公开记录优秀
软件健康报告模式 0.26.0 · 指标 1.13.0 · 2026-07-22 01:49 UTC
pandas-dev / pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandas-dev/pandas 的健康指数为 100 分中的 90 分，处于「优秀」区间。 其得分最高的类别是Vitality（96/100），最低的是AI Readiness（62/100）。 最近一次更新在今天。 近期的大部分工作由 4 位贡献者完成。
90
总分 / 100软件健康指数
指标归入加权类别，统一采用 1–100 量表。总体分先取类别加权平均；当公开证据触发高风险司法辖区政策时，评级会按政策调整，并设置 49（有风险）的上限。AI 就绪度不计入总体分。
90
优秀85-100堪称典范；基本满足所有检验标准
良好70-84健康；仅有轻微不足
中等50-69可接受，但存在明显不足；建议进行审查
存在风险30-49存在重大薄弱环节；采用时应保持审慎
危急1-29问题严重（项目被弃置、仅有单一维护者、缺乏基本工程规范）
评分画像
每条轴代表一个类别。形状比平均值更重要——健康的对象会填满整个图形，而“一峰一谷”式画像意味着某一维度的优势正掩盖另一维度的风险。
所有权
软件包生态系统
| 注册表 | 软件包 | 版本 | 月下载量 | 版本数 | 最近发布 |
|---|---|---|---|---|---|
| PyPI | pandas | 3.0.3 | - | 116 | 71 天前 |
按类别列示的指标
活力
项目是否仍有生命——是否仍在编写代码，是否仍在发布版本？
96
开发活跃度
100优秀
评分方式
| 36/36 | 推送新近度 — 最近一次推送于 0 天前 |
| 36/36 | 提交节奏 — 52 周中有 52 周有提交 |
| 18/18 | 提交量 — 最近一年 2,158 次提交 |
| 10/10 | OpenSSF Scorecard：Maintained — 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10 |
所用输入
| commits_last_year | 2,158 |
| human_commit_share | 0.95 |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
发布纪律
90优秀
评分方式
| 27/27 | 有发布版本 — 已发布 100 个发布版本 |
| 36/36 | 发布时效 — 最近一次发布版本于 23 天前 |
| 27/27 | 发布节奏 — 约每 34.6 天发布一次 |
| 0/10 | OpenSSF Scorecard：Signed-Releases — Project has not signed or included provenance with any releases. |
所用输入
| releases_count | 100 |
| latest_release_tag | v3.0.4 |
| releases_from_tags | 否 |
| days_since_latest_release | 23 |
| mean_days_between_releases | 34.6 |
社区与采用
项目是否拥有用户、下载量与关注度，并具备欢迎贡献者参与的配置？
96
流行度与采用
100优秀
评分方式
| 60/60 | 星标 — 49,285 个星标 |
| 25/25 | 复刻 — 20,152 个复刻 |
| 15/15 | 关注者 — 1,117 位关注者 |
所用输入
| forks | 20,152 |
| stars | 49,285 |
| watchers | 1,117 |
| growth_state | organic |
| growth_factor_pct | 100 |
社区健康
92优秀
评分方式
| 22.5/22.5 | README |
| 22.5/22.5 | 许可证 — 可识别的许可证（BSD-3-Clause） |
| 18/18 | CONTRIBUTING 指南 |
| 13.5/13.5 | 行为准则 |
| 0/7.2 | 议题模板 |
| 6.3/6.3 | PR 模板 |
所用输入
| has_readme | 是 |
| has_license | 是 |
| has_contributing | 是 |
| has_issue_template | 否 |
| has_code_of_conduct | 是 |
| has_pull_request_template | 是 |
可持续性与治理
项目能否在其成员之外延续——巴士系数、响应能力、由谁支持，以及软件包的维护状况？
83
维护者韧性（巴士系数）
85优秀
评分方式
| 43.2/54 | 巴士系数 — 4 位贡献者贡献了半数提交 |
| 18.1/22.5 | 提交分布 — 头号贡献者编写了 20% 的提交 |
| 13.5/13.5 | 贡献者广度 — 97 位贡献者 |
| 10/10 | OpenSSF Scorecard：Contributors — project has 49 contributing companies or organizations |
所用输入
| bus_factor | 4 |
| contributors_sampled | 97 |
| top_contributor_share | 0.197 |
议题与 PR 响应能力
75良好
评分方式
| 42.3/46.8 | 议题解决 — 90% 的议题已关闭 |
| 29.6/38.3 | PR 接受 — 已裁定的 PR 中 29,182/37,702 已合并 |
| 3/15 | OpenSSF Scorecard：Code-Review — Found 7/29 approved changesets -- score normalized to 2 |
所用输入
| merged_prs | 29,182 |
| open_issues | 2,706 |
| closed_issues | 25,703 |
| issue_closed_ratio | 0.905 |
| closed_unmerged_prs | 8,520 |
所有权与托管责任
76良好
评分方式
| 30/30 | 所有权背书 — 组织持有 |
| 0/20 | 已验证域名 |
| 25/25 | 所有者影响力 — pandas-dev 有 5,338 位关注者 |
| 21/25 | 既往记录 — 16 个公开仓库，账户约 9 年 |
所用输入
| followers | 5,338 |
| owner_type | Organization |
| is_verified | — |
| owner_login | pandas-dev |
| public_repos | 16 |
| account_age_days | 3,619 |
软件包维护
100优秀
评分方式
| 25/25 | 已发布且可解析 — pypi 上有 1 个软件包 |
| 35/35 | 发布时效 — 最近一次发布于 71 天前 |
| 20/20 | 版本历史 — 116 个已发布版本 |
| 20/20 | 未被弃用 — 活跃，未被弃用或撤回 |
所用输入
| packages | pandas |
| ecosystems | pypi |
| any_deprecated | 否 |
| min_days_since_publish | 71 |
工程质量
基础的工程与文档实践是否到位？
92
工程实践
94优秀
评分方式
| 24/24 | CI 工作流 — 12 个工作流 |
| 24/24 | 存在测试 |
| 16/16 | Linter 配置 |
