Parse reviewer feedback and generate safety-validated academic rebuttal responses.
npx skills add https://github.com/dogekiki/SP-test --skill rebuttal-dogekiki
Please help me install this Agent Skill. Skill: rebuttal Source: https://github.com/dogekiki/SP-test/tree/main/.trae/skills/rebuttal Command: npx skills add https://github.com/dogekiki/SP-test --skill rebuttal-dogekiki
This Skill manages the complex, high-stakes process of responding to academic peer reviews, ensuring that all reviewer concerns are addressed with grounded evidence while strictly adhering to venue-specific constraints.
Use the rebuttal skill to initialize a new rebuttal project for the paper located in the current directory.
High-intent search queries and answers about installing and using this skill.
To write an academic rebuttal within character limits, you need a structured workflow that parses reviewer feedback and generates compliant responses under strict character budget constraints, ensuring all concerns are systematically addressed.
Provenance mapping in peer review rebuttals grounds every claim in your response to specific paper content, reviewer quotes, or user-confirmed results, preventing fabrication through strict evidence validation gates.
Addressing multiple reviewer threads requires a rebuttal workflow that operates across multi-thread or single-document formats, systematically parsing and segregating each reviewer's concerns to generate distinct, verified responses.
You can stress test your academic rebuttal using AI-driven adversarial simulation to identify logical weak points and unverified claims before submission to venues like ICML or NeurIPS, ensuring compliance and robustness.
Essential safety guardrails for peer review responses include provenance, commitment, and coverage gates that validate evidence, restrict unauthorized commitments, and verify all reviewer concerns are fully addressed without fabrication.
Parsing reviewer feedback for a rebuttal requires integration with external review backends and local document parsing to systematically extract, address, and verify all reviewer concerns against venue-specific constraints.
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