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 agentmods add skills/vthinkdeveloper/vthink-agent-toolkit/bdd-gherkinnpx skills add vthinkdeveloper/vthink-agent-toolkit --skill bdd-gherkingit clone --depth 1 https://github.com/vthinkdeveloper/vthink-agent-toolkitWrote 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/vthinkdeveloper/vthink-agent-toolkit/bdd-gherkin)<a href="https://agentmods.dev/skills/vthinkdeveloper/vthink-agent-toolkit/bdd-gherkin"><img src="https://agentmods.dev/badge/skills/vthinkdeveloper/vthink-agent-toolkit/bdd-gherkin.svg" alt="Measured on agentmods" 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 | $0.00063 | $0.01702 |
| Opus 5 | $0.00032 | $0.00851 |
| Sonnet 5 | $0.00013 | $0.00340 |
| Haiku 4.5 | $0.00006 | $0.00170 |
Grade A, and why
bdd-gherkin 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 3d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BDD Gherkin Scenario Generator
Overview
This skill turns requirements — even rough, vague, or incomplete ones — into comprehensive BDD Gherkin scenarios. Instead of analyzing code, it collaborates with the user through focused questions to surface the full picture before writing scenarios.
The key insight: most requirements start vague. "Users should be able to reset their password" sounds simple until you ask about email delivery failures, expired tokens, and locked accounts. This skill's job is to ask those questions early, then write scenarios that capture the answers.
Workflow
Step 1: Receive the Requirement
The user provides a requirement. It could be anything from a one-liner to a detailed spec. Accept whatever they give without complaint — your job is to work with it.
Examples of inputs you should handle well:
- "Users should be able to export reports"
- "We need an admin page to manage user roles"
- "Add filtering to the dashboard"
- A Jira ticket description pasted in
- A screenshot of a mockup or wireframe
- A bullet-point list of desired behaviors
Step 2: Understand and Clarify (The Collaborative Part)
This is the most important step. Before writing any Gherkin, have a short conversation to fill in the gaps. Your goal is to ask just enough questions to write meaningful scenarios — not to interrogate the user into exhaustion.
How to ask questions:
Use the AskUserQuestion tool to present focused, structured questions. Group related questions together. Offer concrete options where possible so the user can pick rather than think from scratch.
What to probe for:
| Gap to fill | Example questions |
|---|---|
| Who — the actor(s) | "Who performs this action? Admin only, any logged-in user, or unauthenticated users too?" |
| What — the core action | "When you say 'export', what formats? PDF, Excel, CSV, all of them?" |
| When — triggers and preconditions | "Can they do this anytime, or only when certain conditions are met?" |
| Where — the UI context | "Is this on a dedicated page, a modal, or part of an existing screen?" |
| What if — failure and edge cases | "What should happen if the export fails? Retry? Error message? Silent failure?" |
| Who else — impact on others | "Should other users be able to see/access the exported file?" |
| Boundaries — limits and constraints | "Is there a max number of rows? A timeout? Size limit?" |
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.
- 3d ago First seen · 137 lines · 63 tokens per session scan A fe89406afa47
bdd-gherkin is a skill published in the GitHub repository vthinkdeveloper/vthink-agent-toolkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 1,702 once invoked, about $0.0003 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 2026-08-31.
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