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 Affitor/affiliate-skills --skill value-ladder-architectgit clone --depth 1 https://github.com/Affitor/affiliate-skillsWrote 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/affitor/affiliate-skills/value-ladder-architect)<a href="https://agentmods.dev/skills/affitor/affiliate-skills/value-ladder-architect"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/value-ladder-architect/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/affitor/affiliate-skills/value-ladder-architect"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/value-ladder-architect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00096 | $0.02559 |
| Opus 5.5 | $0.00038 | $0.01024 |
| Sonnet 5.5 | $0.00019 | $0.00512 |
| Haiku 4.5 | $0.00010 | $0.00256 |
Grade A, and why
value-ladder-architect 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- value-ladder-architect — 100% identical, 0 lines differ
- value-ladder-architect — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Value Ladder Architect
Design the complete free → tripwire → core → upsell path for affiliate promotions. Maps the entire customer ascension journey, where each step delivers standalone value while naturally leading to the next. The value ladder IS the page sequence: squeeze → bridge → sales → upsell.
Stage
S4: Landing — The value ladder defines the sequence of pages and offers. Each rung is a landing page, email, or content piece that converts the visitor to the next level.
When to Use
- User wants to map the entire customer journey, not just one landing page
- User asks about upsells, downsells, tripwires, or funnel stages
- User wants to maximize lifetime value from affiliate promotions
- User says "value ladder", "customer journey", "ascension", "funnel architecture"
- After running
grand-slam-offerto design the core offer and wanting to expand - User promotes a product with multiple tiers (free, pro, enterprise)
Input Schema
product: # REQUIRED
name: string # Product name
pricing_tiers: object[] # Available pricing tiers
- name: string # e.g., "Free", "Pro", "Enterprise"
price: string # e.g., "$0", "$49/mo", "$199/mo"
features: string[] # Key features at this tier
reward_value: string # Your commission
reward_type: string # "recurring" | "one-time" | "tiered"
url: string # Affiliate link
your_assets: string[] # OPTIONAL — content/resources you already have
# e.g., ["blog", "email list", "YouTube channel", "templates"]
# Default: ["blog"]
goal: string # OPTIONAL — "first_commission" | "maximize_ltv" | "build_list"
# Default: "first_commission"
Chaining from S4 grand-slam-offer: Use offer_stack to position the core offer in the ladder.
Chaining from S4 bonus-stack-builder: Use bonus_stack to populate tripwire and bonus tiers.
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 · 249 lines · 96 tokens per session scan A ad41d002a075
value-ladder-architect is a skill published in the GitHub repository Affitor/affiliate-skills (747 stars, last pushed 8d ago), licensed MIT. It adds 96 tokens to every session and 2,559 once invoked, about $0.0004 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 2026-08-30.
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