codex-spec-interviewer

Interview users to capture requirements and draft Codex-executable implementation specs.

4|1|Updated May 19, 2026
One-click install
npx skills add https://github.com/stark-ai-de/agent-skills --skill codex-spec-interviewer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: codex-spec-interviewer
Source: https://github.com/stark-ai-de/agent-skills/tree/main/skills/codex-operations/codex-spec-interviewer
Command: npx skills add https://github.com/stark-ai-de/agent-skills --skill codex-spec-interviewer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill transforms user requests into detailed, Codex-executable implementation specs, streamlining the process of requirement capture, decision-making, and execution planning.

Core Features & Use Cases

  • Spec Creation: Guides users through defining the scope, requirements, and acceptance criteria for software features.
  • Source Challenge: Validates assumptions and decisions against repository and external sources.
  • ADR Integration: Integrates architectural decision records for durable design choices.
  • Validation and Rollout: Provides guidelines for testing, rollback, and deployment planning.
  • Use Case: Ideal for users who need to capture detailed feature specifications, ensuring that all requirements are understood and documented before development begins.

Quick Start

Use the codex-spec-interviewer skill to guide the creation of an implementation spec for a new feature in the 'project-repo'.

Frequently Asked Questions about codex-spec-interviewer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn user requests into implementation specs for Codex execution?

To turn user requests into implementation specs, you need an interview-based process that captures requirements, validates assumptions against source code, and gates architectural decisions. This produces spec artifacts and execution prompts for automated agents.

What is an architectural decision record and when do I need it for feature specification?

An architectural decision record (ADR) documents durable design choices made during feature specification. You need ADR integration when planning complex software features to ensure architectural decisions are validated, documented, and aligned with repository context before development begins.

How do I capture software requirements and control scope before development begins?

To capture requirements and control scope, conduct structured user interviews to define feature scope, acceptance criteria, and constraints. Validate assumptions through source challenges against repository documentation to ensure all requirements are understood and documented.

Do I need repository context and Plan mode to draft Codex-executable implementation specs?

Yes, you need active repository context and Plan mode access to draft Codex-executable implementation specs. Access to architectural decision records and existing documentation is also required to validate assumptions and gate design choices during the interview process.

What is the best way to validate assumptions and decisions against repository sources?

The best way to validate assumptions against repository sources is to perform source challenges during the specification interview. This mechanism cross-references user requests and architectural decisions with existing repository documentation to ensure feasibility and scope control.

What are the limitations of using automated specification interviews for implementation planning?

Automated specification interviews require active Plan mode, repository context, and accessible architectural decision records. If repository documentation is sparse or inaccessible, the tool cannot effectively validate assumptions or gate architectural decisions, limiting its ability to produce executable specs.