin loss) instead of net-new behavior (retention lift). BOND structures the program around behaviors that change the unit economics.
The BOND Framework
| Letter | Stage | The Question |
|---|---|---|
| B | Behavior Targeting | Which 3-5 customer behaviors, if reinforced, would shift retention and LTV? |
| O | Offer Architecture | What earn / burn mechanics + tier benefits reinforce those behaviors? |
| N | Notification & Lifecycle | What lifecycle triggers and moments deliver the program in-context? |
| D | Defend the Economics | How does the program pay back, and what's the cannibalization guardrail? |
Behavior Targeting
A useful program changes behavior in measurable ways. Start with:
| Behavior Lift | Example Metric | Loyalty Lever |
|---|---|---|
| Frequency | Purchases per quarter | Visit-based earn, accelerator tiers |
| Basket / Expansion | Average order value, modules per account | Bonus earn on add-ons |
| Retention | Renewal rate, churn rate | Time-in-program rewards, tier downgrade protection |
| Advocacy | Referrals, reviews | Referral bonus, badge / status |
| Engagement Depth | Workflow coverage, feature adoption | Achievement-based rewards |
Tier Design
| Element | Best Practice |
|---|---|
| Number of tiers | 3-4; more dilutes status |
| Tier criteria | Mix of spend + behavior; behavior-only tiers possible |
| Tier benefits | At least one experiential benefit per tier (not just discounts) |
| Tier durability | Annual review or rolling 12-month; never punitive |
| Recognition | Visible status (badges, color, named cohort) at every tier |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 108 lines · 70 tokens per session scan A a3e207f7ea7f
loyalty-lifecycle is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (7 stars, last pushed 10d ago), licensed MIT. It adds 70 tokens to every session and 1,213 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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