nature-response
- Repo stars 16,057
- Author repo nature-skills
Nature Reviewer Response — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (the default stance and red lines, and the response workflow with output format). - A dynamic layer (this file plus
manifest.yaml) that loads the core every time and reaches for the deeper response references only when a step needs them.
Do not try to apply the response logic from memory or from this router. Always load fragments from disk as described below.
Routing protocol
Follow these four steps every time the skill is invoked.
1. Load the manifest and the core layer
Read manifest.yaml. Then read every file listed under always_load:
static/core/stance.md— the editor-facing purpose, the default stance, the red lines, and the source hierarchy that apply to every response job.static/core/workflow.md— accepted inputs, the ten-step workflow, and the output package format.
2. No content axis — identify mode and language inline
Unlike nature-writing or nature-figure, nature-response has no fragment axis. Its variation is identified at runtime, not by loading different content bodies:
- task mode —
draft/audit/revise/triage-only/appeal-like. - decision type — minor revision, major revision, revise-and-resubmit, transfer after review, or unclear.
- user language — if the user writes Chinese, also produce the 中文核对 block.
Use references/intake-and-routing.md to fix the task mode, minimum inputs, and readiness state before drafting. Route appeal-like cases separately; do not draft an appeal as the default path.
3. Run the workflow
Follow the ten-step workflow in core/workflow.md: identify mode and decision type, extract editor instructions (IDs E.1) then reviewer comments (R1.1, R2.1), classify each item, build a strategy summary, draft point-by-point responses from the preserved comments, map every claimed change to a manuscript location or an explicit placeholder, flag missing author input, run QA, and return the package with a readiness state.
Never invent experiments, citations, line numbers, figure panels, supplementary items, editor instructions, or manuscript changes. Mark anything the author must supply as AUTHOR_INPUT_NEEDED.
4. Reach for references only when needed
The files under references/ are deep references, not defaults. Open them on demand per the references.on_demand table in the manifest — for example references/comment-taxonomy.md to classify comments, references/action-mapping.md for tracker fields, references/tone-and-stance.md for disagreement wording, references/difficult-cases.md for impossible experiments / conflicting reviewers / appeal-like cases, references/chinese-author-alignment.md for Chinese author notes, and references/qa-checklist.md before finalizing.
Why this split
- The static layer is versioned and reviewable; the core stays small for a normal response.
- The dynamic layer keeps each invocation cheap: the difficult-case, taxonomy, and QA depth load only when a step needs them.
- The router itself is short on purpose. Update fragments and references, not this file, when adding scope.
- This structure mirrors
nature-writing,nature-polishing,nature-reader,nature-paper2ppt,nature-figure, andnature-citation.
- Fluxly category
- Other
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @Yuan1z0825 · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Plug-and-play
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Write / modify
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
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。
The current SKILL.md does not define a fixed output example. Follow these four steps every time the skill is invoked.
Read manifest.yaml. Then read every file listed under alwaysload: static/core/stance.md — the editor-facing purpose, the default stance, the red lines, and the source hierarchy that apply to every response job. static/core/workflow.md — accepted inputs, the…
Unlike nature-writing or nature-figure, nature-response has no fragment axis. Its variation is identified at runtime, not by loading different content bodies: task mode — draft / audit / revise / triage-only / appeal-like.
Follow the ten-step workflow in core/workflow.md: identify mode and decision type, extract editor instructions (IDs E.1) then reviewer comments (R1.1, R2.1), classify each item, build a strategy summary, draft point-by-point responses from the preserved…
The files under references/ are deep references, not defaults. Open them on demand per the references.ondemand table in the manifest — for example references/comment-taxonomy.md to classify comments, references/action-mapping.md for tracker fields,…
The static layer is versioned and reviewable; the core stays small for a normal response. The dynamic layer keeps each invocation cheap: the difficult-case, taxonomy, and QA depth load only when a step needs them. The router itself is short on purpose. Update…
# Nature Reviewer Response — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (the default stance and red lines, and the response workflow with output format).
- A **dynamic layer** (this file plus `manifest.yaml`) that loads the core every time and reaches for the deeper response references only when a step needs them.
Do not try to apply the response logic from memory or from this router. Always load fragments from disk as described below.
## Routing protocol
Follow these four steps every time the skill is invoked.
### 1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). Then read every file listed under `always_load`:
- `static/core/stance.md` — the editor-facing purpose, the default stance, the red lines, and the source hierarchy that apply to every response job.
- `static/core/workflow.md` — accepted inputs, the ten-step workflow, and the output package format.
### 2. No content axis — identify mode and language inline
Unlike nature-writing or nature-figure, nature-response has no fragment axis. Its variation is identified at runtime, not by loading different content bodies:
- **task mode** — `draft` / `audit` / `revise` / `triage-only` / `appeal-like`.
- **decision type** — minor revision, major revision, revise-and-resubmit, transfer after review, or unclear.
- **user language** — if the user writes Chinese, also produce the 中文核对 block.
Use `references/intake-and-routing.md` to fix the task mode, minimum inputs, and readiness state before drafting. Route appeal-like cases separately; do not draft an appeal as the default path.
### 3. Run the workflow
… Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> Routing protocol → 1. Load the manifest and the core layer → 2. No content axis — identify mode and language inline → 3. Run the workflow → 4. Reach for references only when needed → Why this split
terms -> static layer · dynamic layer · task mode · decision type · user language
files/cmd -> static/ · manifest.yaml · alwaysload · static/core/stance.md · static/core/workflow.md · draft · audit · revise
body sha256 -> f028a8f98e66
Decide Fit First
Design Intent
How To Use It
Boundaries And Review