公开记录
软件健康报告模式 0.11.0 · 指标 1.13.0 · 2026-07-14 14:09 UTC

Project-AgML / AgML

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.

PythonApache-2.0★ 291 星标⑂ 45 复刻始于 2021年10月在 GitHub 上查看 ↗

Project-AgML/AgML 的健康指数为 100 分中的 67 分,处于「中等」区间。 其得分最高的类别是Engineering Quality(86/100),最低的是Security(37/100)。 最近一次更新在 3 天前。 近期的大部分工作由 1 位贡献者完成。

67
总分 / 100
中等

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。

67
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)
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。

所有权

AgML组织
49 关注者4 个公开仓库始于 2021年12月

该仓库由组织支持——共同承担、可问责的托管责任,可延续于任何单一维护者之后。

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
PyPIagml0.8.0-303 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?

73良好 · 占总体的 22%
评分方式
36/36推送新近度 — 最近一次推送于 3 天前
6.2/36提交节奏 — 52 周中有 9 周有提交
14/18提交量 — 最近一年 35 次提交
10/10OpenSSF Scorecard:Maintained — 22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
所用输入
commits_last_year35
human_commit_share
days_since_last_push3
active_weeks_last_year9

发布纪律

84良好
评分方式
27/27有发布版本 — 已发布 28 个发布版本
36/36发布时效 — 最近一次发布版本于 3 天前
12.6/27发布节奏 — 约每 121.3 天发布一次
0/10OpenSSF Scorecard:Signed-Releases — 无数据
所用输入
releases_count28
latest_release_tagv0.8.0
releases_from_tags
days_since_latest_release3
mean_days_between_releases121.3
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?

72良好 · 占总体的 18%
评分方式
39.9/60星标 — 291 个星标
13.7/25复刻 — 45 个复刻
6.4/15关注者 — 15 位关注者
所用输入
forks45
stars291
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

社区健康

85优秀
评分方式
22.5/22.5README
22.5/22.5许可证 — 可识别的许可证(Apache-2.0)
18/18CONTRIBUTING 指南
13.5/13.5行为准则
0/7.2议题模板
0/6.3PR 模板
所用输入
has_readme
has_license
has_contributing
has_issue_template
has_code_of_conduct
has_pull_request_template

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?

61中等 · 占总体的 24%
评分方式
9/54巴士系数 — 1 位贡献者贡献了半数提交
4.3/22.5提交分布 — 头号贡献者编写了 81% 的提交
13.5/13.5贡献者广度 — 15 位贡献者
6/10OpenSSF Scorecard:Contributors — project has 2 contributing companies or organizations -- score normalized to 6
所用输入
bus_factor1
contributors_sampled15
top_contributor_share0.81
评分方式
31.2/46.8议题解决 — 67% 的议题已关闭
36.8/38.3PR 接受 — 已裁定的 PR 中 51/53 已合并
0/15OpenSSF Scorecard:Code-Review — Found 0/7 approved changesets -- score normalized to 0
所用输入
merged_prs51
open_issues10
closed_issues20
issue_closed_ratio0.667
closed_unmerged_prs2
评分方式
30/30所有权背书 — 组织持有
0/20已验证域名
12.2/25所有者影响力 — Project-AgML 有 49 位关注者
14.2/25既往记录 — 4 个公开仓库,账户约 4 年
所用输入
followers49
owner_typeOrganization
is_verified
owner_loginProject-AgML
public_repos4
account_age_days1,656
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 3 天前
20/20版本历史 — 30 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
packagesagml
ecosystemspypi
any_deprecated
min_days_since_publish3

工程质量

基础的工程与文档实践是否到位?

86优秀 · 占总体的 20%

工程实践

84良好
评分方式
24/24CI 工作流 — 2 个工作流
24/24存在测试
16/16Linter 配置 — ruff.toml
0/9.6Pre-commit 钩子
0/6.4.editorconfig
20/20OpenSSF Scorecard:CI-Tests — 6 out of 6 merged PRs checked by a CI test -- score normalized to 10
所用输入
has_ci
has_tests
has_editorconfig
has_linter_config
has_precommit_config

文档

90优秀
评分方式
30/30README
25/25文档目录
15/15文档 / 主页站点 — https://project-agml.github.io
10/10仓库描述
10/10主题标签 — 9 个主题标签
0/10Wiki
所用输入
topicsagriculture, computer-vision, dataset, deep-learning, image-classification, object-detection, pytorch, semantic-segmentation, synthetic-data
has_wiki
homepagehttps://project-agml.github.io
has_readme
has_docs_dir
has_description

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?

