公开记录
软件健康报告模式 0.16.0 · 指标 1.13.0 · 2026-07-21 01:14 UTC

stanfordnlp / dspy

DSPy: The framework for programming—not prompting—language models

PythonMIT★ 36,262 星标⑂ 3,117 复刻始于 2023年1月在 GitHub 上查看 ↗

stanfordnlp/dspy 的健康指数为 100 分中的 87 分,处于「优秀」区间。 其得分最高的类别是Vitality(99/100),最低的是AI Readiness(42/100)。 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。

87
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;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。

87
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

2,683 关注者55 个公开仓库始于 2012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
PyPIdspy3.2.1-10676 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?

99优秀 · 占总体的 22%
评分方式
36/36推送新近度 — 最近一次推送于 0 天前
35.3/36提交节奏 — 52 周中有 51 周有提交
18/18提交量 — 最近一年 490 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_year490
human_commit_share
days_since_last_push0
active_weeks_last_year51

发布纪律

100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 54 天前
27/27发布节奏 — 约每 24.2 天发布一次
0/10OpenSSF Scorecard:Signed-Releases — 无数据
所用输入
releases_count100
latest_release_tag3.3.0b1
releases_from_tags
days_since_latest_release54
mean_days_between_releases24.2
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?

85优秀 · 占总体的 18%
评分方式
60/60星标 — 36,262 个星标
25/25复刻 — 3,117 个复刻
12.8/15关注者 — 202 位关注者
所用输入
forks3,117
stars36,262
watchers202
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(MIT)
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
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?

82良好 · 占总体的 24%
评分方式
43.2/54巴士系数 — 4 位贡献者贡献了半数提交
16.1/22.5提交分布 — 头号贡献者编写了 28% 的提交
13.5/13.5贡献者广度 — 100 位贡献者
10/10OpenSSF Scorecard:Contributors — project has 22 contributing companies or organizations
所用输入
bus_factor4
contributors_sampled100
top_contributor_share0.285
评分方式
38/46.8议题解决 — 81% 的议题已关闭
27/38.3PR 接受 — 已裁定的 PR 中 1,649/2,337 已合并
4.5/15OpenSSF Scorecard:Code-Review — Found 10/26 approved changesets -- score normalized to 3
所用输入
merged_prs1,649
open_issues307
closed_issues1,331
issue_closed_ratio0.813
closed_unmerged_prs688
评分方式
30/30所有权背书 — 组织持有
0/20已验证域名
24.7/25所有者影响力 — stanfordnlp 有 2,683 位关注者
24.7/25既往记录 — 55 个公开仓库,账户约 13 年
所用输入
followers2,683
owner_typeOrganization
is_verified
owner_loginstanfordnlp
public_repos55
account_age_days4,966
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 76 天前
20/20版本历史 — 106 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
packagesdspy
ecosystemspypi
any_deprecated
min_days_since_publish76

工程质量

基础的工程与文档实践是否到位?

92优秀 · 占总体的 20%

工程实践

94优秀
评分方式
24/24CI 工作流 — 5 个工作流
24/24存在测试
16/16Linter 配置
9.6/9.6Pre-commit 钩子
0/6.4.editorconfig
20/20OpenSSF Scorecard:CI-Tests — 30 out of 30 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://dspy.ai
10/10仓库描述
0/10主题标签
10/10Wiki
所用输入
topics
has_wiki
homepagehttps://dspy.ai
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?

73良好 · 占总体的 16%

安全态势

69中等
评分方式
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 30 out of 30 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
2.2/7.5Code-Review — Found 10/26 approved changesets -- score normalized to 3
2.5/2.5Contributors — project has 22 contributing companies or organizations
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
4.5/5SAST — SAST tool is not run on all commits -- score normalized to 9
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — 无数据
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
0/7.5Vulnerabilities — 147 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.9
已排除计分(无数据或不适用):signed_releases。 其余权重已重新归一化。
评分方式
26.6/35直接依赖不含已知公告 — 1 个受影响:diskcache 5.6.3 (moderate)
25/25间接依赖不含已知公告 — 没有间接依赖携带已知公告
37.2/40没有长期未处理的公告 — 1 个携带公告的软件包超过 90 天未处理;最早一条发布于 159 天前
所用输入
sourceosv
advisories2
affected_packages1
assessed_packages59
unassessed_packages0
affected_by_severitymoderate 1
direct_affected_packages1
比对的是 pypi:dspy@3.2.1 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 59 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。

