Agent skill

rebuttal

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.

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Install this agent skill to your Project

npx add-skill https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/rebuttal

SKILL.md

Workflow 4: Rebuttal

Prepare and maintain a grounded, venue-compliant rebuttal for: $ARGUMENTS

Scope

This skill is optimized for:

  • ICML-style text-only rebuttal
  • strict character limits
  • multiple reviewers
  • follow-up rounds after the initial rebuttal
  • safe drafting with no fabrication, no overpromise, and full issue coverage

This skill does not:

  • run new experiments automatically unless AUTO_EXPERIMENT = true
  • generate new theorem claims automatically
  • edit or upload a revised PDF
  • submit to OpenReview / CMT / HotCRP

Lifecycle Position

text
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)

Constants

  • VENUE = ICML — Default venue
  • RESPONSE_MODE = TEXT_ONLY — v1 default
  • REVIEWER_MODEL = gpt-5.4 — Used via a secondary Codex agent for internal stress-testing
  • MAX_INTERNAL_DRAFT_ROUNDS = 2
  • MAX_STRESS_TEST_ROUNDS = 1
  • MAX_FOLLOWUP_ROUNDS = 3
  • AUTO_EXPERIMENT = false — When true, invoke /experiment-bridge for reviewer concerns that require new evidence
  • QUICK_MODE = false — When true, only run Phase 0-3 and stop after strategy
  • REBUTTAL_DIR = rebuttal/

Override: /rebuttal "paper/" — venue: NeurIPS, character limit: 5000

Required Inputs

  1. Paper source — PDF, LaTeX directory, or narrative summary
  2. Raw reviews — pasted text, markdown, or PDF with reviewer IDs
  3. Venue rules — venue name, character/word limit, text-only or revised PDF allowed
  4. Current stage — initial rebuttal or follow-up round

If venue rules or limit are missing, stop and ask before drafting.

Safety Model

Three hard gates. If any fails, do not finalize:

  1. Provenance gate — every factual statement maps to a known source
  2. Commitment gate — every promise maps to already-done / approved-for-rebuttal / future-work-only
  3. Coverage gate — every reviewer concern ends in answered / deferred intentionally / needs user input

Workflow

Phase 0: Resume or Initialize

  1. If rebuttal/REBUTTAL_STATE.md exists, resume from the recorded phase
  2. Otherwise, create rebuttal/ and initialize the output documents
  3. Load the paper, reviews, venue rules, and any user-confirmed evidence

Phase 1: Validate Inputs and Normalize Reviews

  1. Validate that venue rules are explicit
  2. Normalize all reviewer text into rebuttal/REVIEWS_RAW.md verbatim
  3. Record metadata in rebuttal/REBUTTAL_STATE.md
  4. If ambiguous, pause and ask

Phase 2: Atomize and Classify Reviewer Concerns

Create rebuttal/ISSUE_BOARD.md.

For each atomic concern, record:

  • issue_id
  • reviewer, round, raw_anchor
  • issue_type
  • severity
  • reviewer_stance
  • response_mode
  • status

Phase 3: Build Strategy Plan

Create rebuttal/STRATEGY_PLAN.md.

  1. Identify 2-4 global themes resolving shared concerns
  2. Choose a response mode per issue
  3. Build the character budget
  4. Identify blocked claims
  5. If unresolved blockers exist, pause and present them to the user

QUICK_MODE exit: if QUICK_MODE = true, stop here and present ISSUE_BOARD.md + STRATEGY_PLAN.md.

Phase 3.5: Evidence Sprint (when AUTO_EXPERIMENT = true)

Skip entirely if AUTO_EXPERIMENT is false.

If the strategy plan identifies issues that require new empirical evidence:

  1. Generate a mini experiment plan from the reviewer concerns
  2. Invoke /experiment-bridge "rebuttal/REBUTTAL_EXPERIMENT_PLAN.md"
  3. Wait for results, then update ISSUE_BOARD.md
  4. If experiments fail or are inconclusive, switch to narrow_concession or future_work_boundary
  5. Save experiment results to rebuttal/REBUTTAL_EXPERIMENTS.md

Phase 4: Draft Initial Rebuttal

Create rebuttal/REBUTTAL_DRAFT_v1.md.

Structure:

  1. Short opener
  2. Per-reviewer numbered responses
  3. Short closing

Also generate rebuttal/PASTE_READY.txt with exact character count.

Phase 5: Safety Validation

Run all lints:

  1. Coverage
  2. Provenance
  3. Commitment
  4. Tone
  5. Consistency
  6. Limit

Phase 6: Stress Test

text
spawn_agent:
  model: gpt-5.4
  reasoning_effort: xhigh
  message: |
    Stress-test this rebuttal draft:
    [raw reviews + issue board + draft + venue rules]

    1. Unanswered or weakly answered concerns?
    2. Unsupported factual statements?
    3. Risky or unapproved promises?
    4. Tone problems?
    5. Paragraph most likely to backfire with a meta-reviewer?
    6. Minimal grounded fixes only. Do not invent evidence.

    Verdict: safe to submit / needs revision

Save the full response to rebuttal/MCP_STRESS_TEST.md. If a hard safety blocker remains, revise before finalizing.

Phase 7: Finalize — Two Versions

Produce:

  1. rebuttal/PASTE_READY.txt — strict version, ready to paste
  2. rebuttal/REBUTTAL_DRAFT_rich.md — extended version with optional sections marked
  3. Update rebuttal/REBUTTAL_STATE.md
  4. Present the remaining risks and any lines needing manual approval

Phase 8: Follow-Up Rounds

When new reviewer comments arrive:

  1. Append them to rebuttal/FOLLOWUP_LOG.md
  2. Link to existing issues or create new ones
  3. Draft the delta reply only
  4. Re-run safety lints
  5. If continuity helps, reuse the same reviewer agent via send_input
  6. Escalate technically, not rhetorically

Key Rules

  • Never fabricate evidence, numbers, derivations, citations, or links
  • Never overpromise. Only promise what the user explicitly approved.
  • Every reviewer concern must be tracked and accounted for
  • Preserve raw records
  • Shared concerns go in the opener; reviewer-specific details go in the per-reviewer sections
  • Answer friendly reviewers too
  • Respect the hard character limit

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