nature-writing
- Repo stars 16,057
- Author updated Live
- Author repo nature-skills
- Domain
- Writing
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 92 / 100 · audit passed
- Author / version / license
- @Yuan1z0825 · v1.0.0 · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: nature-writing
description: This skill is split into two layers: Do not try to apply the drafting logic from memory or from…
category: writing
runtime: no special runtime
---
# nature-writing output preview
## PART A: Task fit
- Use case: This skill is split into two layers: Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below. Follow these five steps every time the skill is invoked. runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the axis values for this request” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “This skill is split into two layers: Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below. Follow these five steps every time the skill is invoked. runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the axis values for this request” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the axis values for this request”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: nature-writing
description: This skill is split into two layers: Do not try to apply the drafting logic from memory or from…
category: writing
source: Yuan1z0825/nature-skills
---
# nature-writing
## When to use
- This skill is split into two layers: Do not try to apply the drafting logic from memory or from this router. Always lo…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the axis values for this request” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "nature-writing" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Routing protocol / 1. Load the manifest and the core layer / 2. Detect the axis values for this request
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review