42存在风险 · 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
0/18一条命令的引导启动
22/22自动化测试
11/11Lint / 格式化配置
0/11静态类型检查
10/10可复现环境 — lockfile
0/10已体现的代理实践 — 无数据
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
has_tests
lockfilesPipfile.lock, uv.lock
has_dockerfile
typed_language
bootstrap_files
has_devcontainer
has_linter_config
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
已排除计分(无数据或不适用):已体现的代理实践。 其余权重已重新归一化。
评分方式
0/45可类型检查的代码 — Python,未配置类型检查
53.5/55可控的文件大小 — 采样的 261 个源文件中有 7 个超过 60KB
所用输入
primary_languagePython
largest_source_bytes114,651
source_files_sampled261
oversized_source_files7
评分方式
0/40API 模式(OpenAPI/GraphQL/proto)
20/20MCP 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

36,262GitHub 星标
100贡献者
490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)
307开放议题
PyPI软件包生态系统数

更多细节

OpenSSF Scorecard 6.9 / 10
6.9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 · 2026-07-21 01:14 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 10/26 approved changesets -- score normalized to 3
10Contributorsproject has 22 contributing companies or organizations
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
9SASTSAST tool is not run on all commits -- score normalized to 9
10Security-Policysecurity policy file detected
不适用Signed-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
0Vulnerabilities147 existing vulnerabilities detected
直接依赖 14
注册表软件包版本约束清单文件
PyPIopenai>=1.66.2pyproject.toml
PyPIregex>=2023.10.3pyproject.toml
PyPIorjson>=3.9.0pyproject.toml
PyPItqdm>=4.66.1pyproject.toml
PyPIrequests>=2.31.0pyproject.toml
PyPIpydantic>=2.0pyproject.toml
PyPIlitellm>=1.65.8pyproject.toml
PyPIdiskcache>=5.6.0pyproject.toml
PyPIjson-repair>=0.54.2pyproject.toml
PyPItenacity>=8.2.3pyproject.toml
PyPIanyiopyproject.toml
PyPIcachetools>=5.5.0pyproject.toml
PyPIcloudpickle>=3.1.2pyproject.toml
PyPIgepa==0.1.1pyproject.toml
全部依赖 293

