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codex-pro-bridge

codex-pro-bridge 收录了来自 WILLOSCAR 的 7 个 skills,并提供仓库级职业覆盖和站内 skill 详情页。

已收集 skills
7
Stars
2
更新
2026-07-10
Forks
0
职业覆盖
2 个职业分类 · 已分类 100%
仓库浏览

这个仓库中的 skills

bundle-algorithm-context
软件开发工程师

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.

2026-07-10
gpt-pro-algorithm-pipeline
软件开发工程师

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.

2026-07-10
gpt-pro-question-window
软件开发工程师

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.

2026-07-10
experiment-plan-generator
软件开发工程师

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.

2026-07-10
gpt-pro-paper-brainstormer
其他高等院校教师

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.

2026-07-10
gpt-pro-research-algorithm-reviewer
软件开发工程师

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.

2026-07-10
implementation-consistency-checker
软件开发工程师

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.

2026-07-10