agent-identifier
Use when creating or configuring Claude Code agents and their frontmatter.
Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript
$ npx -y skills add Galaxy-Dawn/claude-scholar --skill nature-writing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nature-writingContext preview
The summary Claude sees to decide when to auto-load this skill.
Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript
name: nature-writing description: Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose. version: 0.2.0 author: Community contribution based on curated Nature/Nature Communications writing patterns and open research-writing notes
Use this skill when the user needs help creating or rebuilding manuscript prose, not merely polishing existing sentences.
methods, novelty, sample sizes, statistics or limitations.
input instead of filling the gap.
| File | Open when | |---|---| | [references/article-architecture.md](references/article-architecture.md) | You need section-level structure, argument order, or published-article writing patterns | | [references/abstract.md](references/abstract.md) | Drafting or revising an abstract, especially challenge-contribution and challenge-insight-contribution forms | | [references/introduction.md](references/introduction.md) | Drafting or revising an Introduction, task framing, technical challenge, contribution framing, or teaser/pipeline logic | | [references/related-work.md](references/related-work.md) | Rebuilding Related Work as topic synthesis instead of a paper-by-paper list | | [references/method.md](references/method.md) | Writing Method sections, pipeline modules, module motivation, technical advantages, or implementation details | | [references/experiments.md](references/experiments.md) | Planning or writing Experiments/Results around baselines, ablations, metrics, tables, figures, and claim support | | [references/conclusion.md](references/conclusion.md) | Writing a bounded conclusion with contribution, evidence, impact, limitation, and future direction | | [references/paragraph-flow.md](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](references/paper-review.md) | Final manuscript self-review, rejection-risk audit, claim-evidence alignment, or reviewer-facing critique | | [references/chinese-author-workflow.md](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](references/examples/index.md) | You need concrete abstract, introduction, or method examples after choosing the relevant guide |
Before drafting, identify:
conclusion, significance paragraph or full outline
computational or interdisciplinary
If any of `core claim`, `evidence` or `boundary` is absent, expose the gap before drafting. You may still produce a scaffold with explicit placeholders.
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.
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:
Keep it compact. Include quantitative or comparative detail when the user provided it. End with what the work enables, not generic importance.
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.
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.
Use:
`topic scope -> representative methods -> limitation tied to this paper -> distinction`
Group prior work by technical topic and mechanism, not by publication year.
Use:
`central advance -> evidence meaning -> relation to prio
Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding, experiments, writing, and publication.
Repo: Galaxy-Dawn/claude-scholar
Use when creating or configuring Claude Code agents and their frontmatter.
Use only when creating new registrable ML components that require Factory or Registry patterns.
This skill should be used when the user asks to "debug this", "fix this error", "investigate this bug", "troubleshoot this issue", "find the problem",…
This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how…
This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or…
This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command…