公开记录
软件健康报告模式 0.9.0 · 指标 1.13.0 · 2026-07-13 00:53 UTC

Significant-Gravitas / AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

Python · TypeScript自定义许可证★ 185,497 星标⑂ 46,106 复刻始于 2023年3月在 GitHub 上查看 ↗

Significant-Gravitas/AutoGPT 的健康指数为 100 分中的 86 分,处于「优秀」区间。 其得分最高的类别是Vitality(100/100),最低的是Security(58/100)。 最近一次更新在 1 天前。 近期的大部分工作由 5 位贡献者完成。

86
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。

86
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

AutoGPT组织
4,455 关注者28 个公开仓库始于 2023年4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。

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?

100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 1 天前
36/36提交节奏 — 52 周中有 52 周有提交
18/18提交量 — 最近一年 1,841 次提交
10/10OpenSSF Scorecard:Maintained — 30 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 10
所用输入
commits_last_year1,841
human_commit_share
days_since_last_push1
active_weeks_last_year52

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 4 天前
27/27发布节奏 — 约每 8.6 天发布一次
0/10OpenSSF Scorecard:Signed-Releases — 无数据
所用输入
releases_count100
latest_release_tagautogpt-platform-beta-v0.6.66
releases_from_tags
days_since_latest_release4
mean_days_between_releases8.6
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?

93优秀 · 占总体的 18%
评分方式
60/60星标 — 185,497 个星标
25/25复刻 — 46,106 个复刻
15/15关注者 — 1,547 位关注者
所用输入
forks46,106
stars185,497
watchers1,547
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

社区健康

86优秀
评分方式
22.5/22.5README
16.9/22.5许可证 — 存在许可证文件,但不是可识别的许可证
18/18CONTRIBUTING 指南
13.5/13.5行为准则
0/7.2议题模板
6.3/6.3PR 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?

80良好 · 占总体的 24%
评分方式
45.9/54巴士系数 — 5 位贡献者贡献了半数提交
19.4/22.5提交分布 — 头号贡献者编写了 14% 的提交
13.5/13.5贡献者广度 — 100 位贡献者
10/10OpenSSF Scorecard:Contributors — project has 18 contributing companies or organizations
所用输入
bus_factor5
contributors_sampled100
top_contributor_share0.137
评分方式
43.3/46.8议题解决 — 93% 的议题已关闭
21.7/38.3PR 接受 — 已裁定的 PR 中 4,608/8,126 已合并
12/15OpenSSF Scorecard:Code-Review — Found 25/30 approved changesets -- score normalized to 8
所用输入
merged_prs4,608
open_issues285
closed_issues3,606
issue_closed_ratio0.927
closed_unmerged_prs3,518
评分方式
30/30所有权背书 — 组织持有
0/20已验证域名
25/25所有者影响力 — Significant-Gravitas 有 4,455 位关注者
17.1/25既往记录 — 28 个公开仓库,账户约 3 年
所用输入
followers4,455
owner_typeOrganization
is_verified
owner_loginSignificant-Gravitas
public_repos28
account_age_days1,185

工程质量

基础的工程与文档实践是否到位?

96优秀 · 占总体的 20%

工程实践

94优秀
评分方式
24/24CI 工作流 — 33 个工作流
24/24存在测试
16/16Linter 配置 — .eslintrc.json, .flake8
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

100优秀
评分方式
30/30README
25/25文档目录
15/15文档 / 主页站点 — https://agpt.co
10/10仓库描述
10/10主题标签 — 11 个主题标签
10/10Wiki
所用输入
topicsagentic-ai, agents, ai, artificial-intelligence, autonomous-agents, claude, gpt, llama-api, llm, openai, python
has_wiki
homepagehttps://agpt.co
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?

58中等 · 占总体的 16%

安全态势

58中等
评分方式
7.5/7.5Binary-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all 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
6/7.5Code-Review — Found 25/30 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 18 contributing companies or organizations
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5许可证 — license file detected
7.5/7.5Maintained — 30 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — 无数据
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 233 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.8
已排除计分(无数据或不适用):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。

