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Review and improve editorial prose quality and clarity. Use when the user asks for editorial prose review.
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
| name | editorial-prose |
| description | Review and improve editorial prose quality and clarity. Use when the user asks for editorial prose review. |
| metadata | {"managed-by":"bmalph"} |
This wrapper requires local BMALPH assets under _bmad/, which this repository intentionally keeps out of git.
If _bmad/ is missing in a fresh clone or workspace, run make bmalph-setup first.
If BMALPH is already installed and you need to restore local files or reapply this repository's planning artifacts under specs/, rerun make bmalph-setup.
Read and execute the workflow/task at _bmad/core/skills/bmad-editorial-review-prose/workflow.md.
Systematically retrieve and address PR code review comments using make pr-comments. Use when handling code review feedback or addressing PR comments.
Codex entrypoint for post-implementation BMAD FR/NFR review gates. Use after a PR, feature, or bugfix has BMAD specs and must be checked against every functional requirement, non-functional requirement, expanded quality dimension, Wikipedia system quality attribute, generated positive/negative/ edge test case, automated test and CI coverage expectation, flaky-test risk, whole-codebase impact surface, manual-test expectation, GitHub review comments and requested-changes state, and CI check before completion.
Run a BMAD spec-driven post-implementation review gate. Use after implementing a GitHub PR, feature, bugfix, or task with BMAD specs to verify every FR/NFR, pinned NonFunctionals.com NFR category, expanded quality dimension, Wikipedia system quality attribute, positive/negative/edge test case, automated test and CI coverage expectation, flaky-test risk, whole-codebase impact surface, manual test expectation, QA best practice, GitHub review comments and requested-changes state, and CI check before completion.
Design LLM-powered modules with Clean Architecture boundaries, SOLID, DRY, KISS, and provider-agnostic ports/adapters. Use when adding prompt workflows, model/provider clients, tool orchestration, AI review automation, agent skills, or other LLM-backed capabilities.
advanced elicitation. Use when the user asks about advanced elicitation.
adversarial review. Use when the user asks about adversarial review.