37存在风险 · 占总体的 16%

安全态势

37存在风险
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 — 6 out of 6 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 0/7 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5许可证 — license file detected
7.5/7.5Maintained — 22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — 无数据
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — 无数据
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 22 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.7
已排除计分(无数据或不适用):branch_protection, packaging, signed_releases。 其余权重已重新归一化。

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。

54中等 · 占总体的 0%
评分方式
0/45代理指令 — 没有 CLAUDE.md / AGENTS.md / 编辑器规则
0/15机器可读文档(llms.txt)
0/40可读的提交历史 — 无数据
所用输入
has_llms_txt
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
已排除计分(无数据或不适用):可读的提交历史。 其余权重已重新归一化。
评分方式
18/18一条命令的引导启动 — Makefile
22/22自动化测试
11/11Lint / 格式化配置 — ruff.toml
11/11静态类型检查 — config/mypy.ini
10/10可复现环境 — lockfile
0/10已体现的代理实践 — 无数据
0/8自动化维护 — 无数据
0/10OpenSSF Scorecard:Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
所用输入
has_nix
has_tests
lockfilesuv.lock
has_dockerfile
typed_language
bootstrap_filesMakefile
has_devcontainer
has_linter_config
typecheck_configsconfig/mypy.ini
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
已排除计分(无数据或不适用):已体现的代理实践, 自动化维护。 其余权重已重新归一化。
评分方式
27/45可类型检查的代码 — Python,已配置类型检查(config/mypy.ini)
53.7/55可控的文件大小 — 采样的 125 个源文件中有 3 个超过 60KB
所用输入
primary_languagePython
largest_source_bytes86,964
source_files_sampled125
oversized_source_files3

机器可读接口

40存在风险
评分方式
0/40API 模式(OpenAPI/GraphQL/proto)
0/20MCP 服务器
40/40可运行示例 — examples, notebooks
所用输入
example_dirsexamples, notebooks
has_mcp_signal
api_schema_files

关键数据

291GitHub 星标
15贡献者
35最近 12 个月提交数
3距最近推送天数
28发布版本数
1巴士系数(bus factor)
10开放议题
PyPI软件包生态系统数

更多细节

OpenSSF Scorecard 3.7 / 10
3.7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 · 2026-07-14 14:08 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-Tests6 out of 6 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 0/7 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
不适用Packagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
不适用Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities22 existing vulnerabilities detected
直接依赖 11
注册表软件包版本约束清单文件
PyPImatplotlib>=3.7.5pyproject.toml
PyPInumpy>=1.24.4pyproject.toml
PyPIopencv-python>=4.10.0.84pyproject.toml
PyPIopencv-python-headless>=4.10.0.84pyproject.toml
PyPIrequests>=2.0.0pyproject.toml
PyPItqdm>=4.67.0pyproject.toml
PyPIpyyaml>=6.0.2pyproject.toml
PyPIalbumentations>=1.4.18pyproject.toml
PyPIdict2xml>=1.7.6pyproject.toml
PyPIrich>=14.0.0pyproject.toml
PyPIdatasetspyproject.toml
全部依赖 90

