ablation-planner
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says \"rebuttal\", \"reply to reviewers\", \"ICML rebuttal\", \"OpenReview
Claude Code
$ npx -y skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal --agent claude-code
Codex
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal -a codex -y
Cursor
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal -a cursor -y
Gemini CLI
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal -a gemini-cli -y
GitHub Copilot
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal -a github-copilot -y
OpenCode
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal -a opencode -y
Windsurf
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill rebuttal -a windsurf -y
name: rebuttal description: "Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says \"rebuttal\", \"reply to reviewers\", \"ICML rebuttal\", \"OpenReview response\", or wants to answer external reviews safely." argument-hint: "[paper-path-or-review-bundle]" allowed-tools: Bash(*), Read, Grep, Glob, Write, Edit, Skill, mcp__codex__codex, mcp__codex__codex-reply, mcp__manual_review__review, mcp__manual_review__review_reply, mcp__antigravity__antigravity, mcp__antigravity__antigravity-reply, mcp__grok__grok, mcp__grok__grok-reply, mcp__claude-review__review, mcp__claude-review__review_reply, mcp__claude-review__review_start, mcp__claude-review__review_reply_start, mcp__claude-review__review_status
> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md): > resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP) > with `reviewer_route.py` through the canonical helper resolver, preserving this > slot's tier, fresh contexts, source/image inputs and deterministic gates. > Codex examples/pins below apply only to `backend=codex`; other routes use their > own first-call/reply contract. Save the route and actual returned identity; > unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual > families/completion/scope. Forward invocation reviewer/model/effort overrides > to reviewer-bearing children. Generation workers are unchanged.
Prepare and maintain a grounded, venue-compliant rebuttal for: **$ARGUMENTS**
This skill is optimized for:
This skill does **not**:
If the user already has new results, derivations, or approved commitments, the skill can incorporate them as **user-confirmed evidence**.
Workflow 1: idea-discovery Workflow 1.5: experiment-bridge Workflow 2: auto-review-loop (pre-submission) Workflow 3: paper-writing Workflow 4: rebuttal (post-submission external reviews)
> Override: `/rebuttal "paper/" — venue: NeurIPS, character limit: 5000`
When calling the reviewer for stress-testing, branch on REVIEWER_BACKEND:
**If REVIEWER_BACKEND = `codex`:** Use `mcp__codex__codex` for new review threads. Use `mcp__codex__codex-reply` for follow-up rounds (reuse threadId).
**If REVIEWER_BACKEND = `manual`:** Use `mcp__manual_review__review` for new review threads with: prompt: [exact same prompt that would go to Codex] config: {"model_reasoning_effort": "xhigh", "executor_model": "<actual executor model>", "require_reviewer_model": true} Save the returned `threadId`. Use `mcp__manual_review__review_reply` for follow-up rounds with: threadId: [saved manual-review threadId] prompt: [follow-up prompt] config: {"model_reasoning_effort": "xhigh", "executor_model": "<actual executor model>", "require_reviewer_model": true}
Prompt fidelity: the manual
· · · · · · · · 💬 Join Community · 🌱 ARIS is a methodology, not a platform. What matters is the research workflow — take it wherever you go.
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
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