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Chain extract-research-questions into objective-codebase-research. Convenience wrapper for the Q+R phases of QRSPI.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
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.