gherkin-to-code

gherkin-to-code is a skill for Claude Code from cuongtl1992/vibe-skills. It costs 125 tokens per session (2,600 once invoked), scanned A, original, MIT.

A workflow that turns Gherkin feature files into implementation plans, step definitions, and business logic code. Feature files are behavior specifications written as scenarios for people and software to share.

In plain words
What is it for?
Use it to analyze rules and scenarios, design the technical solution, implement the feature, and create the related test steps.
Why use it?
It gives developers a structured path from agreed behavior to code and verification.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; mentions Claude Code.

Part of the ai-first-engineering plugin — 4 skills shipped together

Good fit Use it to analyze rules and scenarios, design the technical solution, implement the feature, and create the related test steps.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cuongtl1992/vibe-skills/gherkin-to-code
Install

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.

Any agent
npx skills add cuongtl1992/vibe-skills --skill gherkin-to-code
Clone the repo
git clone --depth 1 https://github.com/cuongtl1992/vibe-skills

Made for: Claude Code.

Or install ai-first-engineering, the plugin that ships this one along with the rest of its 4 skills.

Wrote 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.

agentmods badge for gherkin-to-code

README.md
[![agentmods](https://agentmods.dev/badge/skills/cuongtl1992/vibe-skills/gherkin-to-code/github.svg)](https://agentmods.dev/skills/cuongtl1992/vibe-skills/gherkin-to-code)
Your own site
<a href="https://agentmods.dev/skills/cuongtl1992/vibe-skills/gherkin-to-code"><img src="https://agentmods.dev/badge/skills/cuongtl1992/vibe-skills/gherkin-to-code/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.

agentmods 80×15 button for gherkin-to-code

Your own site · 80×15
<a href="https://agentmods.dev/skills/cuongtl1992/vibe-skills/gherkin-to-code"><img src="https://agentmods.dev/badge/skills/cuongtl1992/vibe-skills/gherkin-to-code.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,600 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00125 $0.02600
Opus 5 $0.00063 $0.01300
Sonnet 5 $0.00025 $0.00520
Haiku 4.5 $0.00013 $0.00260

Measured 11d ago against content hash 9f480e0a7d73, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

gherkin-to-code 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 11d 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.

plugins/ai-first-engineering/skills/gherkin-to-code/SKILL.md · 313 lines

How it starts

The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gherkin to Code — Feature Implementation

Đọc Gherkin feature file từ living docs → phân tích technical solution → gen step definitions + implementation code. Skill này là bridge từ WHAT (feature file) sang HOW (code).

Triết lý

Feature file là contract. Code phải thỏa mãn contract đó — không hơn, không kém.

Skill này KHÔNG quyết định stack, framework, hay conventions — đó là việc của CLAUDE.md và existing code trong repo. Skill này chỉ hướng dẫn process: đọc gì → phân tích gì → gen gì → verify gì.

Ngôn ngữ

  • Code comments, commit messages: theo convention repo (CLAUDE.md)
  • Technical solution summary: tiếng Việt (consistent với PRD và feature file)
  • Code: theo ngôn ngữ lập trình của repo

Phase 1 — Technical Analysis (bắt buộc, engineer review trước khi code)

Phase này là bước architecture cho feature-level. KHÔNG skip — gen code mà không có technical analysis sẽ dẫn tới refactor.

1.1. Đọc và hiểu feature file

Input: .feature file (hoặc nhiều files nếu feature span nhiều module)

Extract:
├── Feature name + narrative → hiểu context
├── Rules → list business rules cần implement
├── Scenarios per Rule → behaviors cần thỏa mãn
├── Tags → test layer (@api/@web/@integration), priority (@p2/@future)
├── # PRD link → đọc PRD nếu cần thêm context
└── # TODO comments → decisions chưa resolve

1.2. Scan codebase hiện tại

Đọc repo qua git submodule hoặc trực tiếp:

Scan:
├── CLAUDE.md → stack, conventions, patterns
├── Existing step definitions → pattern đang dùng
├── Domain models / entities → data model hiện tại
├── API routes / controllers → endpoints hiện có
├── Database schema → tables, relationships
└── Related features code → follow existing patterns

1.3. Đề xuất Technical Solution

Output dạng summary để engineer review:

## Technical Solution: [Feature Name]

### Tổng quan
[1-2 câu: approach chính để implement feature này]

### Components cần thay đổi

| Component | Thay đổi | Lý do (Rule ID) | Impact |
|-----------|----------|-----------------|--------|
| [service/module] | [new/modify/extend] | [BR-Mxx] | [low/medium/high] |

### Data model changes
| Entity | Thay đổi | Fields | Migration? |
|--------|----------|--------|-----------|
| [entity] | [new table / add columns / modify] | [field list] | [yes/no] |

### API changes
| Endpoint | Method | Thay đổi | Guards (Rules) |
|----------|--------|----------|---------------|
| [path] | [GET/POST/...] | [new/modify] | [BR-Mxx] |

### Quyết định kỹ thuật
- [Decision 1]: [option chọn] — *lý do: [ngắn gọn]*
- [Decision 2]: [option chọn] — *lý do: [ngắn gọn]*

### Breaking changes
- [ ] [Mô tả breaking change nếu có] → *ảnh hưởng: [ai/service nào]*

### Implementation order
1. [Component/step đầu tiên] — *vì: [dependency reason]*
2. [Component/step tiếp theo]
3. ...

Read the full file on GitHub · 313 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 11d ago First seen · 313 lines · 0 tokens per session scan A 9f480e0a7d73

Subscribe to this mod's changes

gherkin-to-code is a skill published in the GitHub repository cuongtl1992/vibe-skills (10 stars, last pushed 5mo ago), licensed MIT. It adds 125 tokens to every session and 2,600 once invoked, about $0.0006 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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