来自 GitHub 依赖图的完整解析依赖集合:11 个直接依赖与 79 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
PyPIalbumentations2.0.5直接
PyPIdatasets5.0.0直接
PyPIdict2xml1.7.6直接
PyPImatplotlib3.10.1直接
PyPInumpy2.2.4直接
PyPIopencv-python4.11.0.86直接
PyPIopencv-python-headless4.11.0.86直接
PyPIpyyaml6.0.2直接
PyPIrequests2.32.3直接
PyPIrich14.0.0直接
PyPItqdm4.67.1直接
PyPIagml0.8.0间接
PyPIaiohappyeyeballs2.7.1间接
PyPIaiohttp3.14.1间接
PyPIaiosignal1.4.0间接
PyPIalbucore0.0.23间接
PyPIannotated-types0.7.0间接
PyPIanyio4.14.1间接
PyPIasync-timeout5.0.1间接
PyPIattrs25.3.0间接
PyPIboto31.37.31间接
PyPIbotocore1.37.31间接
PyPIcertifi2025.1.31间接
PyPIcharset-normalizer3.4.1间接
PyPIclick8.4.2间接
PyPIcolorama0.4.6间接
PyPIcontourpy1.3.1间接
PyPIcoverage7.8.0间接
PyPIcycler0.12.1间接
PyPIdill0.4.1间接
PyPIexceptiongroup1.2.2间接
PyPIfilelock3.29.7间接
PyPIfonttools4.57.0间接
PyPIfrozenlist1.8.0间接
PyPIfsspec2026.4.0间接
PyPIh110.16.0间接
PyPIhf-xet1.5.1间接
PyPIhttpcore1.0.9间接
PyPIhttpx0.28.1间接
PyPIhuggingface-hub1.23.0间接
PyPIidna3.10间接
PyPIimageio2.37.0间接
PyPIiniconfig2.1.0间接
PyPIinterrogate1.7.0间接
PyPIjmespath1.0.1间接
PyPIjoblib1.4.2间接
PyPIkiwisolver1.4.8间接
PyPIlazy-loader0.4间接
PyPImarkdown-it-py3.0.0间接
PyPImdurl0.1.2间接
PyPImultidict6.7.1间接
PyPImultiprocess0.70.19间接
PyPImypy1.15.0间接
PyPImypy-extensions1.0.0间接
PyPInetworkx3.4.2间接
PyPIpackaging24.2间接
PyPIpandas2.2.3间接
PyPIpillow11.1.0间接
PyPIpluggy1.5.0间接
PyPIpropcache0.5.2间接
PyPIpy1.11.0间接
PyPIpyarrow25.0.0间接
PyPIpydantic2.11.3间接
PyPIpydantic-core2.33.1间接
PyPIpygments2.19.1间接
PyPIpyparsing3.2.3间接
PyPIpytest8.3.5间接
PyPIpytest-cov6.1.1间接
PyPIpytest-order1.3.0间接
PyPIpython-dateutil2.9.0.post0间接
PyPIpytz2025.2间接
PyPIruff0.11.5间接
PyPIs3transfer0.11.4间接
PyPIscikit-image0.25.2间接
PyPIscikit-learn1.6.1间接
PyPIscipy1.15.2间接
PyPIshapely2.1.0间接
PyPIsimsimd6.2.1间接
PyPIsix1.17.0间接
PyPIstringzilla3.12.3间接
PyPItabulate0.9.0间接
PyPIthreadpoolctl3.6.0间接
PyPItifffile2025.3.30间接
PyPItomli2.2.1间接
PyPItyping-extensions4.13.2间接
PyPItyping-inspection0.4.0间接
PyPItzdata2025.2间接
PyPIurllib32.4.0间接
PyPIxxhash3.8.1间接
PyPIyarl1.24.2间接
原始 JSON 报告 机器可读
{
  "data": {
    "repo": {
      "topics": [
        "agriculture",
        "computer-vision",
        "dataset",
        "deep-learning",
        "image-classification",
        "object-detection",
        "pytorch",
        "semantic-segmentation",
        "synthetic-data"
      ],
      "is_fork": false,
      "size_kb": 223579,
      "has_wiki": false,
      "homepage": "https://project-agml.github.io",
      "languages": {
        "C++": 15282,
        "CMake": 3680,
        "Shell": 2872,
        "Python": 1239893,
        "Makefile": 636
      },
      "pushed_at": "2026-07-10T21:44:44Z",
      "created_at": "2021-10-29T13:44:40Z",
      "owner_type": "Organization",
      "updated_at": "2026-07-13T05:40:56Z",
      "description": "AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.",
      "is_archived": false,
      "is_disabled": false,
      "license_spdx": "Apache-2.0",
      "default_branch": "main",
      "primary_language": "Python",
      "significant_languages": [
        "Python"
      ]
    },
    "owner": {
      "blog": null,
      "name": "AgML",
      "type": "Organization",
      "login": "Project-AgML",
      "company": null,
      "followers": 49,
      "avatar_url": "https://avatars.githubusercontent.com/u/96885544?v=4",
      "created_at": "2021-12-30T18:16:31Z",
      "is_verified": null,
      "public_repos": 4,
      "account_age_days": 1656
    },
    "activity": {
      "releases_count": 28,
      "commits_last_year": 35,
      "latest_release_at": "2026-07-10T21:44:44Z",
      "latest_release_tag": "v0.8.0",
      "days_since_last_push": 3,
      "active_weeks_last_year": 9,
      "days_since_latest_release": 3,
      "mean_days_between_releases": 121.3
    },
    "community": {
      "has_readme": true,
      "has_license": true,
      "has_description": true,
      "has_contributing": true,
      "health_percentage": 62,
      "has_issue_template": false,
      "has_code_of_conduct": true,
      "has_pull_request_template": false
    },
    "ecosystem": {
      "packages": [
        {
          "name": "agml",
          "exists": true,
          "license": "Apache-2.0",
          "ecosystem": "pypi",
          "matches_repo": null,
          "registry_url": "https://pypi.org/project/agml/",
          "is_deprecated": false,
          "latest_version": "0.8.0",
          "repository_url": null,
          "versions_count": 30,
          "total_downloads": null,
          "dependents_count": null,
          "deprecation_note": null,
          "maintainers_count": null,
