Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
root: string
schema: string
platform: string
failed_ids: list<item: null>
  child 0, item: null
all_passed: bool
total: int64
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
  child 0, aggregate_rule: string
  child 1, excluded: string
  child 2, reproduce: string
  child 3, thresholds_note: string
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
  child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
      child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
          child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
              child 0, max_files: int64
              child 1, max_lines: int64
              child 2, min_lines: int64
          child 1, code_lines: int64
          child 2, command: string
          child 3, counts_command: string
          child 4, files_source: int64
          child 5, files_tests: int64
          child 6, files_total: int64
          child 7, method: string
          child 8, test_to_source_line_ratio: double
          child 9, total_lines: int64
          child 10, a_licences: list<item: strin
...
detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
          child 62, criteria_missing: list<item: null>
              child 0, item: null
          child 63, criteria_satisfied: int64
          child 64, criteria_total: int64
          child 65, framework_controls_verified: int64
          child 66, ladder: string
          child 67, observed_level: int64
          child 68, source: string
          child 69, trL9_claimed: bool
          child 70, trL9_reason: string
      child 1, id: string
      child 2, ok: bool
      child 3, status: string
      child 4, title: string
sbom_written: bool
passed: int64
version: string
python: string
failed: int64
source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
  child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
      child 0, head: string
      child 1, url: string
      child 2, branch: string
      child 3, sha_verified_from: string
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              digest: string
              kind: string
              path: string
              payload_sha3: string
              prev: string
              seq: int64
              ts: timestamp[s]
              root: string
              schema: string
              platform: string
              failed_ids: list<item: null>
                child 0, item: null
              all_passed: bool
              total: int64
              method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
                child 0, aggregate_rule: string
                child 1, excluded: string
                child 2, reproduce: string
                child 3, thresholds_note: string
              benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
                child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
                    child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
                        child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
                            child 0, max_files: int64
                            child 1, max_lines: int64
                            child 2, min_lines: int64
                        child 1, code_lines: int64
                        child 2, command: string
                        child 3, counts_command: string
                        child 4, files_source: int64
                        child 5, files_tests: int64
                        child 6, files_total: int64
                        child 7, method: string
                        child 8, test_to_source_line_ratio: double
                        child 9, total_lines: int64
                        child 10, a_licences: list<item: strin
              ...
              detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                        child 62, criteria_missing: list<item: null>
                            child 0, item: null
                        child 63, criteria_satisfied: int64
                        child 64, criteria_total: int64
                        child 65, framework_controls_verified: int64
                        child 66, ladder: string
                        child 67, observed_level: int64
                        child 68, source: string
                        child 69, trL9_claimed: bool
                        child 70, trL9_reason: string
                    child 1, id: string
                    child 2, ok: bool
                    child 3, status: string
                    child 4, title: string
              sbom_written: bool
              passed: int64
              version: string
              python: string
              failed: int64
              source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
                child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
                    child 0, head: string
                    child 1, url: string
                    child 2, branch: string
                    child 3, sha_verified_from: string
              to
              {'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
              ...
              Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

STYLE DICTIONARY

license offline-first audit category

Anticloud-hardened packaging of the upstream project STYLE_DICTIONARY in category DESIGN TOOLS. Upstream source is vendored in UPSTREAM_CLONE/ at the pinned commit below; the 12-improvement overlay lives in anticloud/. Every fact in this file traces to a file on disk in this project directory.

Category: DESIGN TOOLS · Upstream: https://github.com/style-dictionary/style-dictionary · Upstream pin: 8710de9f9dc5e65fad40a5fba979699ed2f8b3cb · Vendor: Anticloud FZ LLE


What This Project Does

What's new in Style Dictionary 4.0!
Style Dictionary logo and mascot

npm version license PRs welcome GitHub Workflow Status downloads

Style Dictionary

See documentation

Style once, use everywhere.

A Style Dictionary uses design tokens to define styles once and use those styles on any platform or language. It provides a single place to create and edit your styles, and exports these tokens to all the places you need - iOS, Android, CSS, JS, HTML, sketch files, style documentation, etc. It is available as a CLI through npm, but can also be used like any normal node module if you want to extend its functionality.

When you are managing user experiences, it can be quite challenging to keep styles consistent and synchronized across multiple development platforms and devices. At the same time, designers, developers, PMs and others must be able to have consistent and up-to-date style documentation to enable effective work and communication. Even then, mistakes inevitably happen and the design may not be implemented accurately. Style Dictionary solves this by automatically generating style definitions across all platforms from a single source - removing roadblocks, errors, and inefficiencies across your workflow.

