answer-reviewer-questions
For each reviewer question on a PR, recall implementation reasoning and compose a raw answer. Use when the user asks to "answer reviewer questions", "draft answers to PR questions", or "explain reviewer questions".
What it does
Answer Reviewer Questions
For each reviewer question thread, recall the implementer's reasoning and compose a raw answer. The answers are plain text and feed into a downstream reply-drafting skill that applies voice rules and reply formatting.
Step 1: Collect Question Threads
Use the question threads from conversation context. Each thread has: thread id, file path, line (use originalLine when line is null), the reviewer's original comment, and the reconciled intent from /interpret-feedback.
If no question threads were provided, report that there are no questions to answer and stop.
Step 2: Answer Each Thread
For each thread:
- Run the
/recall-reasoningskill with<path>:<line>. It returns either recalled reasoning from a past transcript, or a fallback derived from reading the commit diff and surrounding code. - Compose a one-or-two-sentence answer from the returned reasoning. Quote or paraphrase the implementer's own words when the recalled reasoning explains the decision well.
- Do not mention Claude, transcripts, or that the reasoning was recalled. The answer reads as the implementer's own explanation.
Step 3: Output Answers
Output one block per thread:
**Thread <id>** (<path>:<line>)
<answer text>
_Grounding: derived from current code_
Include the _Grounding:_ line only when /recall-reasoning returned no transcript. Omit it when the answer is grounded in recalled reasoning.
Then use the TaskList tool and proceed to any remaining task.
Rules
- Do not load
/github-voiceor apply reply formatting. Downstream drafting applies voice rules when composing the actual reply. - When
/recall-reasoningreturned no transcript, still compose an answer from the current code and include the_Grounding:_line so the downstream drafter knows the answer has weaker grounding.
Capabilities
Install
Quality
deterministic score 0.59 from registry signals: · indexed on github topic:agent-skills · 280 github stars · SKILL.md body (1,848 chars)