nature-writing

name	nature-writing
description	Draft, restructure, or plan English job-application prose for Chinese-speaking applicants from notes, claims, evidence, or Chinese drafts. Use when the user needs a new English foreign-company ES answer, cover letter, motivation statement, personal statement, career goals essay, role-fit answer, professional bio, research statement, or structured academic/research English draft.

English Application And Scientific Writing

Use this skill when the user needs a new English draft or structure, not merely sentence polishing. For job applications, build the argument around the target role and the applicant's real evidence. For academic text, use the scientific-writing references as needed.

Routing

• Use this skill for drafting from notes, Chinese source material, or incomplete outlines.
• Use nature-polishing instead when the user already has an English draft and wants style, clarity, or concision.
• Use japanese-es-writing instead when the target output is Japanese ES prose.

Core stance

• Author evidence comes first. Do not invent results, mechanisms, references, methods, novelty, sample sizes, statistics or limitations.
• Write the argument before writing the sentences.
• Make the paper easy to judge: relevance, novelty, trust, reuse and meaning.
• Use ambitious but bounded claims.
• If essential evidence is missing, write a placeholder or ask for the missing input instead of filling the gap.

Job Application English

When the target is a job application, internship, foreign company, or global company:

• Treat the section as application prose, not a manuscript section.
• Build around motivation -> evidence -> role fit -> future contribution.
• Use concrete experience, decisions, actions, constraints, and outcomes.
• Avoid academic paper architecture unless the user is writing a research statement.
• Do not invent achievements, metrics, internships, awards, language ability, or company research.
• Ask only for missing details that materially affect the answer: target company, role, limit, experience, result, and intended strength.

When to open extra files

File	Open when
references/article-architecture.md	You need section-level structure, argument order, or published-article writing patterns
references/abstract.md	Drafting or revising an abstract, especially challenge-contribution and challenge-insight-contribution forms
references/introduction.md	Drafting or revising an Introduction, task framing, technical challenge, contribution framing, or teaser/pipeline logic
references/related-work.md	Rebuilding Related Work as topic synthesis instead of a paper-by-paper list
references/method.md	Writing Method sections, pipeline modules, module motivation, technical advantages, or implementation details
references/experiments.md	Planning or writing Experiments/Results around baselines, ablations, metrics, tables, figures, and claim support
references/conclusion.md	Writing a bounded conclusion with contribution, evidence, impact, limitation, and future direction
references/paragraph-flow.md	User asks whether a paragraph flows, makes sense, or is clear; use reverse outlining and paragraph-message checks
references/paper-review.md	Final manuscript self-review, rejection-risk audit, claim-evidence alignment, or reviewer-facing critique
references/chinese-author-workflow.md	The user's notes are Chinese, mixed Chinese-English, or organized as lab notes rather than manuscript prose
references/examples/index.md	You need concrete abstract, introduction, or method examples after choosing the relevant guide

Intake

Before drafting, identify:

• application context: company, role, answer type, word limit, and intended strength
• manuscript section: title, abstract, introduction, results, discussion, conclusion, significance paragraph or full outline
• paper type: mechanism, method, resource, device, model, clinical, materials, computational or interdisciplinary
• core claim: what the paper actually demonstrates
• evidence: figures, measurements, comparisons, datasets, statistics or examples
• boundary: where the claim stops
• target journal or word limit, if provided

If any of core claim, evidence or boundary is absent, expose the gap before drafting. You may still produce a scaffold with explicit placeholders.

Writing workflow

1. Build a one-sentence argument: In [system/problem], we show [advance] using [approach], supported by [evidence], with [boundary].
2. Choose the section architecture from references/article-architecture.md.
3. Map each paragraph to one job: context, gap, approach, result, comparison, mechanism, implication or limitation.
4. Draft from evidence outward. Keep claims near the data that support them.
5. Calibrate verbs: show, demonstrate, suggest, indicate, enable, may, could.
6. Remove unsupported novelty and universal claims.
7. Run a paragraph-flow check: one paragraph, one message, with a clear first sentence and explicit sentence-to-sentence relation.
8. Return prose plus concise notes on assumptions and missing inputs.

Section defaults

Abstract

Default Nature pattern:

context/problem -> gap -> approach -> key result -> implication -> boundary

For technical AI, ML, CV or method-heavy manuscripts, open references/abstract.md and choose one of:

• challenge -> contribution
• challenge -> insight -> contribution
• multiple contributions

Keep it compact. Include quantitative or comparative detail when the user provided it. End with what the work enables, not generic importance.

Introduction

Use:

field scale -> bottleneck -> prior attempts -> unresolved gap -> present study

For method-heavy papers, open references/introduction.md and reason backward from the technical challenge and contribution before drafting forward.

Do not summarize all results. The final paragraph should state what this paper does and how it addresses the gap.

Results narrative

Use an evidence ladder:

system/workflow -> validation -> main result -> baseline comparison -> mechanism/diagnostic analysis -> application or generalization

Each subsection should have a claim-first opening and then data support.

For ML/conference-style experiment sections, open references/experiments.md and make sure each major claim is backed by comparison, ablation, or stress-test evidence.

Related Work

Use:

topic scope -> representative methods -> limitation tied to this paper -> distinction

Group prior work by technical topic and mechanism, not by publication year.

Discussion

Use:

central advance -> evidence meaning -> relation to prior work -> constraints -> future use

This is where interpretation and limitations belong. Do not repeat the Results section figure by figure.

Conclusion

Use:

contribution -> decisive evidence -> implication -> boundary

No new data. No unsupported promises.

Title

Prefer concrete titles that combine:

system/object + action/capability + application or consequence

Avoid slogan titles, grant-style aims and overbroad field claims.

Output format

Default output:

1. Draft: with the requested prose.
2. Section outline: with 3-7 compact bullets when the task involves a full section.
3. Assumptions or missing inputs: with only material issues.
4. Claim-evidence map: for major claims, using Claim: ... | Evidence: ... | Status: supported/needs evidence.
5. Why this structure: with 2-4 short bullets.

For Chinese author notes, provide polished English first, then brief Chinese notes explaining major structural choices.