Nature 写作
- 作者仓库星标 16,057
- 作者仓库 nature-skills
Nature-Style Scientific Writing — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (core stance + workflow, paper-type playbooks, per-section drafting guidance, language-specific rules, per-journal style). - A dynamic layer (this file plus
manifest.yaml) that detects the request's axes and loads only the fragments needed for the current job.
Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below.
Routing protocol
Follow these five steps every time the skill is invoked.
1. Load the manifest and the core layer
Read manifest.yaml. It declares the axes (paper_type, section, language, journal), the allowed values, and the file paths each value maps to.
Also read every file listed under always_load. These hold the default stance, writing workflow, and output format that apply to every drafting job.
2. Detect the axis values for this request
For each axis in the manifest, decide the value using the manifest's detect: hint and the user's input:
paper_type— research / methods / hypothesis / algorithmic / review. Default: research.section— abstract / intro / related-work / method / experiments / discussion / conclusion / title. May be multiple. Ask the user if it is ambiguous and matters for the draft.language— en or zh-to-en. Detect from the user's notes themselves.journal— nature / nat-comms / generic. Default: generic. If the user names a Nature subjournal, treat it asnature.
State the detected axis values in one short line to the user before drafting, so they can correct you cheaply.
3. Load the matching fragments
For each axis value, Read the file mapped in the manifest. Skip the section axis only when the user has explicitly asked for a free-floating argument paragraph with no section context.
Do not read every fragment in static/. Load only what step 2 selected.
4. Draft using the loaded material
Apply the loaded fragments in this priority order:
- Core stance + intake (
core/stance.md) — surface missing claim / evidence / boundary before drafting. - Paper-type playbook — argument chain, drafting order.
- Section-specific drafting rules and structure.
- Journal-specific framing and constraints.
- Language-specific sentence and paragraph rules (apply last).
Run the 8-step workflow in core/workflow.md end-to-end. Do not skip steps 1-3 (planning) just because the user asked for prose immediately — write the one-sentence argument first.
If essential evidence or boundary is missing, write a placeholder and list it under Assumptions or missing inputs: instead of inventing content.
5. Reach for references only when needed
The files under references/ are deep references and the example library, not defaults. Open them on demand per the references.on_demand table in the manifest. Typical triggers:
- The user asks for a concrete example or template →
references/examples/index.md. - A section's draft has structural problems that the section fragment alone does not explain → the matching
references/<section>.md. - The user needs a broad-audience
Natureabstract opening or asks about asummary paragraph→references/nature-summary-paragraph.md. - The user asks "does this paragraph flow?" →
references/paragraph-flow.md. - The user asks for a self-review or rejection-risk audit →
references/paper-review.md.
Why this split
- The static layer is versioned and reviewable. Adding a new journal style, paper type, or section is one new file plus one manifest line.
- The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full multi-thousand-line reference set.
- The router itself is short on purpose. Update fragments, not this file, when adding scope.
- This structure mirrors
nature-polishingso shared content can later be lifted into a_shared/layer used by both skills.
- 流狐分类
- 写作
- 作者声明 Agent
- 未找到明确声明;不据此推断已兼容或已测试
- 静态检查
- 92 / 100 · 启发式扫描,不代表运行安全
- 作者 / 版本 / 许可
- @Yuan1z0825 · v1.0.0 · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- 未声明
- 底层运行要求
- 未声明
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无(仅作为资料)
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
作者没有在当前 SKILL.md 中定义固定输出样例。 Follow these five steps every time the skill is invoked.
Read manifest.yaml. It declares the axes (papertype, section, language, journal), the allowed values, and the file paths each value maps to. Also read every file listed under alwaysload. These hold the default stance, writing workflow, and output format that…
For each axis in the manifest, decide the value using the manifest's detect: hint and the user's input: papertype — research / methods / hypothesis / algorithmic / review. Default: research. section — abstract / intro / related-work / method / experiments /…
For each axis value, Read the file mapped in the manifest. Skip the section axis only when the user has explicitly asked for a free-floating argument paragraph with no section context. Do not read every fragment in static/. Load only what step 2 selected.
Apply the loaded fragments in this priority order: Core stance + intake (core/stance.md) — surface missing claim / evidence / boundary before drafting. Paper-type playbook — argument chain, drafting order.
The files under references/ are deep references and the example library, not defaults. Open them on demand per the references.ondemand table in the manifest. Typical triggers: The user asks for a concrete example or template → references/examples/index.md.
# Nature-Style Scientific Writing — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (core stance + workflow, paper-type playbooks, per-section drafting guidance, language-specific rules, per-journal style).
- A **dynamic layer** (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below.
## Routing protocol
Follow these five steps every time the skill is invoked.
### 1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). It declares the axes (`paper_type`, `section`, `language`, `journal`), the allowed values, and the file paths each value maps to.
Also read every file listed under `always_load`. These hold the default stance, writing workflow, and output format that apply to every drafting job.
### 2. Detect the axis values for this request
For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research.
- `section` — abstract / intro / related-work / method / experiments / discussion / conclusion / title. May be multiple. Ask the user if it is ambiguous and matters for the draft.
- `language` — en or zh-to-en. Detect from the user's notes themselves.
- `journal` — nature / nat-comms / generic. Default: generic. If the user names a Nature subjournal, treat it as `nature`.
State the detected axis values in one short line to the user before drafting, so they can correct you cheaply.
### 3. Load the matching fragments
… 作者原文负责流程事实;流狐只索引当前章节、要点、文件与命令。
章节 -> Routing protocol → 1. Load the manifest and the core layer → 2. Detect the axis values for this request → 3. Load the matching fragments → 4. Draft using the loaded material → 5. Reach for references only when needed
要点 -> static layer · dynamic layer · not · Do not try to apply the drafting logic from memory or from this router. · Follow these five steps every time the skill is invoked. · Read [manifest.yaml](manifest.yaml). · Also read every file listed under alwaysload. · - papertype — research / methods / hypothesis / algorithmic / review.
文件/命令 -> static/ · manifest.yaml · papertype · section · language · journal · alwaysload · detect:
内容 SHA-256 -> 0a2816cd6504
原文结构
适用与边界
原文中的明确线索
static/、manifest.yaml、papertype、section、language、journal、alwaysload、detect: