公开记录
软件健康报告模式 0.34.0 · 指标 2.10.0 · 2026-10-19 19:20 UTC

datris / datris-platform-oss

The Data Control Plane for AI Agents — acquire, validate, and land data over MCP with scoped keys, approval gates, and an audit log. Self-hosted, open source.

Scala · TypeScript · PythonAGPL-3.0★ 12 星标⑂ 1 复刻始于 2026年3月在 GitHub 上查看 ↗
类型网络服务命令行工具MCP 服务器库网页界面如何判定
#ai-agents#claude#data-engineering#data-ingestion#data-pipeline#data-quality#etl#llm#mcp#mcp-server#model-context-protocol#rag#self-hosted#vector-database

datris/datris-platform-oss 的健康指数为 100 分中的 80 分，处于「优秀」区间。 其得分最高的类别是Vitality（87/100），最低的是Community & Adoption（48/100）。 最近一次更新在今天。 近期的大部分工作由 1 位贡献者完成。

80
总分 / 100
优秀

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，再依据公开记录的分布进行校准，使各等级具有百分位含义；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 34（存在风险）的上限。

80
卓越93-100公开记录中的最高层级（约前 5%）；基本满足所有检验标准
优秀80-92各方面均表现强劲；仅有少量不足
良好65-79健康；不足之处有限且可控
中等50-64可接受，但存在明显不足；建议进行审查
薄弱35-49多个领域存在实质性薄弱环节
存在风险20-34存在重大薄弱环节；采用时应保持审慎
危急1-19问题严重（项目被弃置、仅有单一维护者、缺乏基本工程规范）
活力社区与采用可持续性与治理工程质量安全AI 就绪度

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。

加权总体分 68 经校准后在公布的指数量表上为 80（记录校准 2026-08-02）。

所有权

Datris.ai个人账户
1 关注者9 个公开仓库始于 2026年3月Datris.ai

该仓库由个人账户拥有。相较于组织支持的项目，单一所有者项目的延续性风险更高。

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标签
PyPIdatris-mcp-server1.52.010,1461380 天前ai-agentchromadata-platformdata-qualitydatabricksdatrisetlhashicorp-vaultkafkamcpmilvusminiomodel-context-protocolmongodbpgvectorpostgresqlqdrantsnowflakevector-searchweaviate

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？

87优秀 · 占总体的 21%

开发活跃度

86优秀
评分方式
36/36推送新近度 — 最近一次推送于 0 天前
21.5/36提交节奏 — 52 周中有 31 周有提交
18/18提交量 — 最近一年 1,125 次提交
10/10OpenSSF Scorecard：Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
所用输入
commits_last_year1,125
human_commit_share1
days_since_last_push0
active_weeks_last_year31

发布纪律

88优秀
评分方式
16.2/27有发布版本 — 100 个版本标签（无 GitHub 发布版本）
36/36发布时效 — 最近一次发布版本于 0 天前
27/27发布节奏 — 约每 1.2 天发布一次
0/10OpenSSF Scorecard：Signed-Releases — 无数据
所用输入
releases_count100
latest_release_tagv1.52.0
releases_from_tags是
days_since_latest_release0
mean_days_between_releases1.2
已排除计分（无数据或不适用）：OpenSSF Scorecard：Signed-Releases。 其余权重已重新归一化。

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？

48薄弱 · 占总体的 17%

流行度与采用

17危急
评分方式
16.9/60星标 — 12 个星标
0/25复刻 — 1 个复刻
0/15关注者 — 0 位关注者
所用输入
forks1
stars12
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

社区健康

70良好
评分方式
22.5/22.5README
22.5/22.5许可证 — 可识别的许可证（AGPL-3.0）
18/18CONTRIBUTING 指南
0/13.5行为准则
0/7.2议题模板
0/6.3PR 模板
所用输入
has_readme是
has_license是
readme_badges4
has_contributing是
has_issue_template否
has_code_of_conduct否
readme_badge_servicesshields.io
has_pull_request_template否

