hkustdial/supervisor-skills

rebuttal-guidance

Provides actionable peer-review rebuttal guidance (not full rebuttal prose) using conditional persuasion P(Z|X,Y): match reviewer mindset X, recommend strategy Y, optionally ground in manuscript evidence and similar successful historical (review, rebuttal)…

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Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/hkustdial/supervisor-skills --skill rebuttal-guidance

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Rebuttal Guidance

Overview

This skill delivers executable rebuttal guidance per concern: structured plans, evidence pointers, tone and strategy priorities. It does not produce ready-to-paste rebuttal prose; the author writes the final text.

The core model is conditional persuasion P(Z=1 | X, Y):

  • X: reviewer mindset (behavior cluster inferred from review text)
  • Y: rebuttal strategy vector (which tactics to emphasize)
  • Z: success (score increase or paper accepted)

When to use

  • User pastes Weaknesses / Questions from ICLR, NeurIPS, ICML, EMNLP, etc.
  • User asks how to respond to a specific reviewer comment.
  • User wants a structured plan before writing rebuttal prose.
  • User asks which tone or evidence strategy fits a harsh vs. open reviewer.
  • User says "reviewer ignored my rebuttal" and wants to recalibrate.

When NOT to use

  • User wants full rebuttal text copied verbatim → output guidance first; warn

against blind LLM paste.

  • User asks to evaluate a research idea → use idea-evaluator.
  • User asks for pre-submission paper review → use pre-submission-reviewer.
  • No review text provided → ask for it first.

Core procedure

Step 1: Inventory concerns

Extract every numbered Weakness and Question from the pasted review. If the user pasted only one reviewer's block, ask whether other reviewers exist.

Output a short table:

IDTypeOne-line summary
R1.W1W...
R1.Q1Q...

Step 2: Classify each concern

See: references/concern-classification.md

Tag each item as one of: misunderstanding | evidence_gap | novelty | baseline_fairness | scope_claim | writing_clarity | theory | efficiency | other

Step 3: Match reviewer mindset (X)

See: references/mindset-matching-heuristics.md

Score the review on 5–7 behavior signals (openness, severity, constructiveness, specificity, skepticism, harshness, actionability). Map scores to a cluster in references/mindset-library.md.

State: matched cluster name, confidence (high / medium / low), and the specific phrases that triggered the match.

Step 4: Strategy priorities for this mindset (Y)

From the matched cluster in references/mindset-library.md, read:

  • Historical up-rate: calibrate how likely a score increase is.
  • Rule-stat diffs (success vs. failure %): boost tactics with positive diff.
  • Cohen's d effects: highlight dimensions with d > 0.8 in success group.
  • Success / failure patterns: concrete do's and don'ts from data.
  • Key strategy: one-sentence summary for this cluster.

Cross-check dimensions in references/strategy-dimensions.md.

Step 5: Per-concern guidance

For each concern, emit a guidance block (not final prose):

### R?.W?: [short title]
- **Concern type**: ...
- **Mindset-aware strategy**: ...
- **Recommended structure**: Acknowledge → Response → Evidence → Revision note
- **Clarify from paper?**: yes/no: where to look (section, table, appendix)
- **New experiment needed?**: yes/no: what exactly (no fabricated numbers)
- **Tone note**: ...
- **Template**: A / B / C: see references/response-templates.md
- **Avoid**: ...

Do not fabricate experimental numbers. Mark anything unverified as [TO VERIFY].

Step 6: Integrity gate

Before finalizing, run through references/checklist.md.

Key flags:

  • Every W/Q has a guidance block.
  • No fabricated numbers.
  • Defensive phrases (e.g., "you misunderstood") flagged.
  • Overpromise risk flagged for scopeclaim and evidencegap types.

Step 7: Output format

Deliver a ## Rebuttal Guidance section containing:

  1. Reviewer mindset summary: cluster name, confidence, identifying phrases.
  2. Global strategy priorities: 3–5 bullets from mindset data.
  3. Per-concern guidance: Step 5 blocks for each W/Q.
  4. Checklist highlights: pass/fail on key integrity items.

Reference map

PurposeFile
Concern type → response priorityconcern-classification.md
Reviewer signal → mindset clustermindset-matching-heuristics.md
Mindset clusters with stats & patternsmindset-library.md
10 strategy dimensions (Y)strategy-dimensions.md
Response templates A / B / Cresponse-templates.md
Pre-submit integrity checklistchecklist.md

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