Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/nWave-ai/nWavenpx agentmods add skills/nwave-ai/nwave/nw-bdd-methodologyWrote 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-bdd-methodology)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-bdd-methodology"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-bdd-methodology/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-bdd-methodology"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-bdd-methodology.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 | $0.00036 | $0.01278 |
| Opus 5 | $0.00018 | $0.00639 |
| Sonnet 5 | $0.00007 | $0.00256 |
| Haiku 4.5 | $0.00004 | $0.00128 |
Grade A, and why
nw-bdd-methodology 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 9d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BDD Methodology for Acceptance Test Design
Core Philosophy
Test units of behavior, not units of code. Acceptance tests validate business outcomes through public interfaces, decoupled from implementation.
Outside-In Double-Loop TDD
The acceptance-designer creates the outer loop of Outside-In TDD. Development starts from user perspective, drives inward.
Outer loop (acceptance/BDD): Hours to days | User perspective, business language | Defines "done" | Scenarios describe user goals and observable outcomes, not internals | Failing outer-loop test is the starting signal for implementation
Inner loop (unit/TDD): Minutes | Developer perspective, technical terms | Software-crafter owns this loop
Workflow:
- Write failing acceptance test from user perspective (outer loop -- outside)
- Software-crafter drops to inner loop: unit tests to implement components (inside)
- Iterate inner loop until acceptance test passes
- Passing acceptance test proves user value delivered
- Repeat for next behavior
Outer loop defines WHAT users need (outside). Inner loop drives HOW to build it (inside).
Given-When-Then Structure
Scenario: [Business-focused title describing one behavior]
Given [preconditions - system state in business terms]
When [single user action or business event]
Then [observable business outcome]
Scenario Writing Rules
Rule 1: One scenario, one behavior -- Split multi-behavior scenarios.
Rule 2: Declarative, not imperative -- Business outcomes, not UI interactions. "When I log in with valid credentials" not "When I click Login button and enter email."
Rule 3: Concrete examples, not abstractions -- "Given my account balance is $100.00" not "Given the user has sufficient funds."
Rule 4: Keep scenarios short (3-5 steps) -- Longer means testing multiple behaviors or irrelevant details.
Rule 5: Background for shared Given steps only -- Only Given steps. Actions/validations in scenarios.
Scenario Categorization
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.
- 9d ago First seen · 151 lines · 36 tokens per session scan A d7b984b8b643
nw-bdd-methodology is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 3d ago), licensed MIT. It adds 36 tokens to every session and 1,278 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 2026-08-30.
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