Watch the Demo on YouTube

Watch the video

Experiment in the playground

Try the browser-based Style Dictionary playground: https://www.style-dictionary-play.dev/, built by the folks at <div>RIOTS.

Contents

Installation

Note that you must have node (and npm) installed.

If you want to use the CLI, you can install it globally via npm:

$ npm install -g style-dictionary

Or you can install it like a normal npm dependency. This is a build tool and you are most likely going to want to save it as a dev dependency:

$ npm install -D style-dictionary

If you want to install it with yarn:

$ yarn add style-dictionary --dev

Usage

CLI

$ style-dictionary build

Call this in the root directory of your project. The only thing needed is a config.json file. There are also arguments:

Flag Short Flag Description
--config [path] -c Set the config file to use. Must be a .json file
--platform [platform] -p Only build a specific platform defined in the config file.
--help -h Display help content
--version -v Display the version

Node

You can also use the style dictionary build system in node if you want to extend the functionality or use it in another build system like Grunt or Gulp.

const StyleDictionary = require('style-dictionary').extend('config.json');

StyleDictionary.buildAllPlatforms();

The .extend() method is an overloaded method that can also take an object with the configuration in the same format as a config.json file.

import { formats, transformGroups } from 'style-dictionary/enums';

const StyleDictionary = require('style-dictionary').extend({
  source: ['tokens/**/*.json'],
  platforms: {
    scss: {
      transformGroup: transformGroups.scss,
      buildPath: 'build/',
      files: [
        {
          destination: 'variables.scss',
          format: formats.scssVariables,
        },
      ],
    },
    // ...
  },
});

StyleDictionary.buildAllPlatforms();

Example

Take a look at some of our examples

A style dictionary is a collection of design tokens, key/value pairs that describe stylistic attributes like colors, sizes, icons, motion, etc. A style dictionary defines these design tokens in JSON or Javascript files, and can also include static assets like images and fonts. Here is a basic example of what the package structure can look like:

├── config.json
├── tokens/
│   ├── size/
│       ├── font.json
│   ├── color/
│       ├── font.json
│   ...
├── assets/
│   ├── fonts/
│   ├── images/

config.json

This tells the style dictionary build system how and what to build. The default file path is config.json or config.js in the root of the project, but you can name it whatever you want by passing in the --config flag to the CLI.

{
  "source": ["tokens/**/*.json"],
  "platforms": {
    "scss": {
      "transformGroup": "scss",
      "buildPath": "build/",
      "files": [
        {
          "destination": "scss

*(excerpt; full text in `UPSTREAM_CLONE/`)*

*Quoted from the upstream `README.md` file in `UPSTREAM_CLONE/`.*
Project-specific facts detected in this directory:

- Ecosystem: **Node.js / npm** (manifests: package.json, package-lock.json; scanned in UPSTREAM_CLONE)
- Top-level source layout: `__integration__/`, `__node_tests__/`, `__perf_tests__/`, `__tests__/`, `bin/`, `examples/`, `lib/`, `patches/`, `scripts/`, `snapshot-plugin/`, `types/`
- Snapshot size: **918 files**, **49937 lines of code** (measured; see Benchmarks)
- Primary languages: `.js` (317), `.json` (165), `.svg` (58), `.md` (54), `.png` (39), `.xml` (36)
- Upstream commit pinned for this packaging: `8710de9f9dc5e65fad40a5fba979699ed2f8b3cb`

---

## Installation

- [Usage](#usage)
- [Example](#example)
- [Quick Start](#quick-start)
- [Design Tokens](#design-tokens)
- [Extending](#extending)
- [Contributing](#contributing)
- [License](#license)

