nature_writing

Name: nature_writing
Author: ai4protein

244stars35forks

How to install nature_writing?

ai4protein/venusfactory2/nature_writing

$npx -y skills add ai4protein/VenusFactory2 --skill nature_writing

Installs into the current project.

Summary

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, related-work, method, experiments, discussion, conclusion, title, or full m

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SKILL.md

1	# Nature-Style Scientific Writing — Router
2
3	This skill is split into two layers:
4
5	- 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).
6	- A dynamic layer (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
7
8	Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below.
9
10	## Routing protocol
11
12	Follow these five steps every time the skill is invoked.
13
14	### 1. Load the manifest and the core layer
15
16	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.
17
18	Also read every file listed under `always_load`. These hold the default stance, writing workflow, and output format that apply to every drafting job.
19
20	### 2. Detect the axis values for this request
21
22	For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
23
24	- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research.
25	- `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.
26	- `language` — en or zh-to-en. Detect from the user's notes themselves.
27	- `journal` — nature / nat-comms / generic. Default: generic. If the user names a Nature subjournal, treat it as `nature`.
28
29	State the detected axis values in one short line to the user before drafting, so they can correct you cheaply.
30
31	### 3. Load the matching fragments
32
33	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.
34
35	Do not read every fragment in `static/`. Load only what step 2 selected.
36
37	### 4. Draft using the loaded material
38
39	Apply the loaded fragments in this priority order:
40
41	1. Core stance + intake (`core/stance.md`) — surface missing claim / evidence / boundary before drafting.
42	2. Paper-type playbook — argument chain, drafting order.
43	3. Section-specific drafting rules and structure.
44	4. Journal-specific framing and constraints.
45	5. Language-specific sentence and paragraph rules (apply last).
46
47	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.
48
49	If essential evidence or boundary is missing, write a placeholder and list it under `Assumptions or missing inputs:` instead of inventing content.
50
51	### 5. Reach for references only when needed
52
53	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:
54
55	- The user asks for a concrete example or template → `references/examples/index.md`.
56	- A section's draft has structural problems that the section fragment alone does not explain → the matching `references/<section>.md`.
57	- The user needs a broad-audience `Nature` abstract opening or asks about a `summary paragraph` → `references/nature-summary-paragraph.md`.
58	- The user asks "does this paragraph flow?" → `references/paragraph-flow.md`.
59	- The user asks for a self-review or rejection-risk audit → `references/paper-review.md`.
60
61	## Why this split
62
63	- The static layer is versioned and reviewable. Adding a new journal style, paper type, or section is one new file plus one manifest line.
64	- 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.
65	- The router itself is short on purpose. Update fragments, not this file, when adding scope.
66	- This structure mirrors `nature-polishing` so shared content can later be lifted into a `_shared/` layer used by both skills.

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Type

nature_writing

244stars35forks

View on GitHub

How to install nature_writing?

ai4protein/venusfactory2/nature_writing

$npx -y skills add ai4protein/VenusFactory2 --skill nature_writing

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Nature-Style Scientific Writing — Router
2
3	This skill is split into two layers:
4
5	- 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).
6	- A dynamic layer (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
7
8	Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below.
9
10	## Routing protocol
11
12	Follow these five steps every time the skill is invoked.
13
14	### 1. Load the manifest and the core layer
15
16	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.
17
18	Also read every file listed under `always_load`. These hold the default stance, writing workflow, and output format that apply to every drafting job.
19
20	### 2. Detect the axis values for this request
21
22	For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
23
24	- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research.
25	- `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.
26	- `language` — en or zh-to-en. Detect from the user's notes themselves.
27	- `journal` — nature / nat-comms / generic. Default: generic. If the user names a Nature subjournal, treat it as `nature`.
28
29	State the detected axis values in one short line to the user before drafting, so they can correct you cheaply.
30
31	### 3. Load the matching fragments
32
33	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.
34
35	Do not read every fragment in `static/`. Load only what step 2 selected.
36
37	### 4. Draft using the loaded material
38
39	Apply the loaded fragments in this priority order:
40
41	1. Core stance + intake (`core/stance.md`) — surface missing claim / evidence / boundary before drafting.
42	2. Paper-type playbook — argument chain, drafting order.
43	3. Section-specific drafting rules and structure.
44	4. Journal-specific framing and constraints.
45	5. Language-specific sentence and paragraph rules (apply last).
46
47	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.
48
49	If essential evidence or boundary is missing, write a placeholder and list it under `Assumptions or missing inputs:` instead of inventing content.
50
51	### 5. Reach for references only when needed
52
53	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:
54
55	- The user asks for a concrete example or template → `references/examples/index.md`.
56	- A section's draft has structural problems that the section fragment alone does not explain → the matching `references/<section>.md`.
57	- The user needs a broad-audience `Nature` abstract opening or asks about a `summary paragraph` → `references/nature-summary-paragraph.md`.
58	- The user asks "does this paragraph flow?" → `references/paragraph-flow.md`.
59	- The user asks for a self-review or rejection-risk audit → `references/paper-review.md`.
60
61	## Why this split
62
63	- The static layer is versioned and reviewable. Adding a new journal style, paper type, or section is one new file plus one manifest line.
64	- 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.
65	- The router itself is short on purpose. Update fragments, not this file, when adding scope.
66	- This structure mirrors `nature-polishing` so shared content can later be lifted into a `_shared/` layer used by both skills.

People who liked this also viewed

6 picks

Type