75良好 · 占总体的 0%
评分方式
45/45代理指令 — .claude/skills/vercel-react-best-practices/AGENTS.md, .github/copilot-instructions.md, AGENTS.md, CLAUDE.md, autogpt_platform/AGENTS.md, autogpt_platform/CLAUDE.md, autogpt_platform/backend/AGENTS.md, autogpt_platform/backend/CLAUDE.md, autogpt_platform/backend/backend/copilot/bot/AGENTS.md, autogpt_platform/backend/backend/copilot/bot/CLAUDE.md, autogpt_platform/backend/backend/copilot/graphiti/AGENTS.md, autogpt_platform/backend/backend/copilot/graphiti/CLAUDE.md, autogpt_platform/frontend/AGENTS.md, autogpt_platform/frontend/CLAUDE.md, autogpt_platform/frontend/src/tests/AGENTS.md, autogpt_platform/frontend/src/tests/CLAUDE.md, classic/CLAUDE.md, classic/direct_benchmark/CLAUDE.md, classic/forge/CLAUDE.md, classic/original_autogpt/CLAUDE.md, docs/AGENTS.md, docs/CLAUDE.md, docs/content/forge/components/agents.md, docs/platform/gemini.md
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.claude/skills/vercel-react-best-practices/AGENTS.md, .github/copilot-instructions.md, AGENTS.md, CLAUDE.md, autogpt_platform/AGENTS.md, autogpt_platform/CLAUDE.md, autogpt_platform/backend/AGENTS.md, autogpt_platform/backend/CLAUDE.md, autogpt_platform/backend/backend/copilot/bot/AGENTS.md, autogpt_platform/backend/backend/copilot/bot/CLAUDE.md, autogpt_platform/backend/backend/copilot/graphiti/AGENTS.md, autogpt_platform/backend/backend/copilot/graphiti/CLAUDE.md, autogpt_platform/frontend/AGENTS.md, autogpt_platform/frontend/CLAUDE.md, autogpt_platform/frontend/src/tests/AGENTS.md, autogpt_platform/frontend/src/tests/CLAUDE.md, classic/CLAUDE.md, classic/direct_benchmark/CLAUDE.md, classic/forge/CLAUDE.md, classic/original_autogpt/CLAUDE.md, docs/AGENTS.md, docs/CLAUDE.md, docs/content/forge/components/agents.md, docs/platform/gemini.md
agent_instruction_max_bytes60,535
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 — autogpt_platform/Makefile
22/22自动化测试
11/11Lint / 格式化配置 — .eslintrc.json, .flake8
11/11静态类型检查 — autogpt_platform/backend/pyrightconfig.json, autogpt_platform/frontend/tsconfig.json
10/10可复现环境 — devcontainer, Dockerfile, 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
0/10OpenSSF Scorecard:Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
所用输入
has_nix
has_tests
lockfilespnpm-lock.yaml, poetry.lock
has_dockerfile
typed_language
bootstrap_filesautogpt_platform/Makefile
has_devcontainer
has_linter_config
typecheck_configsautogpt_platform/backend/pyrightconfig.json, autogpt_platform/frontend/tsconfig.json
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
27/45可类型检查的代码 — Python,已配置类型检查(autogpt_platform/backend/pyrightconfig.json, autogpt_platform/frontend/tsconfig.json)
54.3/55可控的文件大小 — 采样的 3,223 个源文件中有 42 个超过 60KB
所用输入
primary_languagePython
largest_source_bytes253,703
source_files_sampled3,223
oversized_source_files42

机器可读接口

40存在风险
评分方式
40/40API 模式(OpenAPI/GraphQL/proto) — autogpt_platform/frontend/src/app/api/openapi.json
0/20MCP 服务器
0/40可运行示例
所用输入
example_dirs
has_mcp_signal
api_schema_filesautogpt_platform/frontend/src/app/api/openapi.json

关键数据

185,497GitHub 星标
100贡献者
1,841最近 12 个月提交数
1距最近推送天数
100发布版本数
5巴士系数(bus factor)
285开放议题
PyPI软件包生态系统数

