plan-writing-gherkin-criteria

plan-writing-gherkin-criteria is a skill for Claude Code from wahidyankf/ose-public. It costs 52 tokens per session (1,013 once invoked), scanned A, original, MIT.

A guide to writing acceptance criteria in Gherkin, a structured format using Given, When, and Then to describe expected behaviour.

In plain words
What is it for?
Use it to specify user stories, authentication, create-read-update-delete features, validation rules, and other expected behaviours.
Why use it?
It turns vague feature requirements into examples that people can understand and tests can check, including errors and edge cases.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to specify user stories, authentication, create-read-update-delete features, validation rules, and other expected behaviours.

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Install with agentmods
npx agentmods add skills/wahidyankf/ose-public/plan-writing-gherkin-criteria
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 wahidyankf/ose-public --skill plan-writing-gherkin-criteria
Clone the repo
git clone --depth 1 https://github.com/wahidyankf/ose-public

Made for: Claude Code.

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.

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README.md
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Your own site
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Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,013 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 $0.00052 $0.01013
Opus 5.5 $0.00021 $0.00405
Sonnet 5.5 $0.00010 $0.00203
Haiku 4.5 $0.00005 $0.00101

Measured 2d ago against content hash 4aff9951ca98, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

plan-writing-gherkin-criteria 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 2d 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.

.agents/skills/plan-writing-gherkin-criteria/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gherkin Acceptance Criteria Skill

Purpose

This Skill provides comprehensive guidance for writing Gherkin acceptance criteria using Given-When-Then syntax to create clear, testable specifications for features and user stories.

When to use this Skill: writing acceptance criteria for user stories, defining testable requirements in plans, specifying expected behaviour for features, and documenting edge cases and error handling.

Core Concepts

What is Gherkin?

Gherkin is a structured language for writing acceptance criteria using Given-When-Then syntax. It enables:

  • Clear communication: Non-technical stakeholders understand requirements
  • Testable specifications: Scenarios map directly to automated tests
  • Complete coverage: All scenarios and edge cases documented
  • Unambiguous expectations: No room for interpretation

Given-When-Then Structure

Anatomy of a scenario:

Scenario: [Brief description of scenario]
  Given [Initial context/preconditions]
  When [Action or event occurs]
  Then [Expected outcome/postconditions]

Breakdown:

  • Given: Sets up the context (initial state, preconditions, setup)
  • When: Describes the action or event (user action, system event, trigger)
  • Then: Specifies expected outcome (assertions, verification, results)

Journey Coherence

See Journey Coherence for the full rule text, conforming/non-conforming examples, and the canonical convention link.

Basic Scenario Patterns

See Basic Scenario Patterns for three worked patterns: simple success path, error handling, and boundary conditions.

Advanced Gherkin Features

See Advanced Gherkin Features for Background blocks, Scenario Outline with Examples tables, and Data Tables.

Common Domain Patterns

See Domain Patterns — Auth and CRUD and Domain Patterns — Form Validation and API Responses for worked full-feature examples across authentication, CRUD, form validation, and API responses.

Read the full file on GitHub · 110 lines

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. 2d ago First seen · 110 lines · 52 tokens per session scan A 4aff9951ca98

Subscribe to this mod's changes

plan-writing-gherkin-criteria is a skill published in the GitHub repository wahidyankf/ose-public (12 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 1,013 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 2026-10-14.