生态采用（下载量）

67良好
评分方式
53.4/80月度下载量 — pypi 合计每月 10,146 次下载
0/20注册表被依赖数 — 该生态系统不报告此项
所用输入
packagesdatris-mcp-server
dependents—
ecosystemspypi
total_downloads—
monthly_downloads10,146
unverified_packages_excluded—
已排除计分（无数据或不适用）：注册表被依赖数。 其余权重已重新归一化。

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？

50中等 · 占总体的 23%

维护者韧性（巴士系数）

13危急
评分方式
9/54巴士系数 — 1 位贡献者贡献了半数提交
0/22.5提交分布 — 头号贡献者编写了 100% 的提交
1.4/13.5贡献者广度 — 1 位贡献者
3/10OpenSSF Scorecard：Contributors — project has 1 contributing companies or organizations -- score normalized to 3
所用输入
bus_factor1
contributors_sampled1
top_contributor_share1

议题与 PR 响应能力

77良好
评分方式
42/42议题解决 — 100% 的议题已关闭
24.8/30PR 接受 — 已裁定的 PR 中 129/156 已合并
0/13Newcomer PR acceptance — 30 天内没有首次贡献者的 PR 得到裁决
0/15OpenSSF Scorecard：Code-Review — Found 0/2 approved changesets -- score normalized to 0
所用输入
merged_prs129
open_issues0
closed_issues4
prs_merged_7d8
prs_decided_7d9
prs_merged_30d46
prs_decided_30d47
issue_closed_ratio1
closed_unmerged_prs27
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
已排除计分（无数据或不适用）：Newcomer PR acceptance。 其余权重已重新归一化。

所有权与托管责任

26存在风险
评分方式
10/30所有权背书 — 个人（用户）账户
0/20已验证域名 — 不适用于个人账户
2.2/25所有者影响力 — datris 有 1 位关注者
8.4/25既往记录 — 9 个公开仓库，账户约 0 年
所用输入
followers1
owner_typeUser
is_verified—
owner_logindatris
public_repos9
account_age_days211
已排除计分（无数据或不适用）：已验证域名。 其余权重已重新归一化。

软件包维护

100卓越
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 0 天前
20/20版本历史 — 138 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
packagesdatris-mcp-server
ecosystemspypi
any_deprecated否
min_days_since_publish0

工程质量

基础的工程与文档实践是否到位？

81优秀 · 占总体的 19%

工程实践

68良好
评分方式
24/24CI 工作流 — 7 个工作流
24/24存在测试
0/16Linter 配置
0/9.6Pre-commit 钩子
0/6.4.editorconfig
20/20OpenSSF Scorecard：CI-Tests — 1 out of 1 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否
has_precommit_config否

文档

100卓越
评分方式
30/30README
25/25文档目录
15/15文档 / 主页站点 — https://datris.ai
10/10仓库描述
10/10主题标签 — 14 个主题标签
10/10Wiki
所用输入
topicsai-agents, claude, data-engineering, data-ingestion, data-pipeline, data-quality, etl, llm, mcp, mcp-server, model-context-protocol, rag, self-hosted, vector-database
has_wiki是
homepagehttps://datris.ai
docs_sitehttps://datris.ai
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？

73良好 · 占总体的 16%

安全态势

66良好
评分方式
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — 无数据
2.5/2.5CI-Tests — 1 out of 1 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/2 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5许可证 — license file detected
7.5/7.5Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
3.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — 无数据
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
3/7.5Vulnerabilities — 6 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.6
已排除计分（无数据或不适用）：Branch-Protection, Signed-Releases。 其余权重已重新归一化。