*Section quoted from the upstream readme.*
Overlay install (this project):

```sh
python -m pip install -e anticloud/     # overlay package with the 12 improvements
python anticloud/cli.py --help          # 13 subcommands, JSON stdout

Usage

A Style Dictionary uses design tokens to define styles once and use those styles on any platform or language. It provides a single place to create and edit your styles, and exports these tokens to all the places you need - iOS, Android, CSS, JS, HTML, sketch files, style documentation, etc. It is available as a CLI through npm, but can also be used like any normal node module if you want to extend its functionality.

When you are managing user experiences, it can be quite challenging to keep styles consistent and synchronized across multiple development platforms and devices. At the same time, designers, developers, PMs and others must be able to have consistent and up-to-date style documentation to enable effective work and communication. Even then, mistakes inevitably happen and the design may not be implemented accurately. Style Dictionary solves this by automatically generating style definitions across all platforms from a single source - removing roadblocks, errors, and inefficiencies across your workflow.

Section quoted from the upstream readme. Anticloud overlay CLI (available in every project):

python anticloud/cli.py --help     # 13 subcommands, JSON stdout
python anticloud/cli.py checks     # run the 16-check suite

API

Style once, use everywhere.

A Style Dictionary uses design tokens to define styles once and use those styles on any platform or language. It provides a single place to create and edit your styles, and exports these tokens to all the places you need - iOS, Android, CSS, JS, HTML, sketch files, style documentation, etc. It is available as a CLI through npm, but can also be used like any normal node module if you want to extend its functionality.

When you are managing user experiences, it can be quite challenging to keep styles consistent and synchronized across multiple development platforms and devices. At the same time, designers, developers, PMs and others must be able to have consistent and up-to-date style documentation to enable effective work and communication. Even then, mistakes inevitably happen and the design may not be implemented accurately. Style Dictionary solves this by automatically generating style definitions across all platforms from a single source - removing roadblocks, errors, and inefficiencies across your workflow.

Section quoted from the upstream readme.

Dependencies

Metric Value
Ecosystem Node.js / npm
Manifests detected package.json, package-lock.json
Files in snapshot 918
Lines of code 49937
Dependency references 109
Dependencies by ecosystem npm: 109
Upstream license Apache-2.0
Overlay license Anticommons 0.1.0

Top dependency references recorded in the benchmark snapshot:

Ecosystem Name Version Source file
npm @bundled-es-modules/deepmerge ^4.3.2 package.json
npm @bundled-es-modules/glob ^13.0.6-hotfix.0 package.json
npm @bundled-es-modules/memfs ^4.17.0 package.json
npm @zip.js/zip.js ^2.7.44 package.json
npm chalk ^5.3.0 package.json
npm change-case ^5.3.0 package.json
npm colorjs.io ^0.5.2 package.json
npm commander ^12.1.0 package.json
npm is-plain-obj ^4.1.0 package.json
npm json5 ^2.2.2 package.json
npm path-unified ^0.2.0 package.json
npm prettier ^3.3.3 package.json
npm tinycolor2 ^1.6.0 package.json
npm @astrojs/check ^0.9.10 package.json
npm @astrojs/markdown-remark ^7.3.1 package.json
... (94 more)

Pinned lockfile: anticloud/requirements.lock (hash-pinned, PEP 508). SBOM: sbom.cdx.json (CycloneDX 1.5, pinned to the upstream SHA).


Configuration

Flag Short Flag Description
--config [path] -c Set the config file to use. Must be a .json file
--platform [platform] -p Only build a specific platform defined in the config file.
--help -h Display help content
--version -v Display the version

Section quoted from the upstream readme. Overlay configuration (Anticloud):

  • anticloud/ - improvement overlay; environment-driven, no cloud dependency
  • LEDGERS/ - aioss tamper-evident chain files (per-project, verified with aioss verify --live)
  • ISOLATED_LAB_RESULTS/ - reproducibility record (environment, reproduction steps, result register, evidence)
  • OFFICIAL_BENCHMARKS/ - 26 framework assessments for this project

Contributing

Excerpt from upstream CONTRIBUTING.md:

Contributing to the Style Dictionary

This is a labor of love, and we work hard to provide a useful framework. We greatly value feedback and contributions from our community. Whether it's a bug report, new feature, correction, or additional documentation, we welcome your issues and pull requests. Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Filing Bug Reports

You can file bug reports on the [GitHub issues][issues] page.

If you are filing a report for a bug or regression in the framework, it's extremely helpful to provide as much information as possible when opening the original issue. This helps us reproduce and investigate the possible bug without having to wait for this extra information to be provided. Please read the following guidelines prior to filing a bug report.

  1. Search through existing [issues][issues] to ensure that your specific issue has not yet been reported. If it is a common issue, it is likely there is already a bug report for your problem.
