cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
Draft, audit, or revise point-by-point reviewer response letters for Nature-family manuscript revisions. Use when the user provides reviewer comments, editor decision letters, revision notes, response drafts, or asks how to respond to major/minor revision requests, rebuttal
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill nature-response --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nature-responseContext preview
The summary Claude sees to decide when to auto-load this skill.
Draft, audit, or revise point-by-point reviewer response letters for Nature-family manuscript revisions. Use when the user provides reviewer comments, editor decision letters, revision notes, response drafts, or asks how to respond to major/minor revision requests, rebuttal
name: nature-response description: >- Draft, audit, or revise point-by-point reviewer response letters for Nature-family manuscript revisions. Use when the user provides reviewer comments, editor decision letters, revision notes, response drafts, or asks how to respond to major/minor revision requests, rebuttal letters, response to reviewers, peer-review reports, 审稿意见回复, 逐点回复, 修回信, 大修回复, 小修回复, or 如何回复 reviewer. version: 0.1.0 status: Beta
Use this skill to convert editor decision letters, reviewer comments, author notes, or draft rebuttals into an auditable point-by-point response package for manuscript revisions.
The response letter is an editor-facing verification document. The goal is to show that every reviewer concern has been understood, addressed, and mapped to a concrete manuscript change, justified scientific response, or unresolved author action.
The skill may receive:
If reviewer boundaries or comment segmentation are ambiguous, flag the ambiguity instead of inventing reviewer structure.
1. Identify task mode and input readiness: `draft`, `audit`, `revise`, `triage-only`, or `appeal-like`. 2. Identify decision type: minor revision, major revision, revise-and-resubmit, transfer after review, or unclear. 3. Extract editor instructions first and assign IDs such as `E.1`, then split reviewer comments with IDs such as `R1.1`, `R1.2`, and `R2.1`. 4. Classify each item by category, severity, action label, missing input, readiness state, and risk. 5. Create a response strategy summary before drafting prose. 6. Draft responses using preserved reviewer comments unless the mode is `triage-only` or `appeal-like`. 7. Map each claimed change to manuscript location, figure, table, supplement, citation, or explicit placeholder. 8. Flag missing author input rather than fabricating details. 9. Run QA for completeness, traceability, factuality, tone, and unresolved risk. 10. Return the response package with package readiness: `ready_to_submit`, `draft_with_placeholders`, `needs_author_input`, or `blocked`.
Unless the user asks for another format, return:
Response strategy summary - Decision type: - Overall posture: - Major risks: - Suggested ordering: Comment-response tracker | ID | Reviewer concern | Type | Severity | Proposed action | Missing author input | |---|---|---|---|---|---| Draft point-by-point response letter [editor-readable English response] Manuscript change checklist - [specific manuscript changes or placeholders] Missing information / risk flags - [specific unresolved items or "None"] 中文核对 - [when the user writes in Chinese; otherwise omit unless useful]
| File | Open when | |---|---| | [references/intake-and-routing.md](references/intake-and-routing.md) | Before drafting, to identify task mode, minimum inputs, editor IDs, readiness state, and clarifying-question need | | [references/source-basis.md](references/source-basis.md) | You need source hierarchy, rule provenance, or policy-vs-advice boundaries | | [references/response-structure.md](references/response-structure.md) | You need the response package format or point-by-point letter anatomy | | [references/comment-taxonomy.md](references/comment-taxonomy.md) | You need to classify reviewer comments by category and severity | | [references/action-mapping.md](references/action-mapping.md) | You need action labels, tracker fields, and missing-input states | | [references/tone-and-stance.md](references/tone-and-stance.md) | You need recommended language, forbidden phrasing, or disagreement tone | | [references/chinese-author-alignment.md](references/chinese-author-alignment.md) | The user writes in Chinese or provides Chinese author notes | | [references/difficult-cases.md](references/difficult-cases.md) | The comments involve impossible experiments, factual errors, conflicting reviewers, citations, statistics, compliance, transfer, or appeal-like cases | | [references/qa-checklist.md](references/qa-checklist.md) | Before finalizing an output or auditing a draft response |
Use sources in this or
MUNDO - THE EMPEROR. Complete AI orchestration system with 1208 skills, 25 capability modules, self-evolving, collective consciousness. GitHub Actions 24/7 automation.
Repo: LiHongwei-cn/lihongwei-cn
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase 2 强制走 cheat-score-blind…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed 给更贴合的选题、更准的…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md / rubric_notes.md。**这是工具最早期信号的来源**——cold-start…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级 state"/"migrate"/"我的 state…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md 含实绩信号,cheat-score-blind…