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Chain extract-research-questions into objective-codebase-research. Convenience wrapper for the Q+R phases of QRSPI.
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
The skill for "is this AI-written?" or "make this sound more human." Use whenever a specific text sample is in question and the core concern is AI authenticity — student submissions suspected of AI authorship, blog/wiki drafts that feel off, PR commit messages that smell like boilerplate, cover letters that sound robotic, paragraphs an editor flagged. Detects copula avoidance, ChatGPT vocabulary, significance inflation, and 30+ other documented AI tells. Also rewrites flagged sections. Not for grammar checks, summarization, or style edits where AI detection is not the concern.
Draft a structured design discussion from research findings. Interactive — presents understanding for corrections before finalizing.
Create a structure outline with vertical slices from a design discussion document. Enforces vertical decomposition over horizontal layers.
Extract 5-10 codebase research questions from a ticket or description. Questions only — no answers or opinions.
Conduct problem-aware, solution-blind codebase research. Outputs factual findings only — no opinions or suggestions.
Extract one durable lesson from a session into AGENTS.md. Invoke with a session ID to review a past session.
| name | research-and-questions |
| description | Chain extract-research-questions into objective-codebase-research. Convenience wrapper for the Q+R phases of QRSPI. |
| allowed-tools | ["Skill","Read","Glob","Grep","Bash(acli:*)"] |
Convenience wrapper that chains the Question and Research stages of the QRSPI workflow.
Reduces the workflow from 7 manual steps to 5 by combining:
/extract-research-questions — generates 5-10 research questions from a ticket/objective-codebase-research — investigates those questions in the codebaseDetermine input type:
[A-Z]+-\d+): Fetch ticket via acli jira workitem view <ID> and use the outputCall Skill(skill='extract-research-questions') with the user's input.
The skill will produce:
Call Skill(skill='objective-codebase-research') with the output from Step 2.
Pass the problem statement and acceptance criteria — NOT any proposed solution from the ticket.
Tell the user where the research document was saved and summarize the key findings.
The research document is now ready for /draft-design-discussion.