来自 GitHub 依赖图的完整解析依赖集合:26 个直接依赖与 267 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
PyPIanyio4.13.0直接
PyPIanyio4.9.0直接
PyPIcachetools5.5.2直接
PyPIcachetools7.1.1直接
PyPIcloudpickle3.1.1直接
PyPIcloudpickle3.1.2直接
PyPIdiskcache5.6.3直接
PyPIgepa0.1.1直接
PyPIjson-repair0.40.0直接
PyPIjson-repair0.54.2直接
PyPIlitellm1.63.7直接
PyPIlitellm1.68.0直接
PyPIlitellm1.72.6直接
PyPIopenai1.61.0直接
PyPIopenai1.75.0直接
PyPIopenai1.88.0直接
PyPIorjson3.11.8直接
PyPIpydantic2.10.6直接
PyPIpydantic2.12.4直接
PyPIregex2024.11.6直接
PyPIregex2026.5.9直接
PyPIrequests2.33.1直接
PyPItenacity9.0.0直接
PyPItenacity9.1.4直接
PyPItqdm4.67.1直接
PyPItqdm4.67.3直接
PyPIaiohappyeyeballs2.6.1间接
PyPIaiohttp3.11.14间接
PyPIaiohttp3.13.2间接
PyPIaiosignal1.3.2间接
PyPIaiosignal1.4.0间接
PyPIalembic1.15.1间接
PyPIalembic1.16.2间接
PyPIannotated-types0.7.0间接
PyPIanthropic0.102.0间接
PyPIapscheduler3.11.0间接
PyPIargcomplete3.6.2间接
PyPIasttokens3.0.1间接
PyPIasync-timeout5.0.1间接
PyPIasyncer0.0.8间接
PyPIattrs25.3.0间接
PyPIattrs26.1.0间接
PyPIauthlib1.6.12间接
PyPIauthlib1.7.2间接
PyPIbabel2.18.0间接
PyPIbackoff2.2.1间接
PyPIbackports-asyncio-runner1.2.0间接
PyPIbackrefs7.0间接
PyPIbeautifulsoup44.14.3间接
PyPIblack25.1.0间接
PyPIbleach6.3.0间接
PyPIboto31.34.34间接
PyPIbotocore1.34.162间接
PyPIbuild1.2.2.post1间接
PyPIcairocffi1.7.1间接
PyPIcairosvg2.9.0间接
PyPIcertifi2025.6.15间接
PyPIcertifi2026.4.22间接
PyPIcffi1.17.1间接
PyPIcffi2.0.0间接
PyPIcfgv3.4.0间接
PyPIcharset-normalizer3.4.2间接
PyPIcharset-normalizer3.4.7间接
PyPIclick8.2.1间接
PyPIclick8.3.3间接
PyPIcolorama0.4.6间接
PyPIcolorlog6.9.0间接
PyPIcomm0.2.3间接
PyPIcryptography43.0.3间接
PyPIcryptography45.0.4间接
PyPIcssselect20.9.0间接
PyPIdatamodel-code-generator0.56.1间接
PyPIdatasets3.4.1间接
PyPIdatasets3.6.0间接
PyPIdebugpy1.8.20间接
PyPIdecorator5.2.1间接
PyPIdefusedxml0.7.1间接
PyPIdill0.3.8间接
PyPIdistlib0.3.9间接
PyPIdistro1.9.0间接
PyPIdnspython2.7.0间接
PyPIdocstring-parser0.17.0间接
PyPIdspy间接
PyPIdspy3.2.1间接
PyPIemail-validator2.2.0间接
PyPIexceptiongroup1.3.0间接
PyPIexecuting2.2.1间接
PyPIfastapi0.115.13间接
PyPIfastapi-sso0.16.0间接
PyPIfastjsonschema2.21.2间接
PyPIfilelock3.18.0间接
PyPIfrozenlist1.5.0间接
PyPIfrozenlist1.7.0间接
PyPIfsspec2024.12.0间接
PyPIfsspec2025.3.0间接
PyPIgenson1.3.0间接
PyPIghp-import2.1.0间接
PyPIgreenlet3.1.1间接
PyPIgreenlet3.2.3间接
PyPIgriffe1.6.2间接
PyPIgriffelib2.0.2间接
PyPIgrpcio1.73.0间接
PyPIgunicorn23.0.0间接
PyPIh110.14.0间接
PyPIh110.16.0间接
PyPIhf-xet1.1.4间接
PyPIhttpcore1.0.7间接
PyPIhttpcore1.0.9间接
PyPIhttpx0.27.0间接
PyPIhttpx0.28.1间接
PyPIhttpx-sse0.4.0间接
PyPIhuggingface-hub0.29.3间接
PyPIhuggingface-hub0.33.0间接
PyPIidentify2.6.12间接
PyPIidna3.10间接
PyPIidna3.13间接
PyPIimportlib-metadata8.6.1间接
PyPIimportlib-metadata8.7.0间接
PyPIinflect7.5.0间接
PyPIiniconfig2.1.0间接
PyPIipykernel7.2.0间接
PyPIipython9.13.0间接
PyPIipython-pygments-lexers1.1.1间接
PyPIisort6.0.1间接
PyPIjedi0.19.2间接
PyPIjinja23.1.6间接
PyPIjiter0.10.0间接
PyPIjiter0.9.0间接
PyPIjmespath1.0.1间接
PyPIjoblib1.4.2间接
PyPIjoserfc1.6.5间接
PyPIjsonpatch1.33间接
PyPIjsonpointer3.0.0间接
PyPIjsonschema4.23.0间接
PyPIjsonschema4.24.0间接
PyPIjsonschema-specifications2025.4.1间接
PyPIjsonschema-specifications2025.9.1间接
PyPIjupyter-client8.8.0间接
PyPIjupyter-core5.9.1间接
PyPIjupyterlab-pygments0.3.0间接
PyPIjupytext1.19.1间接
PyPIlangchain-core1.0.4间接
PyPIlangsmith0.4.42间接
PyPIlitellm-proxy-extras0.1.15间接
PyPImagicattr0.1.6间接
