nature-data
- Repo stars 16,057
- Author repo nature-skills
Nature Data Availability — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (the default stance and source hierarchy, the Chinese-user operating mode, and the workflow with output format). - A dynamic layer (this file plus
manifest.yaml) that loads the core every time and reaches for the deeper policy/repository/FAIR references only when a step needs them.
Do not try to apply the data-availability 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— what the data-availability package is, the default stance, and the source hierarchy.static/core/chinese-mode.md— how to operate when the user writes in Chinese (accept Chinese, draft English, convert terms precisely).static/core/workflow.md— the eight-step workflow and the output format.
2. No content axis — confirm journal and language inline
Unlike nature-writing or nature-figure, nature-data has no fragment axis. Its variation is handled at runtime, not by loading different content bodies:
- journal/article type — if journal-specific instructions conflict with this skill, follow the journal.
- access route — each dataset is classified into one route (public repository, controlled access, within paper, reused public, third-party restricted, justified request, or not applicable).
- user language — if the user writes Chinese, follow
core/chinese-mode.mdand add the 中文核对 block.
3. Run the workflow
Follow the eight-step workflow in core/workflow.md: identify the journal, inventory every supporting dataset, classify each into one access route, choose repository and identifier strategy before drafting, draft the statement with explicit dataset-to-location mapping, add formal dataset citations, run the FAIR/metadata audit, and return ready-to-paste text plus unresolved fields.
Do not invent DOIs, accession numbers, repository names, licences, embargo dates, ethics approvals, access committees, or data-use conditions. Flag "available upon request" as weak unless there is a specific legal, ethical, commercial, or third-party restriction.
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/policy-principles.md for the governing rules and edge cases, references/repository-and-identifiers.md for repository/accession/DOI choices, references/statement-patterns.md for ready-to-adapt statements, references/fair-metadata-checklist.md for the FAIR audit, references/chinese-author-alignment.md for Chinese wording, and references/source-basis.md to justify a rule with its official source.
Why this split
- The static layer is versioned and reviewable; the core stays small for a normal statement.
- The dynamic layer keeps each invocation cheap: the policy, repository, and FAIR 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,nature-citation, andnature-response.
- Fluxly category
- Data
- 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 — what the data-availability package is, the default stance, and the source hierarchy. static/core/chinese-mode.md — how to operate when the user writes in Chinese (accept…
Unlike nature-writing or nature-figure, nature-data has no fragment axis. Its variation is handled at runtime, not by loading different content bodies: journal/article type — if journal-specific instructions conflict with this skill, follow the journal.
Follow the eight-step workflow in core/workflow.md: identify the journal, inventory every supporting dataset, classify each into one access route, choose repository and identifier strategy before drafting, draft the statement with explicit dataset-to-location…
The files under references/ are deep references, not defaults. Open them on demand per the references.ondemand table in the manifest — for example references/policy-principles.md for the governing rules and edge cases, references/repository-and-identifiers.md…
The static layer is versioned and reviewable; the core stays small for a normal statement. The dynamic layer keeps each invocation cheap: the policy, repository, and FAIR depth load only when a step needs them. The router itself is short on purpose. Update…
# Nature Data Availability — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (the default stance and source hierarchy, the Chinese-user operating mode, and the workflow with output format).
- A **dynamic layer** (this file plus `manifest.yaml`) that loads the core every time and reaches for the deeper policy/repository/FAIR references only when a step needs them.
Do not try to apply the data-availability 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` — what the data-availability package is, the default stance, and the source hierarchy.
- `static/core/chinese-mode.md` — how to operate when the user writes in Chinese (accept Chinese, draft English, convert terms precisely).
- `static/core/workflow.md` — the eight-step workflow and the output format.
### 2. No content axis — confirm journal and language inline
Unlike nature-writing or nature-figure, nature-data has no fragment axis. Its variation is handled at runtime, not by loading different content bodies:
- **journal/article type** — if journal-specific instructions conflict with this skill, follow the journal.
- **access route** — each dataset is classified into one route (public repository, controlled access, within paper, reused public, third-party restricted, justified request, or not applicable).
- **user language** — if the user writes Chinese, follow `core/chinese-mode.md` and add the 中文核对 block.
### 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 — confirm journal and language inline → 3. Run the workflow → 4. Reach for references only when needed → Why this split
terms -> static layer · dynamic layer · journal/article type · access route · user language
files/cmd -> static/ · manifest.yaml · alwaysload · static/core/stance.md · static/core/chinese-mode.md · static/core/workflow.md · core/chinese-mode.md · core/workflow.md
body sha256 -> 7c53c4535540
Decide Fit First
Design Intent
How To Use It
Boundaries And Review