Agent skill

Nature Paper Card

by Yuan1z0825 in Yuan1z0825/nature-skills

Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.

Apache-2.0Auto-check passedResearch & Science

Install Nature Paper Card

skills CLI

$ npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install Yuan1z0825/nature-skills nature-paper-card --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nature-paper-card .claude/skills/nature-paper-card && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "nature-paper-card" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card into .claude/skills/nature-paper-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nature-paper-card", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install Yuan1z0825/nature-skills nature-paper-card --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/nature-paper-card .agents/skills/nature-paper-card && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "nature-paper-card" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card into .agents/skills/nature-paper-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nature-paper-card", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install Yuan1z0825/nature-skills nature-paper-card --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/nature-paper-card .cursor/skills/nature-paper-card && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "nature-paper-card" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card into .cursor/skills/nature-paper-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nature-paper-card", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/Yuan1z0825/nature-skills.git --path skills/nature-paper-card

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install Yuan1z0825/nature-skills nature-paper-card --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/nature-paper-card .gemini/skills/nature-paper-card && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "nature-paper-card" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card into .gemini/skills/nature-paper-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nature-paper-card", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install Yuan1z0825/nature-skills nature-paper-card

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/nature-paper-card .github/skills/nature-paper-card && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "nature-paper-card" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card into .github/skills/nature-paper-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nature-paper-card", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install Yuan1z0825/nature-skills nature-paper-card --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/nature-paper-card .opencode/skills/nature-paper-card && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "nature-paper-card" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper-card into .opencode/skills/nature-paper-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nature-paper-card", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: nature-paper-card
GitHub stars: 47k
Used in: 2 other repos
Token cost: ~2.1k tokens
SKILL.md length: 1,015 words
Files: 24 (incl. scripts, references)
Skills in repo: 23
Repo updated: Oct 11, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.

Works in 6 steps: Load the manifest and core layer → Establish the source boundary → Classify the paper type → …
Reading a research paper closely before building on it
SKILL.md covers Routing protocol, Script red lines and Relationship to adjacent skills
Runs Python scripts from its folder

What it does

Output is an evidence-grounded research card for a single paper, not a translated abstract, generic summary, reviewer report or publication article. A router loads a manifest and a static core with principles, workflow and a fixed output contract, then one paper-type fragment, and pulls references on demand for evidence labels, the exact card schema and research-idea checks.

The agent first sets the source boundary: full paper with figures and tables, text without reliable layout, abstract or metadata only, or an existing nature-reader artifact, which is preferred when supplied. Partial material produces a visibly partial card with unsupported sections marked as not assessable. For a PDF or a source-map JSON, running the bundled scripts/prepare_paper.py is mandatory and writes a source bundle JSON, optionally rendering pages for visual review.

Page locators follow a fixed state machine, and entries without verified page numbers stay in an unlocated list and are cited structurally rather than as page 1. The agent never writes inline Python or patches the bundled scripts during a normal run, and an audit_paper_card.py script is included.

When your agent uses it

Reading a research paper closely before building on it
Mapping which experiments support which claims
Listing a paper's limitations and follow-up research ideas

Example prompts

“Make a paper card for ./papers/diffusion-survey.pdf with its evidence chain.”
“Break down the methods of this paper and say which claims the experiments actually support.”
“I only have the abstract, so produce a partial paper card and mark what cannot be assessed.”

Requirements

Python, to run scripts/prepare_paper.py on a PDF or source map

Workflow steps

6 steps, taken from the step headings in SKILL.md.

Load the manifest and core layer
Establish the source boundary
Classify the paper type
Build the evidence base before drafting
Generate the fixed Sections 01-16 Paper Card
Run groundedness QA

What it can do on your machine

Read from SKILL.md and the folder at commit e605b35. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 2 files in scripts/ (Python, from the files we listed), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Nature Paper Card loads about 2.1k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 1,015 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~64
When it runs · the whole SKILL.md, loaded when a task matches: ~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~4.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Yuan1z0825/nature-skills at commit e605b35, republished under its Apache-2.0 licence (© Yuan1z0825). 1,015 words, ~2,084 tokens.

Download SKILL.mdSave it as .claude/skills/nature-paper-card/SKILL.md (or your agent's skills folder). This skill also uses 23 other files; get the full folder from GitHub.

name: nature-paper-card
description: Build a structured deep-reading Paper Card for one scientific paper, analysing methods, experiment-to-claim evidence, limitations, and research ideas. Use for 论文精读卡、方法拆解、证据链分析; not full-paper bilingual translation or formal peer review.

Nature Paper Card - Router

Use this skill to turn one paper into an evidence-grounded research card, not a translated abstract, generic summary, reviewer report, or publication article.

The skill uses:

a static core under static/core/ for principles, workflow, and the fixed output contract;
one paper-type fragment under static/fragments/paper_type/;
on-demand references for evidence labels, the exact card schema, and research-idea checks.

Routing protocol

Follow these steps every time.

1. Load the manifest and core layer

Read manifest.yaml, then read every file under always_load. Do not generate the card from this router alone.