依赖安全公告

100卓越
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
0/25间接依赖不含已知公告 — 在此范围内，传递依赖集合无法与开发和测试依赖区分
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
sourceosv
advisories2
affected_packages2
assessed_packages1,322
unassessed_packages20
affected_by_severityhigh 2
direct_affected_packages0
已排除计分（无数据或不适用）：间接依赖不含已知公告, 没有长期未处理的公告。 其余权重已重新归一化。 已将 1322 个已解析依赖与 OSV 比对。 有 20 项无法评估——没有已解析的版本、生态系统不受支持，或超出所报告的软件包清单。 该仓库未发布任何索引可解析的软件包，因此改为评估仓库依赖图。该图将开发与测试版本固定同交付的依赖混在一起，因此仅对声明的运行时依赖计分；传递性发现仅作为背景信息列出，不计入评分。 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？权重刻意设小（4%）：代理工具链是一项真实的维护信号，但完全不具备的仓库仍可达到 100/100。

72良好 · 占总体的 4%

AI 代理上下文与指引

55中等
评分方式
0/45代理指令 — 没有 CLAUDE.md / AGENTS.md / 编辑器规则
15/15机器可读文档（llms.txt） — 项目网站提供 llms.txt（https://datris.ai/llms.txt）
40/40可读的提交历史 — 100 次人类提交中有 98 次说明了意图（结构化标题或解释性正文）
所用输入
has_llms_txt是
llms_txt_urlhttps://datris.ai/llms.txt
legible_history_share0.98
agent_instruction_files—
agent_instruction_max_bytes—

验证循环（构建 / 测试 / 类型检查）

65良好
评分方式
0/18一条命令的引导启动
22/22自动化测试
0/11Lint / 格式化配置
11/11静态类型检查 — ui/tsconfig.json
10/10可复现环境 — Dockerfile, lockfile
10/10已体现的代理实践 — 最近 100 次提交中有 92 次由代理编写或署名代理
5/8自动化维护 — 已配置依赖自动化，但在抽样提交中未观察到
7/10OpenSSF Scorecard：Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 7
所用输入
has_nix否
has_tests是
lockfilespackage-lock.json
has_dockerfile是
typed_language是
bootstrap_files—
has_devcontainer否
has_linter_config否
typecheck_configsui/tsconfig.json
agent_commit_share0.92
toolchain_manifests—
dependency_bot_commit_share0

面向模型的代码可读性

99卓越
评分方式
45/45可类型检查的代码 — Scala（静态类型）
53.6/55可控的文件大小 — 采样的 722 个源文件中有 19 个超过 60KB
所用输入
primary_languageScala
largest_source_bytes353,208
source_files_sampled722
oversized_source_files19

机器可读接口

100卓越
评分方式
40/40API 模式（OpenAPI/GraphQL/proto） — docs/openapi.yaml
20/20MCP 服务器
40/40可运行示例 — examples, recipes
所用输入
example_dirsexamples, recipes
has_mcp_signal是
api_schema_filesdocs/openapi.yaml
interfaces_expected_ofnetwork-service

关键数据

12GitHub 星标
1贡献者
1,125最近 12 个月提交数
0距最近推送天数
100发布版本数
1巴士系数（bus factor）
0开放议题
npm, PyPI软件包生态系统数

数据采集警告

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:datris-mcp-server@1.52.0; advisories assessed against the repository dependency graph instead

更多细节

OpenSSF Scorecard 6.6 / 10
6.6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）。Scorecard v5.5.0 · 2026-10-19 19:20 UTC

10Binary-Artifactsno binaries found in the repo
不适用Branch-Protectioninternal 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
10CI-Tests1 out of 1 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/2 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
7Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 7
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
不适用Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
4Vulnerabilities6 existing vulnerabilities detected
直接依赖 24
注册表软件包版本约束清单文件
PyPImcp>=1.28,<2mcp-server/pyproject.toml
PyPIrequests—mcp-server/pyproject.toml
PyPIurllib3>=2.8.0mcp-server/pyproject.toml
PyPIclick—mcp-server/pyproject.toml
PyPIhttpx—mcp-server/pyproject.toml
PyPIhttpx-sse—mcp-server/pyproject.toml
PyPIpython-dotenv—mcp-server/pyproject.toml
PyPIuvicorn—mcp-server/pyproject.toml
PyPIstarlette—mcp-server/pyproject.toml
npm@angular/animations21.2.24ui/package.json
npm@angular/cdk^21.2.14ui/package.json
npm@angular/common21.2.24ui/package.json
npm@angular/compiler21.2.24ui/package.json
npm@angular/core21.2.24ui/package.json
npm@angular/forms21.2.24ui/package.json
npm@angular/material^21.2.14ui/package.json
npm@angular/platform-browser21.2.24ui/package.json
npm@angular/platform-browser-dynamic21.2.24ui/package.json
npm@angular/router21.2.24ui/package.json
npmecharts^6.1.0ui/package.json
npmngx-echarts^21.0.0ui/package.json
npmrxjs~7.8.0ui/package.json
npmtslib^2.3.0ui/package.json
npmzone.js~0.16.2ui/package.json
全部依赖 1,342

