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, initial-submission 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 (task, 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:

• task — manuscript / submission-package. Use submission-package for first-submission materials, never for revision correspondence.
• 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 / nature-family / nat-comms / nat-mach-intell / generic. Default: generic. Use nature only for the flagship journal Nature, nat-comms for Nature Communications, nat-mach-intell for Nature Machine Intelligence (NMI), and nature-family for other Nature Portfolio titles or an unspecified Nature-family request.

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 when the task is submission-package or when the user explicitly asks 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:

1. Core stance + intake (core/stance.md) — surface missing claim / evidence / boundary before drafting.
2. Paper-type playbook — argument chain, drafting order.
3. Section-specific drafting rules and structure.
4. Task-specific submission rules when task=submission-package.
5. Journal-specific framing and constraints.
6. Language-specific sentence and paragraph rules (apply last).

For task=manuscript, run the workflow in core/workflow.md end-to-end. Do not skip planning just because the user asked for prose immediately.

When drafting or restructuring Results, or compressing a full manuscript's main text, also load ../nature-shared/core/main-text-discipline.md before building the paragraph map. Classify every result by function, allocate it across main text, captions, Methods/source data, and SI, then draft the shortest sufficient evidence chain. Do not equate a complete analysis record with a complete main text.

For task=submission-package, follow static/fragments/task/submission-package.md and references/submission-package.md instead. Build the deliverable matrix and readiness audit; do not force manuscript paragraph architecture onto administrative submission materials.

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 Nature abstract opening or asks about a summary 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.
• The user asks what belongs in the main text, captions, or SI; wants a shorter Results section; or is adding reviewer-driven explanation → ../nature-shared/core/main-text-discipline.md.
• The user requests a complete first-submission package, templates, or a submission-readiness audit → references/submission-package.md.
• The target is the flagship journal Nature and exact submission or formatting requirements matter → ../nature-shared/journal-formats/nature.md.
• The target is Nature Machine Intelligence and exact content-type, submission, data/code or production requirements matter → ../nature-shared/journal-formats/nature-machine-intelligence.md.
• The work involves regulated or specialist research compliance → ../nature-shared/core/research-compliance.md.

Submission boundary

• nature-writing owns initial submission materials prepared before peer review.
• nature-response owns revision cover letters, rebuttals, point-by-point responses, marked manuscripts, appeals, and other post-decision correspondence.
• Route graphical abstracts and TOC graphics to nature-figure; route simulated pre-submission peer review to nature-reviewer.

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-polishing so shared content can later be lifted into a nature-shared/ layer used by both skills.