公开记录卓越
软件健康报告模式 0.27.0 · 指标 2.5.0 · 2026-07-29 00:57 UTC
fastmachinelearning / hls4ml
Machine learning on FPGAs using HLS
fastmachinelearning/hls4ml 的健康指数为 100 分中的 93 分，处于「卓越」区间。 其得分最高的类别是Engineering Quality（95/100），最低的是AI Readiness（50/100）。 最近一次更新在今天。 近期的大部分工作由 3 位贡献者完成。
93
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，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。
93
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）
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 79 经校准后在公布的指数量表上为 93（记录校准 2026-08-02）。
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 | hls4ml | 1.3.0 | 3,335 | 16 | 130 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？
86
开发活跃度
89优秀
评分方式
| 36/36 | 推送新近度 — 最近一次推送于 0 天前 |
| 24.9/36 | 提交节奏 — 52 周中有 36 周有提交 |
| 18/18 | 提交量 — 最近一年 121 次提交 |
| 10/10 | OpenSSF Scorecard：Maintained — 18 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
所用输入
| commits_last_year | 121 |
| human_commit_share | 0.8 |
| days_since_last_push | 0 |
| active_weeks_last_year | 36 |
发布纪律
82优秀
评分方式
| 27/27 | 有发布版本 — 已发布 20 个发布版本 |
| 27/36 | 发布时效 — 最近一次发布版本于 130 天前 |
| 19.8/27 | 发布节奏 — 约每 119 天发布一次 |
| 0/10 | OpenSSF Scorecard：Signed-Releases — 无数据 |
所用输入
| releases_count | 20 |
| latest_release_tag | v1.3.0 |
| releases_from_tags | 否 |
| days_since_latest_release | 130 |
| mean_days_between_releases | 119 |
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？
76
流行度与采用
86优秀
评分方式
| 53.8/60 | 星标 — 2,081 个星标 |
| 23/25 | 复刻 — 572 个复刻 |
| 9.5/15 | 关注者 — 53 位关注者 |
所用输入
| forks | 572 |
| stars | 2,081 |
| watchers | 53 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
社区健康
77良好
评分方式
| 22.5/22.5 | README |
| 22.5/22.5 | 许可证 — 可识别的许可证（Apache-2.0） |
| 18/18 | CONTRIBUTING 指南 |
| 0/13.5 | 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 |
| readme_badges | — |
| has_contributing | 是 |
| has_issue_template | 否 |
| has_code_of_conduct | 否 |
| readme_badge_services | — |
| has_pull_request_template | 是 |
生态采用（下载量）
59中等
评分方式
| 47/80 | 月度下载量 — pypi 合计每月 3,335 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
| packages | hls4ml |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 3,335 |
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？
79
维护者韧性（巴士系数）
75良好
评分方式
| 36/54 | 巴士系数 — 3 位贡献者贡献了半数提交 |
| 15.5/22.5 | 提交分布 — 头号贡献者编写了 31% 的提交 |
| 13.5/13.5 | 贡献者广度 — 75 位贡献者 |
| 10/10 | OpenSSF Scorecard：Contributors — project has 45 contributing companies or organizations |
所用输入
| bus_factor | 3 |
| contributors_sampled | 75 |
| top_contributor_share | 0.309 |
议题与 PR 响应能力
75良好
评分方式
| 25/42 | 议题解决 — 60% 的议题已关闭 |
| 25.5/30 | PR 接受 — 已裁定的 PR 中 656/771 已合并 |
| 0/13 | Newcomer PR acceptance — 30 天内没有首次贡献者的 PR 得到裁决 |
| 15/15 | OpenSSF Scorecard：Code-Review — all changesets reviewed |
所用输入
| merged_prs | 656 |
| open_issues | 196 |
| closed_issues | 288 |
| prs_merged_7d | — |
| prs_decided_7d | — |
| prs_merged_30d | — |
| prs_decided_30d | — |
| issue_closed_ratio | 0.595 |
| closed_unmerged_prs | 115 |
| first_time_authors_30d | — |
| first_time_prs_merged_30d | — |
| first_time_prs_decided_30d | — |
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
72良好
评分方式
| 30/30 | 所有权背书 — 组织持有 |
| 0/20 | 已验证域名 |
| 17.5/25 | 所有者影响力 — fastmachinelearning 有 270 位关注者 |
| 25/25 | 既往记录 — 61 个公开仓库，账户约 8 年 |
所用输入
| followers | 270 |
| owner_type | Organization |
| is_verified | — |
| owner_login | fastmachinelearning |
| public_repos | 61 |
| account_age_days | 3,198 |
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 130 天前 |
| 20/20 | 版本历史 — 16 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 | hls4ml |
| ecosystems | pypi |
| any_deprecated | 否 |
| min_days_since_publish | 130 |
工程质量
基础的工程与文档实践是否到位？
95
工程实践
92优秀
评分方式
| 24/24 | CI 工作流 — 5 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 |
| 18/20 | OpenSSF Scorecard：CI-Tests — 25 out of 26 merged PRs checked by a CI test -- score normalized to 9 |
所用输入
| has_ci | 是 |
| has_tests | 是 |
| has_editorconfig | 否 |
| has_linter_config | 是 |
| has_precommit_config | 是 |
文档
100卓越
评分方式
| 30/30 | README |
| 25/25 | 文档目录 |
| 15/15 | 文档 / 主页站点 — https://fastmachinelearning.org/hls4ml |
| 10/10 | 仓库描述 |
| 10/10 | 主题标签 — 11 个主题标签 |
| 10/10 | Wiki |
所用输入
| topics | hls, machine-learning, fpga, python, keras, pytorch, onnx, vivado, vivado-hls, neural-network, intel-hls |
| has_wiki | 是 |
| homepage | https://fastmachinelearning.org/hls4ml |
| 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？
64
安全态势
55中等
评分方式
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — 无数据 |
| 2.2/2.5 | CI-Tests — 25 out of 26 merged PRs checked by a CI test -- score normalized to 9 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 7.5/7.5 | Code-Review — all changesets reviewed |