PyPImako1.3.10间接
PyPImako1.3.9间接
PyPImarkdown3.10.2间接
PyPImarkdown-it-py4.0.0间接
PyPImarkupsafe3.0.2间接
PyPImarkupsafe3.0.3间接
PyPImatplotlib-inline0.2.1间接
PyPImcp1.5.0间接
PyPImcp1.9.4间接
PyPImdit-py-plugins0.5.0间接
PyPImdurl0.1.2间接
PyPImergedeep1.3.4间接
PyPImistune3.2.1间接
PyPImkdocs1.6.1间接
PyPImkdocs-autorefs1.4.4间接
PyPImkdocs-get-deps0.2.2间接
PyPImkdocs-jupyter间接
PyPImkdocs-jupyter0.26.3间接
PyPImkdocs-llmstxt间接
PyPImkdocs-material间接
PyPImkdocs-material9.7.6间接
PyPImkdocs-material-extensions1.3.1间接
PyPImkdocs-redirects间接
PyPImkdocs-redirects1.2.3间接
PyPImkdocstrings间接
PyPImkdocstrings1.0.4间接
PyPImkdocstrings-python间接
PyPImkdocstrings-python2.0.3间接
PyPImore-itertools10.7.0间接
PyPImultidict6.2.0间接
PyPImultidict6.5.0间接
PyPImultiprocess0.70.16间接
PyPImypy-extensions1.1.0间接
PyPInbclient0.10.4间接
PyPInbconvert7.17.1间接
PyPInbformat5.10.4间接
PyPInest-asyncio1.6.0间接
PyPInodeenv1.9.1间接
PyPInumpy2.2.4间接
PyPInumpy2.2.6间接
PyPInumpy2.3.4间接
PyPIoauthlib3.3.0间接
PyPIoptuna4.2.1间接
PyPIoptuna4.8.0间接
PyPIpackaging24.2间接
PyPIpackaging26.2间接
PyPIpaginate0.5.7间接
PyPIpandas2.2.3间接
PyPIpandas2.3.3间接
PyPIpandocfilters1.5.1间接
PyPIparso0.8.6间接
PyPIpathspec0.12.1间接
PyPIpathspec1.1.1间接
PyPIpexpect4.9.0间接
PyPIpillow12.0.0间接
PyPIpillow12.2.0间接
PyPIplatformdirs4.3.8间接
PyPIplatformdirs4.9.6间接
PyPIpluggy1.6.0间接
PyPIpre-commit4.6.0间接
PyPIprompt-toolkit3.0.52间接
PyPIpropcache0.3.0间接
PyPIpropcache0.3.2间接
PyPIproperdocs1.6.7间接
PyPIprotobuf6.31.1间接
PyPIpsutil7.2.2间接
PyPIptyprocess0.7.0间接
PyPIpure-eval0.2.3间接
PyPIpyarrow19.0.1间接
PyPIpyarrow22.0.0间接
PyPIpycparser2.22间接
PyPIpycparser3.0间接
PyPIpydantic-core2.27.2间接
PyPIpydantic-core2.41.5间接
PyPIpydantic-settings2.9.1间接
PyPIpygments2.19.1间接
PyPIpygments2.20.0间接
PyPIpyjwt2.10.1间接
PyPIpymdown-extensions10.21.3间接
PyPIpynacl1.5.0间接
PyPIpyproject-hooks1.2.0间接
PyPIpytest8.4.2间接
PyPIpytest-asyncio1.3.0间接
PyPIpytest-mock3.14.1间接
PyPIpython-dateutil2.9.0.post0间接
PyPIpython-dotenv1.0.1间接
PyPIpython-dotenv1.1.0间接
PyPIpython-multipart0.0.18间接
PyPIpython-multipart0.0.20间接
PyPIpytz2025.1间接
PyPIpytz2025.2间接
PyPIpyyaml6.0.2间接
PyPIpyyaml6.0.3间接
PyPIpyyaml-env-tag1.1间接
PyPIpyzmq27.1.0间接
PyPIredis6.2.0间接
PyPIreferencing0.36.2间接
PyPIreferencing0.37.0间接
PyPIrequests-toolbelt1.0.0间接
PyPIrich13.9.4间接
PyPIrpds-py0.25.1间接
PyPIrpds-py0.30.0间接
PyPIrq2.4.0间接
PyPIruff0.15.10间接
PyPIs3transfer0.10.4间接
PyPIsetuptools间接
PyPIsix1.17.0间接
PyPIsniffio1.3.1间接
PyPIsoupsieve2.8.3间接
PyPIsqlalchemy2.0.39间接
PyPIsqlalchemy2.0.41间接
PyPIsse-starlette2.3.6间接
PyPIstack-data0.6.3间接
PyPIstarlette0.46.2间接
PyPIstarlette0.47.0间接
PyPItiktoken0.12.0间接
PyPItiktoken0.9.0间接
PyPItinycss21.4.0间接
PyPItokenizers0.21.1间接
PyPItomli2.2.1间接
PyPItornado6.5.5间接
PyPItraitlets5.14.3间接
PyPItypeguard4.5.1间接
PyPItyping-extensions4.15.0间接
PyPItyping-inspection0.4.2间接
PyPItzdata2025.2间接
PyPItzlocal5.3.1间接
PyPIujson5.10.0间接
PyPIurllib32.4.0间接
PyPIurllib32.6.3间接
PyPIuvicorn0.29.0间接
PyPIuvicorn0.34.3间接
PyPIuvloop0.21.0间接
PyPIvalidators0.35.0间接
PyPIvirtualenv20.31.2间接
PyPIwatchdog6.0.0间接
PyPIwcwidth0.6.0间接
PyPIweaviate-client4.21.0间接
PyPIwebencodings0.5.1间接
PyPIwebsockets13.1间接
PyPIwheel间接
PyPIxxhash3.5.0间接
PyPIxxhash3.6.0间接
PyPIyarl1.18.3间接
PyPIyarl1.20.1间接
PyPIzipp3.21.0间接
PyPIzipp3.23.0间接
PyPIzstandard0.25.0间接
依赖安全公告 1

