Results for “requirements”

Guides a structured brainstorm that surfaces user ideas, explores directions, and produces a spec and report for later planning.

Guides users through a structured interview to clarify their AI agent idea and produces an Agent Requirement Document (ARD).

Designs system architecture and translates requirements into actionable plans, creating PRDs and tasks via Task Copilot.

Update an existing implementation plan file with new or updated requirements for features, refactoring, package upgrades, design, architecture, or infrastructure.

Interviews the user in depth about a plan, probing technical implementation, UI/UX, risks, tradeoffs, and missing decisions before writing or refining a spec.

Guides a structured interview and codebase exploration to produce a PRD, then submits it as a GitHub issue.

Formaliza una idea como propuesta de cambio antes de invertir tiempo en especificaciones y diseño, alineando contexto, alternativas, impacto y criterios de éxito.

Designs an approval-gated feature specification from approved requirements, covering architecture decisions, component boundaries, quality constraints, and definition of done.

Breaks a product requirements document into independently-grabbable GitHub issues using vertical slices, with user approval before creation.

Turns product ideas into structured specs for AI tools or stakeholder review, with quick feature specs and full project scopes.

Synthesizes the current conversation and codebase context into a structured PRD and publishes it to the project issue tracker with a triage label.

Turns the current conversation context and codebase understanding into a PRD and publishes it to the project issue tracker with a triage label.

Runs a structured, multi-round brainstorm to capture actors, features, scope, constraints, and business rules for a project before writing a spec.

Generates a high-level technical architecture specification for an epic from a Product Requirements Document, including system diagrams, component lists, and estimates.

Writes user-focused acceptance criteria for Jira stories using Given/When/Then scenarios, and updates the ticket via the Atlassian MCP server.

Exports a platform feature as a product constitution and data reference, including data model, API contracts, and acceptance criteria, for use in AI prototyping tools.

Write and refine user stories using INVEST criteria, the 'As a X, I want Y, so that Z' format, Gherkin acceptance criteria, definition of ready, anti-patterns, and a review checklist.

Translate a vague request or GitHub issue into a concrete, testable spec using five structured elements (problem, scope, acceptance criteria, edge cases, success criterion) before writing any code. Prevents scope creep, PR churn, and mid-implementation pivots.

Turns a raw idea, brain dump, or conversation into a complete PRD with mandatory acceptance criteria and measurable success metrics. Extracts the problem, target users, and jobs-to-be-done, runs a quick competitive scan (web if available, logged as a gap if not), drafts the full PRD (problem, personas, user stories.