| 2.5/2.5 | Contributors — project has 45 contributing companies or organizations |
| 0/10 | Dangerous-Workflow — dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | 许可证 — license file detected |
| 7.5/7.5 | Maintained — 18 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — 无数据 |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
所用输入
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 5.5 |
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 |
| 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 | 5 |
| 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:hls4ml@1.3.0 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 5 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？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。
50
AI 代理上下文与指引
37薄弱
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） |
| 36.7/40 | 可读的提交历史 — 80 次人类提交中有 55 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 | 0.688 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
评分方式
| 18/18 | 一条命令的引导启动 — docs/Makefile, hls4ml/templates/quartus/Makefile |
| 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 |
| 0/10 | 已体现的代理实践 — 最近 100 次提交中没有代理编写的提交 |
| 8/8 | 自动化维护 — 最近 100 次提交中有 1 次为自动依赖更新 |
| 0/10 | OpenSSF Scorecard：Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
所用输入
| has_nix | 否 |
| has_tests | 是 |
| lockfiles | — |
| has_dockerfile | 否 |
| typed_language | 否 |
| bootstrap_files | docs/Makefile, hls4ml/templates/quartus/Makefile |
| has_devcontainer | 否 |
| has_linter_config | 是 |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0.01 |
面向模型的代码可读性
54中等
评分方式
| 0/45 | 可类型检查的代码 — Python，未配置类型检查 |
| 54.4/55 | 可控的文件大小 — 采样的 644 个源文件中有 7 个超过 60KB |
所用输入
| primary_language | Python |
| largest_source_bytes | 261,465 |
| source_files_sampled | 644 |
| oversized_source_files | 7 |
关键数据
2,081GitHub 星标
75贡献者
121最近 12 个月提交数
0距最近推送天数
20发布版本数
3巴士系数（bus factor）
196开放议题
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
更多细节
Star 与 Fork 历史 0 ★ / 572 ⇿
0Star
572Fork
20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。
主版本 1次版本 10修订 6
每个点涵盖 8 天。
OpenSSF Scorecard 5.5 / 10
5.5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 |
| 9 | CI-Tests | 25 out of 26 merged PRs checked by a CI test -- score normalized to 9 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 10 | Code-Review | all changesets reviewed |
| 10 | Contributors | project has 45 contributing companies or organizations |
| 0 | Dangerous-Workflow | dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 18 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| 不适用 | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 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 | h5py | — | pyproject.toml |
| PyPI | numpy | — | pyproject.toml |
| PyPI | pydigitalwavetools | ==1.1 | pyproject.toml |
| PyPI | pyyaml | — | pyproject.toml |
| PyPI | quantizers | — | pyproject.toml |
全部依赖 25
来自 GitHub 依赖图的完整解析依赖集合：5 个直接依赖与 20 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 | h5py | — | 直接 |
| PyPI | numpy | — | 直接 |
| PyPI | pydigitalwavetools | 1.1 | 直接 |
| PyPI | pyyaml | — | 直接 |
| PyPI | quantizers | — | 直接 |
| PyPI | da4ml | — | 间接 |
| PyPI | hgq | — | 间接 |
| PyPI | hgq2 | — | 间接 |
| PyPI | keras | 3.14.1 | 间接 |
| PyPI | keras-tuner | 1.1.3 | 间接 |
| PyPI | onnx | — | 间接 |
| PyPI | ortools | 9.4.1874 | 间接 |
| PyPI | pquant-ml | — | 间接 |
| PyPI | setuptools | — | 间接 |
| PyPI | setuptools-scm | — | 间接 |
| PyPI | sparsepixels | — | 间接 |
| PyPI | sphinx | — | 间接 |
| PyPI | sphinx-contributors | — | 间接 |
| PyPI | sphinx-github-changelog | — | 间接 |
| PyPI | sphinx-rtd-theme | — | 间接 |
| PyPI | sphinx-tabs | — | 间接 |
| PyPI | sympy | — | 间接 |
| PyPI | tensorflow | — | 间接 |
| PyPI | tensorflow-model-optimization | — | 间接 |
| PyPI | toposort | — | 间接 |
依赖安全公告 0
安装 pypi:hls4ml@1.3.0 会引入 5 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": [
"hls",
"machine-learning",
"fpga",
"python",
"keras",
"pytorch",
"onnx",
"vivado",
"vivado-hls",
"neural-network",
"intel-hls"
],
"is_fork": false,
"size_kb": 278631,
"has_wiki": true,
"homepage": "https://fastmachinelearning.org/hls4ml",
"languages": {
"C": 5730,
"C++": 2462305,
"Tcl": 72725,
"CMake": 16046,
"Shell": 33861,
"Python": 2718787,
"Verilog": 21471,
"Makefile": 798,
"SystemVerilog": 41743
},
"pushed_at": "2026-07-28T12:38:15Z",
"created_at": "2017-10-25T21:43:56Z",
"owner_type": "Organization",
"updated_at": "2026-07-28T17:17:39Z",
"description": "Machine learning on FPGAs using HLS",
"is_archived": false,
"is_disabled": false,
"license_spdx": "Apache-2.0",
"default_branch": "main",
"license_spdx_raw": "Apache-2.0",
