Diagram Design
cathrynlavery/diagram-design
Creates branded diagrams, from architecture, flowchart and sequence to charts and maps, as self-contained HTML with inline SVG, with import from draw.io, Mermaid and Excalidraw.
Write or review docstrings for public modules, classes, and functions in sdm/.
Install Docstring
$ npx skills add NVIDIA/structured-data-models --skill docstring -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/structured-data-models docstring --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/structured-data-models.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/docstring .claude/skills/docstring && rm -rf skills-srcUse ~/.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/
Install the "docstring" agent skill from https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstring into .claude/skills/docstring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docstring", 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 install https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstringType 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.
$ npx skills add NVIDIA/structured-data-models --skill docstring -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/structured-data-models docstring --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/structured-data-models.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/docstring .agents/skills/docstring && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "docstring" agent skill from https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstring into .agents/skills/docstring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docstring", 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.
$ npx skills add NVIDIA/structured-data-models --skill docstring -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/structured-data-models docstring --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/structured-data-models.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/docstring .cursor/skills/docstring && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "docstring" agent skill from https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstring into .cursor/skills/docstring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docstring", 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 https://github.com/NVIDIA/structured-data-models.git --path .agents/skills/docstring--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/structured-data-models --skill docstring -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/structured-data-models docstring --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/structured-data-models.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/docstring .gemini/skills/docstring && rm -rf skills-srcUse ~/.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/
Install the "docstring" agent skill from https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstring into .gemini/skills/docstring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docstring", 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.
$ gh skill install NVIDIA/structured-data-models docstringInstalls 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).
$ npx skills add NVIDIA/structured-data-models --skill docstring -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/structured-data-models.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/docstring .github/skills/docstring && rm -rf skills-srcUse ~/.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/
Install the "docstring" agent skill from https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstring into .github/skills/docstring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docstring", 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.
$ npx skills add NVIDIA/structured-data-models --skill docstring -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/structured-data-models docstring --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/structured-data-models.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/docstring .opencode/skills/docstring && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "docstring" agent skill from https://github.com/NVIDIA/structured-data-models/tree/main/.agents/skills/docstring into .opencode/skills/docstring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docstring", 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
docstring- GitHub stars
- 310
- Token cost
- ~1.2k tokens
- SKILL.md length
- 341 words
- Files
- 1
- Skills in repo
- 3
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Write or review docstrings for public modules, classes, and functions in sdm/.
- Reviewing docstrings to follow repo best practices (Args sections
- SKILL.md covers General Principles, Example, Sphinx Cross-Referencing… and Verification
- Calls uv; reaches arxiv.org and docs.pytorch.org
- Paper citations
What it does
Docstring is an agent skill from NVIDIA/structured-data-models, published by the product's own GitHub organization. Write or review docstrings for public modules, classes, and functions in sdm/. Use when adding or reviewing docstrings to follow repo best practices (Args sections, paper citations, tensor shape notation).
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Technical documentation. The repository describes itself as: Foundation Models for Structured Data. The licence is Apache-2.0.
When your agent uses it
- Reviewing docstrings to follow repo best practices (Args sections
- Paper citations
- Tensor shape notation)
Example prompts
- “/docstring”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 2be5e60. 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
Shell commands in SKILL.md call:
uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
arxiv.orgdocs.pytorch.org
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
Docstring loads about 1.2k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 341 words of instructions outside code blocks.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from NVIDIA/structured-data-models at commit 2be5e60, republished under its Apache-2.0 licence (© NVIDIA). 341 words, ~1,233 tokens.
Download SKILL.mdSave it as
.claude/skills/docstring/SKILL.md (or your agent's skills folder).- name
- docstring
- description
- Write or review docstrings for public modules, classes, and functions in sdm/. Use when adding or reviewing docstrings to follow repo best practices (Args sections, paper citations, tensor shape notation).
Docstring Writing and Reviewing Guide
Use this when writing or reviewing docstrings for public modules, classes, and functions in sdm/.
Follow these best practices up front to keep docstrings consistent across the codebase.
General Principles
- Keep docstrings as minimal as possible and avoid documenting implementation details.
- Do not add module-level docstrings to individual modules; keep only a short package summary in the package
__init__.py. - Every public class and function has a docstring, a one-line summary, then an
Args:section. - When a class or function implements functionality proposed in an academic paper, cite it in the first sentence of its docstring.
- Document every public parameter, especially, constructor parameters. Document them in the class docstring's
Args:, not in__init__. - Use
r"""..."""whenever the docstring contains math, LaTeX, or backslashes (e.g., a.. math::block). - Describe tensor parameters with their shape in double-backtick notation, using a leading
...for the batch dimensions (e.g.,[..., S, H, C]). Spell out each remaining dimension letter, and keep the notation consistent across related processors/modules. - If splitting a long line leads to a line-too-long error, put
# noqa: <code>to ignore the error. - Document non-obvious behavior: implicit caps, defaults, transformations, or side effects that affect results. If it would surprise a caller, state it.
- Do not add docstrings to methods that already have one in superclass's methods even if the class/methods are public. For example,
Processor.transform()already has a general docstring that's applicable to its subclasses. In this case, put a comment# noqa: D102to ignore the linter error.
Example
class MyClass:
r"""My Class from the `"My Paper" <https://arxiv.org/abs/2602.11139>`_ paper.
