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 krillinai/growth-skills --skill incentive-system-designgit clone --depth 1 https://github.com/krillinai/growth-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/krillinai/growth-skills/incentive-system-design)<a href="https://agentmods.dev/skills/krillinai/growth-skills/incentive-system-design"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/incentive-system-design/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/krillinai/growth-skills/incentive-system-design"><img src="https://agentmods.dev/badge/skills/krillinai/growth-skills/incentive-system-design.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 | $0.00104 | $0.02036 |
| Opus 5 | $0.00052 | $0.01018 |
| Sonnet 5 | $0.00021 | $0.00407 |
| Haiku 4.5 | $0.00010 | $0.00204 |
Grade A, and why
incentive-system-design 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 12d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incentive System Design
Design incentives to remove a specific barrier to real customer or network value, then keep only behavior whose retained incremental contribution exceeds full marginal cost and harm. An incentive can accelerate value discovery or coordination; it cannot manufacture Product-Market Fit, make attributed activity incremental, or turn reward-dependent behavior into retention.
Read incentive-contract.md before accepting eligibility, behavior, reward, exposure, cost, cohort, or risk evidence. Read economics-and-incrementality.md before calculating lift, full cost, retained incremental value, payback, cannibalization, or portfolio allocation. Read mechanism-risk-and-governance.md before selecting reward mechanics, fraud controls, fairness rules, fulfillment, taper, or stop conditions. Read output-contract.md before delivery. Use playbook-sources.md to cite the pinned Growth Playbook basis.
Select One Mode
| Mode | Use |
|---|---|
audit |
Evaluate an existing program, result, economics claim, risk system, or retained-value effect |
design |
Define a bounded incentive hypothesis, pilot, eligibility, reward, measurement, risk, taper, and stop contract |
portfolio |
Compare programs, markets, segments, or reward tiers using marginal retained value, capacity, risk, and strategic dependence |
Name one primary mode, decision, owner, target behavior, customer or network value, eligible population, horizon, budget, and external-action boundary. If private evidence is unavailable, return a public-evidence-bounded hypothesis and measurement plan, not a score or causal claim.
Freeze The Incentive Contract
Record product, market, lifecycle role, participant sides and entities; value, natural frequency, behavioral barrier, target action, non-incentive alternatives, and counterfactual; eligible and excluded populations; reward type, amount, currency, payer, recipient, timing, visibility, terms, expiration, settlement, reversal, liability, and dispute rules; assignment or eligibility, exposure, action, fulfillment, outcome, identity, deduplication, cohort, window, cutoff, and maturity; organic baseline, holdout, attribution and incrementality basis; full cost, contribution, payback, budget, capacity, and uncertainty; fraud, cannibalization, quality, trust, fairness, accessibility, privacy, compliance, and support; taper, stop, owners, sources, evidence states, and requested external actions.
What ships with it
5 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.
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.
- 12d ago First seen · 86 lines · 104 tokens per session scan A 8494a5fb6bf8
incentive-system-design is a skill published in the GitHub repository krillinai/growth-skills (43 stars, last pushed 15d ago), licensed MIT. It adds 104 tokens to every session and 2,036 once invoked, about $0.0005 per session on Opus 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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