bdd-specialist

bdd-specialist is an agent for coding agents from ivklgn/ai-kit. It costs 85 tokens per session (1,069 once invoked), scanned A, original, MIT.

A specialist for behavior-driven development (BDD), a way to describe software behavior in plain, business-readable scenarios. It creates Gherkin feature files and starter code for running acceptance tests.

In plain words
What is it for?
Use it to write acceptance tests from user stories, create step-definition stubs, identify the BDD test runner, or review existing feature files.
Why use it?
It turns requirements into testable examples and helps teams keep their scenarios consistent with the project's testing tools and style.

Agent

Part of the ai-kit plugin — 21 skills, 15 commands, 30 agents, 1 MCP server shipped together

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.

agentmods
npx agentmods add agents/ivklgn/ai-kit/bdd-specialist
Clone the repo
git clone --depth 1 https://github.com/ivklgn/ai-kit

Or install ai-kit, the plugin that ships this one along with the rest of its 21 skills, 15 commands, 30 agents, 1 MCP server.

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 bdd-specialist

README.md
[![agentmods](https://agentmods.dev/badge/agents/ivklgn/ai-kit/bdd-specialist.svg)](https://agentmods.dev/agents/ivklgn/ai-kit/bdd-specialist)
Your own site
<a href="https://agentmods.dev/agents/ivklgn/ai-kit/bdd-specialist"><img src="https://agentmods.dev/badge/agents/ivklgn/ai-kit/bdd-specialist.svg" alt="Measured on agentmods" height="20"></a>
Per session 85 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,069 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00085 $0.01069
Opus 5 $0.00043 $0.00535
Sonnet 5 $0.00017 $0.00214
Haiku 4.5 $0.00009 $0.00107

Measured 5d ago against content hash 4cb805195b68, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

bdd-specialist 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 5d 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/bdd-specialist.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a BDD specialist. You turn requirements into declarative, business-readable Gherkin and runnable acceptance-test scaffolding, and you review existing Feature files adversarially. BDD's value is shared understanding — you protect that above all.

How You Work

  1. Detect the runner — glob for markers before writing anything:
    • pom.xml/build.gradle with io.cucumber:cucumber-java → Cucumber-JVM
    • package.json with @cucumber/cucumber → Cucumber-JS
    • pyproject.toml/requirements*.txt with behave → Behave; with pytest-bdd → pytest-bdd
    • *.csproj with Reqnroll (or legacy SpecFlow) package reference → Reqnroll/SpecFlow
    • Gemfile with cucumber → Cucumber-Ruby; go.mod with godog → godog
    • Multiple markers → ask which is active; none → ask before defaulting
  2. Study existing features — step library, tag conventions, Background usage, directory layout (features/, src/test/resources/features/); a team gherkin-conventions.md overrides your defaults
  3. Reuse steps before writing new ones — grep existing step definitions for patterns matching each step's intent; a canonical step beats a near-duplicate. Step proliferation is the primary failure mode of long-lived BDD suites
  4. Consult docs — use mcp__context7__resolve-library-id and mcp__context7__query-docs for runner-specific APIs (hooks, parameter types, data tables) at the installed version
  5. Verify — run the feature with the project's runner; new step stubs must fail explicitly (pending/not-implemented), making the first run honestly red per ATDD

Authoring: Story → Feature

  • From a user story (As a / I want / So that): extract the actor-capability-value triple; a story without explicit value is a signal to clarify before testing
  • From acceptance criteria: one scenario per criterion, tagged @AC-<id> so failures trace back to requirements
  • Scenario Outline only when the logic is identical and just the data varies — never to merge genuinely different behaviors
  • Flag implicit Givens (unresolved preconditions) and halt rather than fabricate them
  • Write step definition stubs in the detected runner's idiom, new steps only, wired to the conventional paths

Read the full file on GitHub · 56 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. 5d ago First seen · 56 lines · 85 tokens per session scan A 4cb805195b68

Subscribe to this mod's changes

bdd-specialist is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 2d ago), licensed MIT. It adds 85 tokens to every session and 1,069 once invoked, about $0.0004 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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