来自 GitHub 依赖图的完整解析依赖集合：26 个直接依赖与 1,316 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
npm@angular/animations21.2.24直接
npm@angular/cdk21.2.14直接
npm@angular/common21.2.24直接
npm@angular/compiler21.2.24直接
npm@angular/core21.2.24直接
npm@angular/forms21.2.24直接
npm@angular/material21.2.14直接
npm@angular/platform-browser21.2.24直接
npm@angular/platform-browser-dynamic21.2.24直接
npm@angular/router21.2.24直接
npmecharts6.1.0直接
npmngx-echarts21.0.0直接
npmrxjs7.8.2直接
npmtslib1.14.1直接
npmtslib2.3.0直接
npmtslib2.8.1直接
npmzone.js0.16.3直接
PyPIclick—直接
PyPIhttpx—直接
PyPIhttpx-sse—直接
PyPImcp—直接
PyPIpython-dotenv—直接
PyPIrequests—直接
PyPIstarlette—直接
PyPIurllib3—直接
PyPIuvicorn—直接
Mavenat.yawk.lz4:lz4-java1.11.4间接
Mavench.qos.logback:logback-classic1.5.38间接
Mavench.qos.logback:logback-core1.5.38间接
Mavencom.amazonaws:aws-java-sdk-bundle1.12.262间接
Mavencom.azure:azure-core1.58.1间接
Mavencom.azure:azure-core-http-netty1.16.5间接
Mavencom.azure:azure-identity1.18.4间接
Mavencom.azure:azure-json1.5.1间接
Mavencom.azure:azure-xml1.2.1间接
Mavencom.carrotsearch.thirdparty:simple-xml-safe2.7.1间接
Mavencom.clearspring.analytics:stream2.9.6间接
Mavencom.databricks:databricks-jdbc3.4.1间接
Mavencom.esotericsoftware:kryo-shaded4.0.2间接
Mavencom.esotericsoftware:minlog1.3.0间接
Mavencom.fasterxml.jackson.core:jackson-annotations2.18.11间接
Mavencom.fasterxml.jackson.core:jackson-core2.18.11间接
Mavencom.fasterxml.jackson.core:jackson-databind2.18.11间接
Mavencom.fasterxml.jackson.datatype:jackson-datatype-jdk82.21.5间接
Mavencom.fasterxml.jackson.datatype:jackson-datatype-jsr3102.21.5间接
Mavencom.fasterxml.jackson.module:jackson-module-parameter-names2.21.5间接
Mavencom.fasterxml.jackson.module:jackson-module-scala_2.122.18.11间接
Mavencom.github.luben:zstd-jni1.5.6-4间接
Mavencom.github.stephenc.jcip:jcip-annotations1.0-1间接
Mavencom.github.virtuald:curvesapi1.08间接
Mavencom.google.android:annotations4.1.1.4间接
Mavencom.google.api.grpc:proto-google-common-protos2.59.2间接
Mavencom.google.code.findbugs:jsr3053.0.2间接
Mavencom.google.code.gson:gson2.13.1间接
Mavencom.google.crypto.tink:tink1.9.0间接
Mavencom.google.errorprone:error_prone_annotations2.38.0间接
Mavencom.google.flatbuffers:flatbuffers-java1.12.0间接
Mavencom.google.guava:failureaccess1.0.3间接
Mavencom.google.guava:guava33.4.8-jre间接
Mavencom.google.guava:listenablefuture9999.0-empty-to-avoid-conflict-with-guava间接
Mavencom.google.j2objc:j2objc-annotations3.0.0间接
Mavencom.google.protobuf:protobuf-java4.28.3间接
Mavencom.knuddels:jtokkit1.1.0间接
Mavencom.microsoft.azure:msal4j1.23.1间接
Mavencom.microsoft.azure:msal4j-persistence-extension1.3.0间接
Mavencom.mysql:mysql-connector-j8.4.0间接
Mavencom.nimbusds:content-type2.3间接
Mavencom.nimbusds:lang-tag1.7间接
Mavencom.nimbusds:nimbus-jose-jwt10.0.2间接
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Mavencom.ning:compress-lzf1.1.2间接
Mavencom.squareup.okhttp3:okhttp5.1.0间接
Mavencom.squareup.okhttp3:okhttp-jvm5.1.0间接
Mavencom.squareup.okio:okio3.15.0间接
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Mavencom.thoughtworks.paranamer:paranamer2.8间接
Mavencom.twitter:chill-java0.10.0间接
Mavencom.twitter:chill_2.120.10.0间接
Mavencom.univocity:univocity-parsers2.9.1间接
Mavencom.zaxxer:HikariCP5.1.0间接
Mavencom.zaxxer:SparseBitSet1.3间接
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Mavenio.dropwizard.metrics:metrics-jmx4.2.19间接
Mavenio.dropwizard.metrics:metrics-json4.2.19间接
Mavenio.dropwizard.metrics:metrics-jvm4.2.19间接
Mavenio.github.jopenlibs:vault-java-driver6.2.1间接
Mavenio.grpc:grpc-api1.75.0间接
Mavenio.grpc:grpc-context1.75.0间接
Mavenio.grpc:grpc-core1.75.0间接
Mavenio.grpc:grpc-netty-shaded1.75.0间接
Mavenio.grpc:grpc-protobuf1.75.0间接
Mavenio.grpc:grpc-protobuf-lite1.75.0间接
Mavenio.grpc:grpc-stub1.75.0间接
Mavenio.grpc:grpc-util1.75.0间接
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Mavenio.micrometer:micrometer-jakarta91.16.7间接
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PyPIpsycopg2-binary—间接
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PyPIstomp-py—间接
PyPIweaviate-client—间接
依赖安全公告 2