| 9.6/9.6 | Pre-commit 钩子 |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard：CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
所用输入
| has_ci | 是 |
| has_tests | 是 |
| has_editorconfig | 否 |
| has_linter_config | 是 |
| has_precommit_config | 是 |
文档
90优秀
评分方式
| 30/30 | README |
| 25/25 | 文档目录 |
| 15/15 | 文档 / 主页站点 — https://pandas.pydata.org |
| 10/10 | 仓库描述 |
| 10/10 | 主题标签 — 6 个主题标签 |
| 0/10 | Wiki |
所用输入
| topics | data-analysis, pandas, flexible, alignment, python, data-science |
| has_wiki | 否 |
| homepage | https://pandas.pydata.org |
| has_readme | 是 |
| has_docs_dir | 是 |
| has_description | 是 |
安全
可见的安全与供应链实践是否稳固，且不存在未解决的高风险司法辖区暴露？
81
安全态势
76良好
评分方式
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — 无数据 |
| 2.5/2.5 | CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 1.5/7.5 | Code-Review — Found 7/29 approved changesets -- score normalized to 2 |
| 2.5/2.5 | Contributors — project has 49 contributing companies or organizations |
| 0/10 | Dangerous-Workflow — 无数据 |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 5/5 | Fuzzing — project is fuzzed |
| 2.5/2.5 | 许可证 — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — 无数据 |
| 0/5 | Pinned-Dependencies — 无数据 |
| 4.5/5 | SAST — SAST tool is not run on all commits -- score normalized to 9 |
| 5/5 | Security-Policy — security policy file detected |
| 0/7.5 | Signed-Releases — Project has not signed or included provenance with any releases. |
| 0/7.5 | Token-Permissions — 无数据 |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
所用输入
| source | openssf_scorecard |
| checks_evaluated | 13 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 5 |
| scorecard_aggregate | 7.6 |
已排除计分（无数据或不适用）：branch_protection, dangerous_workflow, packaging, pinned_dependencies, token_permissions。 其余权重已重新归一化。
依赖安全公告
100优秀
评分方式
| 35/35 | 直接依赖不含已知公告 — 没有直接依赖携带已知公告 |
| 25/25 | 间接依赖不含已知公告 — 没有间接依赖携带已知公告 |
| 0/40 | 没有长期未处理的公告 — 没有公告带有发布日期 |
所用输入
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 3 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
已排除计分（无数据或不适用）：没有长期未处理的公告。 其余权重已重新归一化。 比对的是 pypi:pandas@3.0.3 的运行时依赖闭包——安装已发布的软件包时真正被拉取进来的内容——共 3 个软件包。 未对可达性进行分析。
AI 就绪度
该仓库在多大程度上具备与 AI 编码代理协同开发与维护的条件？这是一枚独立的实验性徽章——权重为 0.0，因此单独呈现，不影响总体健康评分。
62
AI 代理上下文与指引
85优秀
评分方式
| 45/45 | 代理指令 — AGENTS.md |
| 0/15 | 机器可读文档（llms.txt） |
| 40/40 | 可读的提交历史 — 95 次人类提交中有 85 次说明了意图（结构化标题或解释性正文） |
所用输入
| has_llms_txt | 否 |
| legible_history_share | 0.895 |
| agent_instruction_files | AGENTS.md |
| agent_instruction_max_bytes | 2,827 |
评分方式
| 0/18 | 一条命令的引导启动 |
| 22/22 | 自动化测试 |
| 11/11 | Lint / 格式化配置 |
| 0/11 | 静态类型检查 |
| 0/10 | 可复现环境 |
| 10/10 | 已体现的代理实践 — 最近 100 次提交中有 79 次由代理编写或署名代理 |
| 8/8 | 自动化维护 — 最近 100 次提交中有 4 次为自动依赖更新 |
| 0/10 | OpenSSF Scorecard：Pinned-Dependencies — 无数据 |
所用输入
| has_nix | 否 |
| has_tests | 是 |
| lockfiles | — |
| has_dockerfile | 否 |
| typed_language | 否 |
| bootstrap_files | — |
| has_devcontainer | 否 |
| has_linter_config | 是 |
| typecheck_configs | — |
| agent_commit_share | 0.79 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0.04 |
已排除计分（无数据或不适用）：OpenSSF Scorecard：Pinned-Dependencies。 其余权重已重新归一化。
面向模型的代码可读性
52中等
评分方式
| 0/45 | 可类型检查的代码 — Python，未配置类型检查 |
| 52.2/55 | 可控的文件大小 — 采样的 1,542 个源文件中有 79 个超过 60KB |
所用输入
| primary_language | Python |
| largest_source_bytes | 691,047 |
| source_files_sampled | 1,542 |
| oversized_source_files | 79 |
机器可读接口
40存在风险
评分方式
| 0/40 | API 模式（OpenAPI/GraphQL/proto） |