"primary_language": "Python",
"significant_languages": [
"Python",
"C++"
]
},
"owner": {
"blog": "http://fastmachinelearning.org/",
"name": "Fast Machine Learning Lab",
"type": "Organization",
"login": "fastmachinelearning",
"company": null,
"location": null,
"followers": 270,
"avatar_url": "https://avatars.githubusercontent.com/u/33101568?v=4",
"created_at": "2017-10-25T18:35:07Z",
"is_verified": null,
"public_repos": 61,
"account_age_days": 3198
},
"license": {
"state": "standard",
"spdx_id": "Apache-2.0",
"raw_spdx": "Apache-2.0",
"file_present": true,
"scorecard_found": true,
"profile_has_license": true
},
"activity": {
"releases": [
{
"tag": "v1.3.0",
"kind": "minor",
"published_at": "2026-03-20T14:59:12Z"
},
{
"tag": "v1.2.0",
"kind": "minor",
"published_at": "2025-11-03T20:19:32Z"
},
{
"tag": "v1.1.0",
"kind": "minor",
"published_at": "2025-03-17T16:51:08Z"
},
{
"tag": "v1.0.0",
"kind": "major",
"published_at": "2024-12-09T22:47:29Z"
},
{
"tag": "v0.8.1",
"kind": "patch",
"published_at": "2023-12-19T21:00:03Z"
},
{
"tag": "v0.8.0",
"kind": "minor",
"published_at": "2023-11-16T00:10:25Z"
},
{
"tag": "v0.8.0rc1",
"kind": "other",
"published_at": "2023-11-08T00:09:05Z"
},
{
"tag": "v0.7.1",
"kind": "patch",
"published_at": "2023-05-13T15:55:52Z"
},
{
"tag": "v0.7.0",
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{
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"points": 23,
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"details": [
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}
],
"max_points": 25
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{
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},
{
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"note": null,
"notes": [],
"value": 77,
"inputs": {
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"has_license": true,
"readme_badges": null,
"has_contributing": true,
"has_issue_template": false,
"has_code_of_conduct": false,
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"status": "met",
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{
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"details": [
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{
"code": "license_spdx",
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{
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"points": 18,
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{
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"points": 0,
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{
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"components": [
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"ecosystems": "pypi"
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}
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"max_points": 80
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{
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"points": 0,
"status": "excluded",
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{
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{
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}
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{
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"points": 13.5,
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"details": [
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"code": "contributors_sampled",
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}
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{
"key": "openssf_scorecard_contributors",
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"details": [],
"max_points": 10
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]
},
{
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"notes": [
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{
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{
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{
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],
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},
{
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},
{
"key": "fuzzing",
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{
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{
"key": "maintained",
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},
{
"key": "packaging",
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{
"key": "pinned_dependencies",
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{
"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": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
"band": "exceptional",
"name": "Dependency advisories",