该仓库未发布可被索引解析的包，因此评估的是其自身的依赖图——共 1,322 个包，其中也包含从不交付的开发与测试版本固定：2 个存在已知公告，0 个为直接依赖。 有 20 个无法评估——没有已解析的版本、生态系统不受支持，或不在所列包清单之内。

软件包版本关系严重程度公告数修复版本
braces3.0.3间接高1—
webpack-dev-middleware7.4.5间接高18.3.0

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

反馈

发现这份报告有不准确之处，或有想法要分享？错误的测量、未识别的工具、建议、疑问——都欢迎提出。每条消息都会被阅读并得到回复。

登录过程中消息不会丢失。

相关记录

与 datris/datris-platform-oss 共享目录标签或生态系统的已检测仓库。 并排阅读 →

98Agenta-AI/agentaAgenta is a workspace where you and your team build agents and automations.卓越97langchain4j/langchain4jLangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.卓越100deepset-ai/haystackOpen-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.卓越98googleapis/mcp-toolboxMCP Toolbox for Databases is an open source MCP server for databases.卓越97datacontract/datacontract-cliEnforce Data Contracts卓越96agentscope-ai/QwenPawYour Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.卓越

评分是信号，而非担保。 评分反映的是 GitHub 上公开可见的实践——不是代码审计，也不是安全保证。

缺失数据将被剔除并重新归一化权重，绝不按零分计。方法论已版本化并公开：指标 v2.10.0、模式 v0.34.0—— 完整方法论 · 指标知识库.

单项结果在整体记录中的位置： 汇总统计 — PyPI.