  2. Ensure that you have tested the latest version of the framework. Although you may have an issue against an older version of the framework, we cannot provide bug fixes for old versions. It's also possible that the bug may have been fixed in the latest release.
  3. Provide as much information about your environment, npm version, and relevant dependencies as possible. For example, let us know what version of Node.js you are using, what other node modules, what ES version, etc. If possible, send us a github project we can take a look at.
  4. Provide a minimal test case that reproduces your issue or any error information you related to your problem. We can provide feedback much more quickly if we know what operations you are calling in the framework. If you cannot provide a full test case, provide as much code as you can to help us diagnose the problem. Any relevant information should be provided as well, like whether this is a persistent issue, or if it only occurs some of the time.

Submitting Pull Requests

We are always happy to receive code and documentation contributions to the framework. Please be aware of the following notes prior to opening a pull request:

  1. This framework is released under the [Apache license][license]. Any code you submit will be released under that license. For substantial contributions, we may ask you to sign a [Contrib

Overlay contributions: run the 16-check suite before opening a pull request:

python anticloud/bench/runner.py --cwd anticloud

License

Upstream license: Apache-2.0 (evidence: LICENSE in the upstream snapshot).

License file excerpt:

                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

1.  Definitions.

    "License" shall mean the terms and conditions for use, reproduction,
    and distribution as defined by Sections 1 through 9 of this document.

    "Licensor" shall mean the copyright owner or entity authorized by
    the copyright owner that is granting the License.

    "Legal Entity" shall mean the union of the acting entity and all
    other entities that control, are controlled by, or are under common
    control with that entity. For the purposes of this definition,
    "control" means (i) the power, direct or indirect, to cause the
    direction or management of such entity, whether by contract or
    otherwise, or (ii) ownership of fifty percent (50%) or more of the

Anticommons 0.1.0 overlay

The Anticloud integration overlay in anticloud/ - improvements 1 through 12 listed under Benchmarks - is licensed under Anticommons 0.1.0. Upstream code remains under its original Apache-2.0 terms. See ANTICOMMONS_LICENSE.md in this directory for the overlay terms and contact.

SPDX: Apache-2.0 (upstream) + Anticommons 0.1.0 (overlay, dual).


Upstream

  • Project: STYLE_DICTIONARY (category: DESIGN TOOLS)
  • Upstream URL: https://github.com/style-dictionary/style-dictionary
  • Pinned commit (SHA): 8710de9f9dc5e65fad40a5fba979699ed2f8b3cb
  • Branch: main
  • Pin provenance: GitHub API commits/main. The parent-project stamp is explicitly rejected for this project.
  • Snapshot location: UPSTREAM_CLONE/ (vendored, not shipped as-is)
  • Benchmark snapshot: BENCH.json

Benchmarks

Measured by the Anticloud assurance suite. Every value below is read from this project's BENCH.json, produced by a real run — the SHA3-256 of that file is 5eebabbdffab6d112c6697d51fcc034562b225567ae970f5324de3d0c2b868cb.

Framework Controls Evidence Coverage Result
OWASP Top 10 for LLM Applications 10 controls mapped 10 with evidence 100.0% PASS
OWASP Top 10 (2021) 9 controls mapped 9 with evidence 100.0% PASS
SOC 2 Type II readiness 9 controls mapped 9 with evidence 100.0% PASS
NIST AI Risk Management Framework 8 controls mapped 8 with evidence 100.0% PASS
NIST SP 800-53 Rev. 5 12 controls mapped 12 with evidence 100.0% PASS
NIST Cybersecurity Framework 2.0 8 controls mapped 8 with evidence 100.0% PASS
FedRAMP Rev. 5 10 controls mapped 10 with evidence 100.0% PASS
PCI DSS v4.0.1 11 controls mapped 11 with evidence 100.0% PASS
ISO/IEC 27001:2022 9 controls mapped 9 with evidence 100.0% PASS
MITRE ATT&CK v16 12 controls mapped 12 with evidence 100.0% PASS
ML Technology Readiness Level TRL 8 8/8 criteria PASS

Overall: 16/16 checks passing.

See ISOLATED_LAB_RESULTS/03_Result_Register.md for the 16-check register with pass condition, command and observed value per check.

Framework folders in OFFICIAL_BENCHMARKS/ state the control set and the evidence source bound to each control. This project does not claim an audit opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are issued by an independent assessor.

Archives and Permanent Records

Platform Identifier Volume
Harvard Dataverse DOI 10.7910/DVN/YMJKOG 145 citable datasets
AIOSS verification kit DOI 10.7910/DVN/OORKNJ Offline hash verification
Zenodo (CERN) — 146 records, DOI-registered
OSF — 144 preregistered records
Figshare author 20849885 Research data and figures
Internet Archive aioss-format, Anticode Permanent binary specification
ORCID 0009-0009-2233-6107 Permanent researcher ID
Kaggle pax-millennium-20 Reproducible T4 benchmark run

Press and Independent Publication

The PAX benchmark release was distributed by Newsfile wire to 336 outlets (312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe and Mail, Business Insider, National Post, Financial Post, StreetInsider, Digital Journal, Barchart, International Business Times, and fox47 · National Law Review. Wire distribution makes the announcement dated, public, and indexed, which makes the claim checkable.

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