mpiton/agentic-atdd/spec-generate

Claude Code and agent skill by mpiton/agentic-atdd

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Generate Gherkin acceptance scenarios from a context.md, with mandatory interview for ambiguities, concrete data, and test-level tags. Use after impact-map, or when the user provides a user story and rules and asks for scenarios.

Install

npx vskill@latest install mpiton/agentic-atdd/spec-generate

SKILL.md

/spec-generate

Generate Gherkin scenarios from specs/<us-slug>/context.md. The pipeline calls this skill in Phase 2 §3 of the diagram.

When to use

  • After impact-map produced context.md.
  • When the user pastes a structured story + rules and asks for acceptance scenarios.

Inputs

Workflow

1. Interview (mandatory before generation)

Read context.md first, and treat it as answered ground. impact-map (or from-issue / from-linear) already elicited the actor, the action, the goal, and the numbered rules — do NOT re-ask any of that. Re-interviewing fields the user already gave upstream is the main avoidable token cost in the spec phase; thread them forward instead.

Ask only the ambiguities that context.md does NOT already resolve — DO NOT guess on those. For each genuinely-new ambiguity, ask one focused question. Examples of things that always require a question if not already explicit in context.md:

  • Numeric thresholds without units ("limit of 100" — 100 what?).
  • Implicit time zones, date formats, currency.
  • Identity / equality semantics (case sensitivity, trimming).
  • Default values for omitted fields.
  • Behavior on the boundary itself (<= vs <).

Stop the interview only when every rule can be expressed with concrete, unambiguous data.

2. Generate scenarios

For each business rule R-NN, produce one .feature file at specs/<us-slug>/<rule-slug>.feature.

Each file MUST contain scenarios covering at least:

  • Nominal path (tag: @nominal).
  • Violation of the rule (tag: @violation).
  • Authorization path if the rule involves access (tag: @auth).
  • Technical / integration edge if applicable (tag: @technical).
  • Limits / boundaries for any numeric rule (tag: @limit).

Use concrete data (real values, not placeholders). Example: prefer Given the cart contains 3 items at 19.99 EUR over Given some items in the cart.

Add a # Rule: R-NN comment at the top of each feature file so traceability survives renames.

Triangulation: if a rule is complex, produce multiple examples (Scenario Outline with Examples:) rather than a single example.

3. Test-level tag

Tag each scenario by the appropriate test level:

  • @use-case — pure domain / use case test.
  • @e2e — end-to-end with the real adapters.
  • @ui — UI driver (Playwright, RTL, etc.).

If unsure, ask the user before generating.

Outputs

  • specs/<us-slug>/<rule-slug>.feature — one per business rule.

Handoff

Next: `spec-review` on the generated .feature files.

Anti-patterns

  • Don't generate scenarios for rules that are not in context.md. Push back, ask impact-map to capture them first.
  • Don't invent assertions; every assertion must trace to a rule.
  • Don't mock the system under test in the scenario data. Scenarios describe behavior, not implementation.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

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