2. Establish the source boundary

Identify which material is available:

full paper with figures and tables;
paper text without reliable layout;
abstract or metadata only;
an existing nature-reader artifact with stable source IDs.

Prefer an existing nature-reader artifact when supplied. Do not repeat full bilingual translation or figure extraction. If only partial material is available, create a visibly partial card and mark every unsupported section Not assessable from supplied material.

For a PDF or nature-reader source-map JSON, the bundled script is mandatory.

Resolve SKILL_DIR as the directory containing this loaded SKILL.md.
Verify SKILL_DIR/scripts/prepare_paper.py exists.
Run exactly the bundled script by its resolved path:

text

python "SKILL_DIR/scripts/prepare_paper.py" INPUT \
  --output WORKDIR/source_bundle.json

Add --render-dir WORKDIR/rendered-pages when visual page review is needed. Inspect the script exit code and the bundle validation block before drafting.

For source-map input, also inspect locator_summary and unlocated_blocks. Only records under pages have verified positive PDF page locators. Missing or invalid page locators remain in unlocated_blocks with an explicit status and must be cited structurally, never as page 1.

Never write inline Python, a temporary extraction script, or a replacement script during a Paper Card run. Never patch the bundled scripts during a normal Paper Card run. Modify these scripts only when the user explicitly asks to develop, debug, or improve the skill itself.

Use this fixed locator state machine:

page-grounded: the bundled script succeeds and validates reliable PDF page indices. Use PDF page plus structural locators. Printed page labels are optional metadata.
structure-grounded: page extraction is unreliable, but reliable sections, figures, tables, equations, source blocks, or full text remain available. Do not emit page-number citations.
source-limited: only an abstract, metadata, or user-provided excerpt is reliable. Do not emit page-number citations or infer unseen evidence.

If preparation fails, record the failure. Prefer an existing nature-reader source map or the environment PDF/OCR capability, but do not create a replacement script. Then enter the strongest supported fallback mode.

3. Classify the paper type

Use the manifest to choose one primary paper_type and, only for a genuinely hybrid paper, one secondary contribution lens:

methods
discovery
resource
clinical
materials
review

Load the primary fragment and no more than one secondary fragment. Classify by the paper's argument and evidence structure, not merely its discipline. State both selections before analysis. For example, an algorithm paper that also introduces a substantial dataset may use methods as the primary lens and resource as the secondary lens.

4. Build the evidence base before drafting

Build an internal evidence inventory before drafting. At minimum, enumerate:

bibliographic metadata and access status;
research question and claimed contribution;
method components, assumptions, and data flow;
every main figure, table, and essential equation with its argumentative role;
experiments, baselines, metrics, ablations, and reported results;
author-stated limitations;
stable source pointers to pages, sections, equations, figures, tables, or nature-reader block IDs.

Then build a compact claim-evidence matrix linking each central claim to the evidence that supports it and to any unresolved gap.

Use external search only for Section 04, Section 15, bibliographic verification, or an explicit novelty check. Never present the paper's own related-work narrative as independently verified field history. Record whether the context mode is paper-only, targeted external check, or externally verified.

Show full SKILL.md (401 more words)Show less

5. Generate the fixed Sections 01-16 Paper Card

Apply, in order:

core principles;
the selected paper-type fragment;
core workflow;
output contract.

Read references/evidence-and-provenance.md before making analytical or externally verified claims. Read references/card-schema.md when drafting the final Markdown. Read references/research-idea-gates.md before writing Section 16.

Write a real Markdown artifact, defaulting to paper-card.md. Keep all 16 numbered sections in order, but write Not applicable or Not assessable instead of inventing content.

Match the user's language by default. The skill source and schema remain English, but localize the Paper Card headings and prose when the user writes in another language. Preserve canonical technical terms and formulas.

6. Run groundedness QA

Before delivery, resolve the bundled auditor from SKILL_DIR. In page-grounded mode, run:

text

python "SKILL_DIR/scripts/audit_paper_card.py" \
  --card WORKDIR/paper-card.md \
  --bundle WORKDIR/source_bundle.json \
  --locator-mode page-grounded \
  --report WORKDIR/audit-report.json

In either fallback mode, run the same auditor without a bundle:

text

python "SKILL_DIR/scripts/audit_paper_card.py" \
  --card WORKDIR/paper-card.md \
  --locator-mode structure-grounded-or-source-limited \
  --report WORKDIR/audit-report.json

Replace the last value with the actual canonical mode. Treat audit errors as blockers. Review warnings with scientific judgment rather than suppressing them mechanically.

Also verify:

numerical results match the source;
the evidence inventory covers every main figure and table;
every major method, result, boundary, and limitation has a source pointer;
PDF page pointers distinguish PDF page index from printed page labels;
author statements are separated from Agent analysis;
external field-history claims have external citations or are marked unverified;
proposed ideas are hypotheses, not novelty claims;
Sections 17 and 18 do not exist;
no academic-English collection, comprehension quiz, or public-article draft was added.

