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+…
Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers,
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill nature-data --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nature-dataContext preview
The summary Claude sees to decide when to auto-load this skill.
Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers,
name: nature-data description: >- Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers, restricted or sensitive data, source data, supplementary datasets, DataCite-style dataset references, FAIR metadata for academic publication, or Chinese-to-English data availability wording for Chinese-speaking authors preparing Nature-family submissions.
Use this skill to turn a manuscript's supporting data into a transparent, Nature-ready data availability package: statement text, repository plan, dataset citations, and missing-information flags.
The governing policy layer is Springer Nature / Nature Portfolio data policy. The implementation layer is FAIR data practice and DataCite-style citation metadata.
When the user writes in Chinese, provides a Chinese manuscript note, or asks for "中文对应", "中英对照", "数据可用性声明", "数据获取声明", "原始数据", "数据存储库", or "受限数据":
the user explicitly asks for Chinese only.
for Nature-style English unless the restriction and access process are specified.
`数据可用性声明` -> `Data Availability`; `原始数据` -> `raw data`; `处理后数据` -> `processed data`; `源数据` -> `source data`; `补充材料` -> `Supplementary Information`; `受限数据` -> `restricted data`; `合理请求` -> `reasonable request`, only with reason and review route.
modes, and bilingual intake questions.
needed to inspect, reproduce, or reuse them.
approvals, access committees, or data-use conditions.
only when no suitable community repository exists.
and what metadata or representative data can still be public.
availability section.
statistics, or polish the manuscript unless the user asks for those tasks separately.
third-party restriction.
1. Identify the target journal and article type. If journal-specific instructions conflict with this skill, follow the journal. 2. Inventory every dataset needed to support the main and supplementary results: generated raw data, processed data, figure source data, secondary data, software outputs, models, tables, images, and files underlying statistical analysis. 3. Classify each dataset into one access route: `public repository`, `controlled access repository`, `within paper or supplement`, `reused public source`, `third-party restricted`, `available on justified request`, or `not applicable`. 4. Choose repository and identifier strategy before drafting text. Prefer DOI, accession number, Handle, ARK, or stable repository record over personal websites and temporary cloud links. 5. Draft the Data Availability statement using explicit dataset-to-location mapping. 6. Add formal dataset citations for public data that support conclusions. 7. Run the FAIR and metadata audit before finalizing. 8. Return ready-to-paste statement text plus any unresolved fields the author must confirm.
Unless the user asks for another format, return:
Data Availability [ready-to-paste statement] Repository and citation actions - [specific actions or "None"] Missing information / risk flags - [specific flags or "None"] 中文核对 - [用中文列出作者需要确认的字段或 "无"]
When auditing an existing statement, lead with blocking issues first, then provide a revised version.
| File | Open when | |---|---| | [references/policy-principles.md](references/policy-principles.md) | You need the governing Nature/Springer Nature data-sharing rules or edge-case policy logic | | [references/chinese-author-alignment.md](references/chinese-author-alignment.md) | The user writes in Chinese, needs bilingual wording, or provides Chinese availability notes | | [references/statement-patterns.md](references/statement-patterns.md) | You need ready-to-adapt Data Availability statement patterns | | [references/repository-and-identifiers.md](references/repository-and-identifiers.md) | You need repository choice, accession, DOI, embargo, versioning, or dataset citation guidance | | [references/fair-metadata-checklist.md](references/fair-metadata-checklist.md) | You need FAIR checks, README metadata, file organization, licences, provenance, or DataCite fields | | [references/source-basis.md](references/source-basis.md) | You need to justify rules with official sources or check which source supports which rule |
Use sources in this order:
1. Target journal instructions and submission system requirements. 2. Nature Portfolio / Springer Nature data, code, materials, and reporting policies. 3. Repository-specific requirements and domain community standards. 4. FAIR principles and Dat
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…