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 marcos-sponton/frameworks-as-skills --skill monetizing-innovationgit clone --depth 1 https://github.com/marcos-sponton/frameworks-as-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/marcos-sponton/frameworks-as-skills/monetizing-innovation)<a href="https://agentmods.dev/skills/marcos-sponton/frameworks-as-skills/monetizing-innovation"><img src="https://agentmods.dev/badge/skills/marcos-sponton/frameworks-as-skills/monetizing-innovation/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/marcos-sponton/frameworks-as-skills/monetizing-innovation"><img src="https://agentmods.dev/badge/skills/marcos-sponton/frameworks-as-skills/monetizing-innovation.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 | $0.00240 | $0.02968 |
| Opus 5.5 | $0.00096 | $0.01187 |
| Sonnet 5.5 | $0.00048 | $0.00594 |
| Haiku 4.5 | $0.00024 | $0.00297 |
Grade A, and why
monetizing-innovation 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 8d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monetizing Innovation
Madhavan Ramanujam's framework for designing products around the price, distilled from Monetizing Innovation: How Smart Companies Design the Product Around the Price (Wiley, 2016, co-authored with Georg Tacke), its sequel Scaling Innovation: How Smart Companies Architect Profitable Growth (Wiley, 2025, co-authored with Eddie Hartman), and Ramanujam's extensive podcast, talk, and advisory work since. Ramanujam was managing partner at Simon-Kucher & Partners (the world's leading pricing and monetization consultancy) and now runs 49 Palms, a fund for early-stage AI companies. The framework's core insight: have the willingness-to-pay conversation before you build, not after — because 72% of innovations that fail do so not because the technology doesn't work, but because they were never designed around what customers would pay.
This skill helps your agent think about pricing as a design input, not a post-launch afterthought. It's opinionated because Ramanujam is opinionated: price is a measure of value, how you charge often matters more than how much you charge, one-size-fits-all pricing always leaves money on the table, and feature bloat is the most common way innovations die.
When this skill activates
Use this skill when the user is:
- Pricing a new product or feature and doesn't know where to start.
- Deciding between pricing models (subscription, usage-based, freemium, outcome-based, dynamic, auction/market-based).
- Diagnosing why a launched product isn't monetizing — revenue below plan, too many free users, customers churning at renewal.
- Planning willingness-to-pay research (survey design, customer interviews about price, conjoint analysis).
- Making bundling or unbundling decisions (good/better/best tiers, add-ons, feature packaging).
- Choosing between freemium, free trial, and paid-only strategies.
- Segmenting customers by willingness to pay rather than demographics.
- Repricing after a market shift, competitive entry, or AI disruption.
- Pricing an AI product (agents, copilots, autonomous tools) and deciding between per-seat, usage, credits, or outcome-based models.
- Preparing a pricing strategy document (goals, strategy type, price-setting rules, reaction principles).
- Running a "leaders, fillers, killers" analysis on a feature set.
- Negotiating a deal and needs a give-and-get framework.
- Building a business case that links price, value, volume, and cost.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 9.0 KB
- examples/.gitkeep 0 B
- README.md 6.2 KB
- references/applications.md 9.6 KB
- references/author-live-sources.md 4.7 KB
- references/examples.md 11 KB
- references/heuristics.md 8.6 KB
- references/method.md 16 KB
- references/post-book.md 8.1 KB
- references/prompts.md 5.4 KB
- references/sources.md 11 KB
- references/voice-and-tone.md 5.1 KB
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.
- 8d ago First seen · 106 lines · 0 tokens per session scan A eb08daf5aae1
monetizing-innovation is a skill published in the GitHub repository marcos-sponton/frameworks-as-skills (1 stars, last pushed 9d ago), licensed MIT. It adds 240 tokens to every session and 2,968 once invoked, about $0.0010 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 2026-10-08.
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