If the auditor itself cannot run, state that failure and manually apply only its documented checks. Do not write a substitute auditor.

Script red lines

Do not resolve bundled scripts relative to the user's current working directory.
Do not write or execute inline Python as a substitute for either bundled script.
Do not create extract_pdf.py, parse_paper.py, or another one-off replacement.
Do not patch skill code during a normal Paper Card generation request.
Do not fabricate page numbers when preparation fails.
Do not remove all grounding in fallback mode; use structural locators or explicit source-scope locators.

Relationship to adjacent skills

Use nature-reader for full-text bilingual reading artifacts, extraction, and stable source maps.
Use nature-academic-search when external literature is needed to verify field history or knowledge connections.
Use nature-reviewer for formal reviewer-style manuscript assessment.
Use nature-literature-pipeline for batch discovery and lightweight monitoring notes.
Use nature-paper2ppt when the requested end product is a presentation.

Do not silently switch the requested Paper Card into any of these outputs.

Files

SKILL.md and 23 other files (scripts, references) in skills/nature-paper-card of Yuan1z0825/nature-skills.

SKILL.md
README.md
README_EN.md
agents/openai.yaml
evals/evals.json
manifest.yaml
references/card-schema.md
references/evidence-and-provenance.md
references/research-idea-gates.md
scripts/audit_paper_card.py
scripts/prepare_paper.py
static/core/output-contract.md
static/core/principles.md
static/core/workflow.md
static/fragments
… and 9 more

Open the folder on GitHubat commit e605b35

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in Yuan1z0825/nature-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Nature Paper Card next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Nature Paper Card compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Nature Paper Card this skillYuan1z0825/nature-skills	47k	2 repos	~2.1k	Automated safety check: Pass	Apache-2.0	today
Research SurveyEvoScientist/EvoSkills	478	3 repos	~2.5k	Automated safety check: Pass	Apache-2.0	10 days ago
Research Proposalluwill/research-skills	862	—	~4.5k	Automated safety check: Notes	None	yesterday
Paper NavigatorEvoScientist/EvoSkills	478	—	~6.3k	Automated safety check: Notes	Apache-2.0	10 days ago
Research PlatformZS520L/HanakoPro	103	—	~1.1k	Automated safety check: Pass	Apache-2.0	4 mo ago
Research IdeationGalaxy-Dawn/claude-scholar	5.7k	2 repos	~2.4k	Automated safety check: Pass	MIT	18 days ago

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Questions about Nature Paper Card

What does Nature Paper Card do?

Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source. Output is an evidence-grounded research card for a single paper, not a translated abstract, generic summary, reviewer report or publication article. A router loads a manifest and a static core with principles, workflow and a fixed output contract, then one paper-type fragment, and pulls references on demand for evidence labels, the exact card schema and research-idea checks.

When should I use Nature Paper Card?

Nature Paper Card fits situations like: reading a research paper closely before building on it; mapping which experiments support which claims; listing a paper's limitations and follow-up research ideas.

How do I install Nature Paper Card in Claude Code?

Run `npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a claude-code`. Or copy the skill folder (skills/nature-paper-card in Yuan1z0825/nature-skills) into .claude/skills/nature-paper-card in your project. Claude Code loads it when a task matches its description.

How do I install Nature Paper Card in Codex?

Run `npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a codex`. Or copy the skill folder (skills/nature-paper-card in Yuan1z0825/nature-skills) into .agents/skills/nature-paper-card in your project. Codex loads it when a task matches its description.

Can I use Nature Paper Card in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nature-paper-card, .gemini/skills/nature-paper-card, .github/skills/nature-paper-card and .opencode/skills/nature-paper-card in your project.

What does Nature Paper Card need to run?

Going by SKILL.md and its folder, Nature Paper Card needs Python for the scripts in its folder. Our summary lists: Python, to run scripts/prepare_paper.py on a PDF or source map.

Does Nature Paper Card access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Nature Paper Card safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Nature Paper Card use?

Nature Paper Card is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Nature Paper Card use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Nature Paper Card?

Skills that share tags, products or a category with Nature Paper Card: Research Survey (EvoScientist/EvoSkills, 478 stars), Research Proposal (luwill/research-skills, 862 stars), Paper Navigator (EvoScientist/EvoSkills, 478 stars) and Research Platform (ZS520L/HanakoPro, 103 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nature Paper Card?

Yuan1z0825 (a GitHub user) maintains it in Yuan1z0825/nature-skills, which has 47,222 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 11, 2026.

Source: Yuan1z0825/nature-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Nature Paper Card

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Nature Paper Card - Router

Routing protocol

1. Load the manifest and core layer

2. Establish the source boundary

3. Classify the paper type

4. Build the evidence base before drafting

5. Generate the fixed Sections 01-16 Paper Card

6. Run groundedness QA

Script red lines

Relationship to adjacent skills

Files

Used in 2 other repositories

Compare with similar skills

Similar skills

More from Yuan1z0825/nature-skills

Related

Questions about Nature Paper Card