"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:hls4ml@1.3.0 runtime dependency closure — what installing the published package pulls in — 5 packages. Reachability is not analyzed.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"no_advisories_left_outstanding"
]
}
},
{
"code": "weights_renormalized",
"params": {}
},
{
"code": "advisories_scope_published",
"params": {
"package": "pypi:hls4ml@1.3.0",
"assessed": 5
}
},
{
"code": "advisories_reachability",
"params": {}
}
],
"value": 100,
"inputs": {
"source": "osv",
"advisories": 0,
"affected_packages": 0,
"assessed_packages": 5,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
"params": {}
}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
{
"code": "no_indirect_advisories",
"params": {}
}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
"name": "No advisories left outstanding",
"detail": "no advisory carries a publication date",
"points": 0,
"status": "excluded",
"details": [
{
"code": "advisories_no_publication_date",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "malicious_dependencies",
"band": "exceptional",
"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"source": "osv",
"meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
"packages": [],
"red_flag": false,
"assessed_packages": 5,
"malicious_packages": 0,
"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
{
"key": "no_dependency_reported_as_a_malicious_package",
"name": "No dependency reported as a malicious package",
"detail": "no dependency is reported as a malicious package",
"points": 100,
"status": "met",
"details": [
{
"code": "no_malicious_dependencies",
"params": {}
}
],
"max_points": 100
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "exceptional",
"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"
],
"commit_weight_rule": {
"min_commits": 50,
"min_commit_share": 0.1
},
"review_only_matches": 0,
"below_threshold_exposures": [],
"assessed_self_published_locations": 5
},
"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": 50,
"weight": 0.04,
"metrics": [
{
"key": "ai_agent_context",
"band": "weak",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 37,
"inputs": {
"has_llms_txt": false,
"legible_history_share": 0.688,
"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": "55 of 80 human commits state their intent (structured subject or explanatory body)",
"points": 36.7,
"status": "partial",
"details": [
{
"code": "legible_history",
"params": {
"legible": 55,
"sampled": 80
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "moderate",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 59,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [
"docs/Makefile",
"hls4ml/templates/quartus/Makefile"
],
"has_devcontainer": false,
"has_linter_config": true,
"typecheck_configs": [],
"agent_commit_share": 0,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0.01
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "docs/Makefile, hls4ml/templates/quartus/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "docs/Makefile, hls4ml/templates/quartus/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": null,
"points": 11,
"status": "met",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no agent-authored commits among the last 100",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_authored_commits",
"params": {
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "1 of the last 100 commits are automated dependency updates",
"points": 8,
"status": "met",
"details": [
{
"code": "dependency_bot_commits",
"params": {
"count": 1,
"sampled": 100
}
}
],
"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": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 54,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 261465,
"source_files_sampled": 644,
"oversized_source_files": 7
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "7/644 source files over 60KB",
"points": 54.4,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 644,
"oversized": 7
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
"classification": {
"top": [
"library"
],
"labels": [
"library"
],
"scores": {
"library": 6
},
"primary": "library",
"evidence": [
{
"tier": "distribution",
"label": "library",
"source": "registry:pypi",
"weight": 6
}
],
"artifacts": [],
"confidence": "medium",
"host_extension": false,
"runs_as_process": false,
"consumed_by_code": true
},
"metrics_version": "2.5.0"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
],
"report_type": "repository",
"generated_at": "2026-07-29T00:57:59.624569Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/f/fastmachinelearning/hls4ml.svg",
"full_name": "fastmachinelearning/hls4ml",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}