          "monthly_downloads": null,
          "first_published_at": "2021-10-29T19:00:48.123127Z",
          "latest_published_at": "2026-07-10T21:27:25.722835Z",
          "latest_version_yanked": null,
          "days_since_latest_publish": 3
        }
      ]
    },
    "popularity": {
      "forks": 45,
      "stars": 291,
      "watchers": 15,
      "open_issues_and_prs": 13
    },
    "ai_readiness": {
      "has_nix": false,
      "example_dirs": [
        "examples",
        "notebooks"
      ],
      "has_llms_txt": false,
      "has_dockerfile": false,
      "has_mcp_signal": false,
      "bootstrap_files": [
        "Makefile"
      ],
      "api_schema_files": [],
      "has_devcontainer": false,
      "typecheck_configs": [
        "config/mypy.ini"
      ],
      "largest_source_bytes": 86964,
      "source_files_sampled": 125,
      "oversized_source_files": 3,
      "agent_instruction_files": [],
      "agent_instruction_max_bytes": null
    },
    "dependencies": {
      "manifests": [
        "pyproject.toml"
      ],
      "ecosystems": [
        "pypi"
      ],
      "dependencies": [
        {
          "name": "matplotlib",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=3.7.5"
        },
        {
          "name": "numpy",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=1.24.4"
        },
        {
          "name": "opencv-python",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=4.10.0.84"
        },
        {
          "name": "opencv-python-headless",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=4.10.0.84"
        },
        {
          "name": "requests",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=2.0.0"
        },
        {
          "name": "tqdm",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=4.67.0"
        },
        {
          "name": "pyyaml",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=6.0.2"
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                "detail": "project has 2 contributing companies or organizations -- score normalized to 6",
                "points": 1.5,
                "status": "partial",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "no update tool detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow not detected",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "22 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 4
            },
            "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",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 54,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "legible_commit_history"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "excellent",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice",
                    "automated_maintenance"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 88,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "uv.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "config/mypy.ini"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "Makefile"
                    }
                  }
                ],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": "ruff.toml",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "ruff.toml"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "config/mypy.ini",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "config/mypy.ini"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "lockfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 81,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 86964,
              "source_files_sampled": 125,
              "oversized_source_files": 3
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (config/mypy.ini)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "config/mypy.ini",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "3/125 source files over 60KB",
                "points": 53.7,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 125,
                      "oversized": 3
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples",
                "notebooks"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples, notebooks",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples, notebooks"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-14T14:09:16.743236Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/Project-AgML/AgML.svg",
  "full_name": "Project-AgML/AgML",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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 v1.13.0、模式 v0.11.0—— 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.