| 0/20 | MCP 服务器 |
| 40/40 | 可运行示例 — notebooks |
所用输入
| example_dirs | notebooks |
| has_mcp_signal | 否 |
| api_schema_files | — |
关键数据
49,285GitHub 星标
97贡献者
2,158最近 12 个月提交数
0距最近推送天数
100发布版本数
4巴士系数（bus factor）
2,706开放议题
PyPI软件包生态系统数
更多细节
Star 与 Fork 历史 49,285 ★ / 20,152 ⇿
49,285Star
20,152Fork
6发布
每颗 star 和每个 fork 的添加时间，来自 GitHub 并按天汇总。累计增长位于其构成来源——每日新增——的正上方，二者可相互对照：稳定的自然增长与短暂的突增形态截然不同。当这一差别可被衡量时，它会作为增长真实性予以报告。
仅显示最近的历史——该仓库超出采集窗口，因此未采集最早的历史记录。
主版本 1次版本 0修订 4
OpenSSF Scorecard 7.6 / 10
7.6综合
来自开源项目 OpenSSF Scorecard 的独立、工具无关的安全评估。每项检查奖励的是安全实践本身，而非特定供应商的工具。Scorecard 无法判定的检查项标记为 不适用，并从安全评分中剔除（绝不按零分计）。
| 10 | Binary-Artifacts | no binaries found in the repo |
| 不适用 | Branch-Protection | internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md |
| 10 | CI-Tests | 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 2 | Code-Review | Found 7/29 approved changesets -- score normalized to 2 |
| 10 | Contributors | project has 49 contributing companies or organizations |
| 不适用 | Dangerous-Workflow | no workflows found |
| 10 | Dependency-Update-Tool | update tool detected |
| 10 | Fuzzing | project is fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10 |
| 不适用 | Packaging | packaging workflow not detected |
| 不适用 | Pinned-Dependencies | no dependencies found |
| 9 | SAST | SAST tool is not run on all commits -- score normalized to 9 |
| 10 | Security-Policy | security policy file detected |
| 0 | Signed-Releases | Project has not signed or included provenance with any releases. |
| 不适用 | Token-Permissions | No tokens found |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
直接依赖 5
| 注册表 | 软件包 | 版本约束 | 清单文件 |
|---|---|---|---|
| PyPI | numpy | >=1.26.0 | pyproject.toml |
| PyPI | numpy | >=2.3.3 | pyproject.toml |
| PyPI | python-dateutil | >=2.8.2 | pyproject.toml |
| PyPI | tzdata | — | pyproject.toml |
| PyPI | tzdata | — | pyproject.toml |
全部依赖 86
来自 GitHub 依赖图的完整解析依赖集合：3 个直接依赖与 83 个间接（传递）软件包。仓库提交锁文件时，传递闭包才是完整的。
| 注册表 | 软件包 | 版本 | 关系 |
|---|---|---|---|
| PyPI | numpy | — | 直接 |
| PyPI | python-dateutil | — | 直接 |
| PyPI | tzdata | — | 直接 |
| PyPI | adbc-driver-postgresql | — | 间接 |
| PyPI | adbc-driver-sqlite | — | 间接 |
| PyPI | asv | — | 间接 |
| PyPI | beautifulsoup4 | — | 间接 |
| PyPI | bottleneck | — | 间接 |
| PyPI | coverage | — | 间接 |
| PyPI | cython | — | 间接 |
| PyPI | dask | — | 间接 |
| PyPI | fastparquet | — | 间接 |
| PyPI | feedparser | — | 间接 |
| PyPI | fsspec | — | 间接 |
| PyPI | gcsfs | — | 间接 |
| PyPI | gitpython | — | 间接 |
| PyPI | html5lib | — | 间接 |
| PyPI | hypothesis | — | 间接 |
| PyPI | ipykernel | — | 间接 |
| PyPI | ipython | — | 间接 |
| PyPI | ipywidgets | — | 间接 |
| PyPI | jinja2 | — | 间接 |
| PyPI | jupyterlite-core | — | 间接 |
| PyPI | jupyterlite-pyodide-kernel | — | 间接 |
| PyPI | lxml | — | 间接 |
| PyPI | markdown | — | 间接 |
| PyPI | matplotlib | — | 间接 |
| PyPI | meson | — | 间接 |
| PyPI | meson-python | — | 间接 |
| PyPI | moto | — | 间接 |
| PyPI | mypy | 2.1.0 | 间接 |
| PyPI | natsort | — | 间接 |
| PyPI | nbconvert | — | 间接 |
| PyPI | nbformat | — | 间接 |
| PyPI | nbsphinx | — | 间接 |
| PyPI | notebook | — | 间接 |
| PyPI | numba | — | 间接 |
| PyPI | numexpr | — | 间接 |
| PyPI | numpydoc | — | 间接 |
| PyPI | odfpy | — | 间接 |
| PyPI | openpyxl | — | 间接 |
| PyPI | pandoc | — | 间接 |
| PyPI | pickleshare | — | 间接 |
| PyPI | pip | — | 间接 |
| PyPI | pre-commit | — | 间接 |
| PyPI | psycopg2 | — | 间接 |
| PyPI | psycopg2-binary | — | 间接 |
