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-jtbd-opportunity-scoringgit 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-jtbd-opportunity-scoring)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-jtbd-opportunity-scoring"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-jtbd-opportunity-scoring/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-jtbd-opportunity-scoring"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-jtbd-opportunity-scoring.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 | $0.00035 | $0.01814 |
| Opus 5 | $0.00017 | $0.00907 |
| Sonnet 5 | $0.00007 | $0.00363 |
| Haiku 4.5 | $0.00003 | $0.00181 |
Grade A, and why
nw-jtbd-opportunity-scoring 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JTBD Opportunity Scoring
Use when prioritizing features, stories, or backlog items based on customer-defined outcomes. Opportunity scoring (Ulwick's ODI) replaces gut-feel prioritization with evidence-based ranking.
Outcome Statements
Every customer need expressed as a desired outcome following strict format:
[Direction] + the [metric] + [object of control] + [contextual clarifier]
- Direction: "Minimize" or "Maximize"
- Metric: time, likelihood, number, or frequency
Examples
- "Minimize the time it takes to identify the root cause of a production issue"
- "Minimize the likelihood of deploying untested code to production"
- "Maximize the likelihood that acceptance criteria cover all relevant scenarios"
- "Minimize the number of iterations needed to reach shared understanding"
- "Minimize the frequency of false positive alerts during monitoring"
Quality Checks
Outcome statement must be: Solution-free (no specific technology) | Measurable (ratable on importance/satisfaction 1-5) | Controllable (customer can assess improvement) | Unambiguous (same interpretation by all stakeholders)
Deriving Outcome Statements
Walk the 8-step job map (see jtbd-core skill) and generate 2-3 per step. Produces 16-24 outcome statements per job -- comprehensive view of customer needs.
| Job Map Step | Outcome Statement Pattern |
|---|---|
| Define | "Minimize the time to determine [what is needed]" |
| Locate | "Minimize the likelihood of missing [required input]" |
| Prepare | "Minimize the time to set up [environment/context]" |
| Confirm | "Minimize the likelihood of proceeding with [invalid state]" |
| Execute | "Minimize the time to complete [core action]" |
| Monitor | "Minimize the likelihood of [undetected failure]" |
| Modify | "Minimize the time to recover from [exception]" |
| Conclude | "Minimize the likelihood of [incomplete cleanup]" |
The Opportunity Algorithm
Opportunity Score = Importance + max(0, Importance - Satisfaction)
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 · 168 lines · 35 tokens per session scan A 26c943e89014
nw-jtbd-opportunity-scoring is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 5d ago), licensed MIT. It adds 35 tokens to every session and 1,814 once invoked, about $0.0002 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 2026-09-03.
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