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 nWave-ai/nWave --skill nw-outcome-kpi-frameworkgit clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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/nwave-ai/nwave/nw-outcome-kpi-framework)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-outcome-kpi-framework"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-outcome-kpi-framework/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/nwave-ai/nwave/nw-outcome-kpi-framework"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-outcome-kpi-framework.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 | $0.00050 | $0.02310 |
| Opus 5.5 | $0.00020 | $0.00924 |
| Sonnet 5.5 | $0.00010 | $0.00462 |
| Haiku 4.5 | $0.00005 | $0.00231 |
Grade A, and why
nw-outcome-kpi-framework 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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outcome KPI Framework
"Doing stuff isn't the point. Achieving stuff is." -- Jeff Gothelf
Defines measurable outcome KPIs for user stories and features. Loaded during Phase 4 (Requirements Crafting) to produce outcome-kpis.md. Synthesizes three frameworks: customer-centric OKRs, lean metrics, and OKR methodology.
The Outcome KPI Formula
Primary template from Gothelf/Seiden. Every KPI answers five questions:
| Component | Question | Example |
|---|---|---|
| Who | Which user segment? | Returning customers with 2+ orders |
| Does What | What observable behavior changes? | Complete checkout without contacting support |
| By How Much | What is the measurable target? | 40% reduction in support tickets |
| Measured By | How do we collect the data? | Support ticket system + checkout analytics |
| Timeframe | When do we measure? | 30 days post-release, then weekly |
Formula: [Who] [Does what] [By how much]
Apply as litmus test: if a KPI cannot answer all five components, it measures an output (feature delivery), not an outcome (behavior change).
Good vs Bad KPIs
| Bad (Output) | Good (Outcome) |
|---|---|
| Launch mobile app v2 | Mobile users complete purchases 40% more often |
| Build recommendation engine | Users purchase from recommendations, increasing from 10% to 25% |
| Deploy onboarding redesign | New users complete onboarding within 24 hours 30% more often |
| Ship CSV export | Analysts resolve data questions without engineering support 60% of the time |
Leading vs Lagging Indicators
From Gothelf/Seiden: business results are lagging -- teams cannot directly influence them. Target leading indicators instead.
| Type | Definition | Examples | Actionable? |
|---|---|---|---|
| Lagging (Impact) | Business results already happened | Revenue, NPS, market share, churn rate | No -- too slow, too many variables |
| Leading (Outcome) | Behavior changes predicting business results | Purchase completion rate, feature adoption, retention | Yes -- teams can run experiments |
| Leading (Secondary) | Behaviors predicting primary leading indicators | Page visits, trial starts, onboarding steps completed | Yes -- most granular, fastest signal |
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 · 222 lines · 50 tokens per session scan A 9e9bf77b0af5
nw-outcome-kpi-framework is a skill published in the GitHub repository nWave-ai/nWave (620 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 2,310 once invoked, about $0.0002 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 2026-09-03.
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