| PyPI | py-rattler | — | 间接 |
| PyPI | pyarrow | — | 间接 |
| PyPI | pygments | — | 间接 |
| PyPI | pyiceberg | — | 间接 |
| PyPI | pymysql | — | 间接 |
| PyPI | pyqt5 | — | 间接 |
| PyPI | pyreadstat | — | 间接 |
| PyPI | pytest | — | 间接 |
| PyPI | pytest-cov | — | 间接 |
| PyPI | pytest-cython | — | 间接 |
| PyPI | pytest-localserver | — | 间接 |
| PyPI | pytest-qt | — | 间接 |
| PyPI | pytest-xdist | — | 间接 |
| PyPI | python-calamine | — | 间接 |
| PyPI | pytz | — | 间接 |
| PyPI | pyxlsb | — | 间接 |
| PyPI | pyyaml | — | 间接 |
| PyPI | qtpy | — | 间接 |
| PyPI | requests | — | 间接 |
| PyPI | s3fs | — | 间接 |
| PyPI | scipy | — | 间接 |
| PyPI | scipy-stubs | — | 间接 |
| PyPI | seaborn | — | 间接 |
| PyPI | sphinx | — | 间接 |
| PyPI | sphinx-copybutton | — | 间接 |
| PyPI | sphinx-design | — | 间接 |
| PyPI | sqlalchemy | — | 间接 |
| PyPI | tables | — | 间接 |
| PyPI | tabulate | — | 间接 |
| PyPI | tokenize-rt | — | 间接 |
| PyPI | types-pymysql | — | 间接 |
| PyPI | types-python-dateutil | — | 间接 |
| PyPI | types-pytz | — | 间接 |
| PyPI | types-pyyaml | — | 间接 |
| PyPI | versioneer | — | 间接 |
| PyPI | xarray | — | 间接 |
| PyPI | xlrd | — | 间接 |
| PyPI | xlsxwriter | — | 间接 |
| PyPI | zstandard | — | 间接 |
依赖安全公告 0
安装 pypi:pandas@3.0.3 会引入 3 个包（直接与传递）：其中 0 个存在已知公告，0 个为直接依赖。
没有已知公告影响已评估的依赖。
公告表示依赖图中记录的版本落入某条公告的受影响范围。可达性未经分析，且依赖图包含开发与测试的版本固定——某项发现可能只涉及工具链而非交付的软件。
原始 JSON 报告 机器可读
{
"data": {
"repo": {
"topics": [
"data-analysis",
"pandas",
"flexible",
"alignment",
"python",
"data-science"
],
"is_fork": false,
"size_kb": 402112,
"has_wiki": false,
"homepage": "https://pandas.pydata.org",
"languages": {
"C": 376146,
"C++": 24439,
"CSS": 9371,
"HTML": 285657,
"XSLT": 1196,
"Meson": 15262,
"Cython": 1658038,
"Python": 23268964,
"Smarty": 127,
"Go Template": 8725
},
"pushed_at": "2026-07-22T01:15:37Z",
"created_at": "2010-08-24T01:37:33Z",
"owner_type": "Organization",
"updated_at": "2026-07-22T01:21:54Z",
"description": "Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more",
"is_archived": false,
"is_disabled": false,
"license_spdx": "BSD-3-Clause",
"default_branch": "main",
"license_spdx_raw": "BSD-3-Clause",
"primary_language": "Python",
"significant_languages": [
"Python"
]
},
"owner": {
"blog": "http://pandas.pydata.org",
"name": "pandas",
"type": "Organization",
"login": "pandas-dev",
"company": null,
"location": null,
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},
{
"key": "packaging",
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{
"code": "no_data",
"params": {}
}
],
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{
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{
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],
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{
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{
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"points": 5,
"status": "met",
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},
{
"key": "signed_releases",
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"points": 0,
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},
{
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{
"code": "no_data",
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}
],
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{
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}
]
},
{
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"notes": [
{
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{
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"direct_affected_packages": 0
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"components": [
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{
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"code": "no_indirect_advisories",
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{
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"note": null,
"notes": [],
"value": 100,
"inputs": {
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"red_flag": false,
"assessed_packages": 3,
"malicious_packages": 0,
"direct_malicious_packages": 0,
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"installable_malicious_packages": 0
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"components": [
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{
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{
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"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
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"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
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"name": "AI Readiness",
"value": 62,
"weight": 0,
"metrics": [
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"note": null,
"notes": [],
"value": 85,
"inputs": {
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"points": 0,
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"points": 40,
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{
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},
{
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"code": "excluded_no_data",
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{
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"components": [
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"points": 0,
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{
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"points": 22,
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{
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"points": 11,
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{
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"points": 0,
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"points": 0,
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"points": 10,
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{
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"points": 8,
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{
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"notes": [],
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"largest_source_bytes": 691047,
"source_files_sampled": 1542,
"oversized_source_files": 79
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"components": [
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"points": 0,
"status": "missed",
"details": [
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],
"max_points": 45
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{
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"points": 52.2,
"status": "partial",
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"points": 0,
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{
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"points": 0,
"status": "missed",
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{
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