.. math::
y = \frac{x}{\sqrt{d}}
Args:
fill_value: Value written into masked positions. Capped at ``1.0``;
larger values are silently clamped.
"""
def __init__(self, fill_value: float) -> None:
...
def forward(self, x: Tensor) -> Tensor:
"""Normalize ``x`` along its last dimension.
Args:
x: Input tensor with shape ``[..., S, C]``.
Returns:
Tensor with shape ``[..., S, C]``.
"""
def citation(self) -> str:
"""Return the key from :func:`sdm.refs.resolve_default_citation_key`.""" # noqa: E501Sphinx Cross-Referencing Reference
The same roles resolve internal sdm targets and external ones. Prefer
cross-reference roles over plain literals, e.g.,
""":class:`pandas.DataFrame`"""over
"""``pandas.DataFrame``"""whenever the target lives in an intersphinx-mapped project (python, torch, numpy,
pandas, pyarrow, cudf, typing_extensions; see intersphinx_mapping
in docs/source/conf.py).
r"""
- :mod:`sdm.nn`: Module reference.
- :class:`~sdm.nn.Module`: Class reference. External targets use the same
role: :class:`pandas.DataFrame`, :class:`torch.nn.Module`, :class:`dict`,
:class:`TypeError`, :class:`collections.abc.Mapping`.
- :class:`~pyarrow.Array`: Leading ``~`` renders only ``Array``. Use it in
summary lines; keep the full path in ``Args:`` entries.
- :meth:`~sdm.nn.Module.forward`: Method reference.
- :func:`torch.nn.functional.scaled_dot_product_attention`: Function
reference. Use :func: for free functions and :meth: only for methods.
- :attr:`attribute`: Attribute reference.
- :math:`equation`: Inline math.
- :ref:`label`: Internal label reference.
- :ref:`calling convention <torch-dispatch-calling-convention>`: External
label reference with custom link text, resolved through intersphinx.
- :external+torch:ref:`torch.int32 <dtype-doc>`: Label reference pinned to a
specific project's inventory. Use for targets without their own API entry
(e.g., dtypes like ``torch.int32`` resolve to the ``dtype-doc`` label).
Never guess label names: search the linked documentation for a fitting
target by dumping the project's inventory, e.g.
``uv run --no-default-groups --group doc python -m sphinx.ext.intersphinx https://docs.pytorch.org/docs/stable/objects.inv | grep -i dtype``.
"""Verification
Run uv run ruff check. This is a structural backstop only: it flags missing public class/method/function docstrings, capitalization, end punctuation, r""" for backslashes, and Args:/signature mismatches.
It does not require an Args: section to exist, or verify citations, shape notation, or behavior notes — confirm those by hand against the principles above.
© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .agents/skills/docstring of NVIDIA/structured-data-models.
Open the folder on GitHubat commit 2be5e60
Compare with similar skills
Docstring 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Docstring this skillNVIDIA/structured-data-models | 310 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Diagram Designcathrynlavery/diagram-design | 44k | 1 repos | ~7.5k | Automated safety check: Pass | MIT | |
| Simple Englishmoeru-ai/airi | 50k | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Get API Docs with chubandrewyng/context-hub | 14k | 2 repos | ~775 | Automated safety check: Pass | MIT | |
| Doc SyncJetBrains/ideavim | 10k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Mailspring App ScreenshotsFoundry376/Mailspring | 18k | — | ~1.4k | Automated safety check: Pass | GPL-3.0 |
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Related
Categories
Questions about Docstring
What does Docstring do?
Write or review docstrings for public modules, classes, and functions in sdm/. Docstring is an agent skill from NVIDIA/structured-data-models, published by the product's own GitHub organization. Write or review docstrings for public modules, classes, and functions in sdm/.
When should I use Docstring?
Docstring fits situations like: reviewing docstrings to follow repo best practices (Args sections; paper citations; tensor shape notation).
How do I install Docstring in Claude Code?
Run `npx skills add NVIDIA/structured-data-models --skill docstring -a claude-code`. Or copy the skill folder (.agents/skills/docstring in NVIDIA/structured-data-models) into .claude/skills/docstring in your project. Claude Code loads it when a task matches its description.
How do I install Docstring in Codex?
Run `npx skills add NVIDIA/structured-data-models --skill docstring -a codex`. Or copy the skill folder (.agents/skills/docstring in NVIDIA/structured-data-models) into .agents/skills/docstring in your project. Codex loads it when a task matches its description.
Can I use Docstring 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 NVIDIA/structured-data-models --skill docstring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/docstring, .gemini/skills/docstring, .github/skills/docstring and .opencode/skills/docstring in your project.
What does Docstring need to run?
Going by SKILL.md and its folder, Docstring needs the command-line tools its instructions call (uv). Our summary lists: Python 3.
Does Docstring access the network?
SKILL.md names 2 domains. In commands or code: arxiv.org and docs.pytorch.org; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Is Docstring 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. Review the folder before installing.
What licence does Docstring use?
Docstring 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 Docstring use?
About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Docstring?
Skills that share tags, products or a category with Docstring: Diagram Design (cathrynlavery/diagram-design, 44k stars), Simple English (moeru-ai/airi, 50k stars), Get API Docs with chub (andrewyng/context-hub, 14k stars) and Doc Sync (JetBrains/ideavim, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Docstring?
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/structured-data-models, which has 310 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 7, 2026.
Source: NVIDIA/structured-data-models on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.