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Use GPT Pro for research-paper brainstorming, claim sharpening, novelty analysis, related-work positioning, reviewer objections, and experiment story design. Best for algorithm/research ideas where Codex alone is too implementation-biased.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | gpt-pro-paper-brainstormer |
| description | Use GPT Pro for research-paper brainstorming, claim sharpening, novelty analysis, related-work positioning, reviewer objections, and experiment story design. Best for algorithm/research ideas where Codex alone is too implementation-biased. |
Gather only the evidence needed to test the research claim, then ask GPT Pro to act as a skeptical research advisor.
$bundle-algorithm-context if code, experiments, docs, or logs matter.$gpt-pro-question-window to ask GPT Pro.bridge-thread-id.Completion criterion: claims and related-work references are marked as verified or unverified, the required experiments are concrete, and the publishability judgment is preserved separately from Codex's local verdict.
Ask GPT Pro to cover:
GPT Pro may invent related work or overstate novelty. After GPT Pro responds, Codex should mark related-work items as unverified unless it has searched or the user supplied citations.
Build a compact, immutable GPT Pro evidence bundle from repository code, configs, docs, logs, Codex notes, and recent bridge events. Use before algorithm review, paper brainstorm, experiment analysis, implementation consistency review, or any GPT Pro round that needs local evidence.
Run the end-to-end Codex to GPT Pro to Codex loop for algorithm, research, experiment, or implementation-consistency work. Use when the user wants scoped evidence bundling, deep external review, local verification, experiments, and safe implementation connected through one reproducible task thread.
Bridge Codex to a signed-in ChatGPT/GPT Pro conversation, including scoped file upload, conversation reuse, raw answer capture, and later Codex verification. Use for normal GPT Pro questions and as the browser/persistence foundation for other Codex Pro Bridge skills; do not use for local tasks that need no external reasoning.
Convert an algorithm review or research idea into a prioritized experiment matrix with baselines, ablations, metrics, success/failure criteria, commands, logging requirements, and decision rules. Use after GPT Pro review or before implementing experiments.
Deep GPT Pro algorithm/research/pipeline review. Use for RL, reward modeling, OPD, agentic workflows, search/QA, training/eval pipelines, or algorithm proposals where Codex needs stronger hypothesis, experiment, ablation, data leakage, novelty, and go/no-go analysis.
Verify that an algorithm proposal, GPT Pro review, code implementation, configs, data splits, eval scripts, logs, and experiment commands are mutually consistent. Use before trusting results or after Codex implements an algorithm/pipeline change.