安装 pypi:dspy@3.2.1 会引入 59 个包(直接与传递):其中 1 个存在已知公告,1 个为直接依赖。

软件包版本关系严重程度公告数修复版本
diskcache5.6.3直接2

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
{
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      "owner_type": "Organization",
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            "cvss_score": null,
            "advisory_ids": [
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        ],
        "collected": true,
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        "advisory_count": 2,
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        "unassessed_count": 0,
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                "key": "pr_acceptance",
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            "notes": [],
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                "key": "verified_domain",
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              {
                "key": "owner_reach",
                "name": "Owner reach",
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                "key": "track_record",
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                      "count": 55
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                "max_points": 25
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            "key": "package_maintenance",
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                "key": "publish_recency",
                "name": "Publish recency",
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                "key": "version_history",
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                "points": 20,
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                    "code": "published_versions",
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                      "count": 106
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                "key": "not_deprecated",
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                "points": 20,
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                "max_points": 20
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        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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      {
        "key": "engineering",
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        "name": "Engineering Quality",
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        "metrics": [
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            "key": "engineering_practices",
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                "key": "ci_workflows",
                "name": "CI workflows",
                "detail": "5 workflow(s)",
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                    "code": "ci_workflows",
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                      "count": 5
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                "max_points": 24
              },
              {
                "key": "tests_present",
                "name": "Tests present",
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              {
                "key": "linter_config",
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              },
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                "key": "pre_commit_hooks",
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                "key": "openssf_scorecard_ci_tests",
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              },
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                "key": "dependency_update_tool",
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                "key": "fuzzing",
                "name": "Fuzzing",
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                "key": "maintained",
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                "max_points": 7.5
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                "key": "token_permissions",
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                "key": "vulnerabilities",
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                "status": "missed",
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                ],
                "max_points": 35
              },
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                "max_points": 25
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              {
                "key": "no_advisories_left_outstanding",
                "name": "No advisories left outstanding",
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                "status": "partial",
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                      "oldest": 159
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                  }
                ],
                "max_points": 40
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            ]
          },
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            "key": "malicious_dependencies",
            "band": "excellent",
            "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": 59,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
            },
            "components": [
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                "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": [
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                    "code": "no_malicious_dependencies",
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                ],
                "max_points": 100
              }
            ]
          },
          {
            "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,
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              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 9
            },
            "components": [
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                "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
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            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "at_risk",
        "name": "AI Readiness",
        "value": 42,
        "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": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 61,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "Pipfile.lock",
                "uv.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "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": "lockfile",
                "points": 10,
                "status": "met",
                "details": [
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                    "code": "file_list",
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                    }
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                ],
                "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": "dependency automation configured, none observed in the sampled commits",
                "points": 5,
                "status": "partial",
                "details": [
                  {
                    "code": "dependency_bot_config_only",
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                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
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                "points": 7,
                "status": "partial",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 54,
            "inputs": {
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              "largest_source_bytes": 114651,
              "source_files_sampled": 261,
              "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": "7/261 source files over 60KB",
                "points": 53.5,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
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                      "sampled": 261,
                      "oversized": 7
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "moderate",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 60,
            "inputs": {
              "example_dirs": [
                "examples",
                "notebooks"
              ],
              "has_mcp_signal": true,
              "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": 20,
                "status": "met",
                "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": "2026-07-21T01:14:44.545005Z",
  "schema_version": "0.16.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/s/stanfordnlp/dspy.svg",
  "full_name": "stanfordnlp/dspy",
  "license_state": "standard",
  "license_spdx": "MIT"
}

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 v0.16.0—— 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.