数据采集警告

  • Could not fetch pypi package 'autogpt-classic' from its registry

更多细节

OpenSSF Scorecard 5.8 / 10
5.8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 · 2026-07-13 00:53 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all 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
8Code-ReviewFound 25/30 approved changesets -- score normalized to 8
10Contributorsproject has 18 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
不适用Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities233 existing vulnerabilities detected
直接依赖 50
注册表软件包版本约束清单文件
PyPIaiohttp^3.8.5classic/pyproject.toml
PyPIbeautifulsoup4^4.12.2classic/pyproject.toml
PyPIrequests*classic/pyproject.toml
PyPItrafilatura^2.0classic/pyproject.toml
PyPIanthropic^0.45.0classic/pyproject.toml
PyPIgroq^0.8.0classic/pyproject.toml
PyPIlitellm>=1.17.9,<1.82.7classic/pyproject.toml
PyPIopenai^1.50.0classic/pyproject.toml
PyPItiktoken>=0.7.0,<1.0.0classic/pyproject.toml
PyPIfastapi^0.109.1classic/pyproject.toml
PyPIhypercorn^0.14.4classic/pyproject.toml
PyPIuvicorn>=0.23.2,<1classic/pyproject.toml
PyPIpython-multipart^0.0.7classic/pyproject.toml
PyPIcharset-normalizer^3.1.0classic/pyproject.toml
PyPIdemjson3^3.0.0classic/pyproject.toml
PyPIjsonschema*classic/pyproject.toml
PyPIorjson^3.8.10classic/pyproject.toml
PyPIpydantic^2.7.2classic/pyproject.toml
PyPIpyyaml^6.0classic/pyproject.toml
PyPItoml^0.10.2classic/pyproject.toml
PyPIboto3^1.33.6classic/pyproject.toml
PyPIchromadb^1.4.0classic/pyproject.toml
PyPIgoogle-cloud-logging^3.8.0classic/pyproject.toml
PyPIgoogle-cloud-storage^2.13.0classic/pyproject.toml
PyPIsqlalchemy^2.0.19classic/pyproject.toml
PyPIclick^8.0classic/pyproject.toml
PyPIcolorama^0.4.6classic/pyproject.toml
PyPIprompt-toolkit^3.0.0classic/pyproject.toml
PyPIrich^13.0classic/pyproject.toml
PyPIpypdf^3.1.0classic/pyproject.toml
PyPIpython-docx*classic/pyproject.toml
PyPIpylatexenc*classic/pyproject.toml
PyPIPillow*classic/pyproject.toml
PyPIen-core-web-smclassic/pyproject.toml
PyPIspacy^3.8.0classic/pyproject.toml
PyPIddgs^9.9classic/pyproject.toml
PyPIgoogle-api-python-client^2.116classic/pyproject.toml
PyPIplaywright^1.50.0classic/pyproject.toml
PyPIdistro^1.8.0classic/pyproject.toml
PyPIdocker*classic/pyproject.toml
PyPIgitpython^3.1.32classic/pyproject.toml
PyPIgTTS^2.3.1classic/pyproject.toml
PyPIjinja2^3.1.2classic/pyproject.toml
PyPInumpy>=2.0.0classic/pyproject.toml
PyPIplaysound~1.2.2classic/pyproject.toml
PyPIpython-dotenv^1.0.0classic/pyproject.toml
PyPIsentry-sdk^1.40.4classic/pyproject.toml
PyPItenacity^8.2.2classic/pyproject.toml
PyPIwatchdog^6.0.0classic/pyproject.toml
PyPIpytest^8.0classic/pyproject.toml
原始 JSON 报告 机器可读
{
  "data": {
    "repo": {
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        "agentic-ai",
        "agents",
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        "Batchfile": 14868,
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      "created_at": "2023-03-16T09:21:07Z",
      "owner_type": "Organization",
      "updated_at": "2026-07-13T00:14:45Z",
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      "active_weeks_last_year": 52,
      "days_since_latest_release": 4,
      "mean_days_between_releases": 8.6
    },
    "community": {
      "has_readme": true,
      "has_license": true,
      "has_description": true,
      "has_contributing": true,
      "health_percentage": 100,
      "has_issue_template": false,
      "has_code_of_conduct": true,
      "has_pull_request_template": true
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    "ecosystem": {
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    "popularity": {
      "forks": 46106,
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    "ai_readiness": {
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      "example_dirs": [],
      "has_llms_txt": false,
      "has_dockerfile": true,
      "has_mcp_signal": false,
      "bootstrap_files": [
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      "api_schema_files": [
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      "has_devcontainer": true,
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        "CLAUDE.md",
        "autogpt_platform/AGENTS.md",
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        "autogpt_platform/backend/CLAUDE.md",
        "autogpt_platform/backend/backend/copilot/bot/AGENTS.md",
        "autogpt_platform/backend/backend/copilot/bot/CLAUDE.md",
        "autogpt_platform/backend/backend/copilot/graphiti/AGENTS.md",
        "autogpt_platform/backend/backend/copilot/graphiti/CLAUDE.md",
        "autogpt_platform/frontend/AGENTS.md",
        "autogpt_platform/frontend/CLAUDE.md",
        "autogpt_platform/frontend/src/tests/AGENTS.md",
        "autogpt_platform/frontend/src/tests/CLAUDE.md",
        "classic/CLAUDE.md",
        "classic/direct_benchmark/CLAUDE.md",
        "classic/forge/CLAUDE.md",
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                "key": "openssf_scorecard_signed_releases",
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        ],
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      {
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            "key": "popularity",
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                "key": "openssf_scorecard_contributors",
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          {
            "key": "responsiveness",
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                "key": "issue_resolution",
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                "key": "pr_acceptance",
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              {
                "key": "openssf_scorecard_code_review",
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          {
            "key": "stewardship",
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              "followers": 4455,
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                "key": "ownership_backing",
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                "key": "verified_domain",
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                "key": "owner_reach",
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                "key": "track_record",
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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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            "key": "engineering_practices",
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                "key": "ci_workflows",
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                "detail": "33 workflow(s)",
                "points": 24,
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              {
                "key": "linter_config",
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                "key": "pre_commit_hooks",
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              {
                "key": "editorconfig",
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                "key": "openssf_scorecard_ci_tests",
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                "key": "documentation_directory",
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                "key": "documentation_homepage_site",
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        ],
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            "value": 58,
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                "key": "branch_protection",
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                "key": "contributors",
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                "key": "dangerous_workflow",
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              {
                "key": "dependency_update_tool",
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              {
                "key": "fuzzing",
                "name": "Fuzzing",
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                "key": "license",
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                "key": "maintained",
                "name": "Maintained",
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                "key": "packaging",
                "name": "Packaging",
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                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
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              {
                "key": "sast",
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              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
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                "status": "met",
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              {
                "key": "signed_releases",
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                "max_points": 7.5
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                "key": "token_permissions",
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                "points": 0,
                "status": "missed",
                "details": [],
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              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "233 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
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            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
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                "code": "jurisdiction_evidence_limits",
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            "value": 100,
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            "components": [
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                "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?"
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        "key": "ai_readiness",
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        "name": "AI Readiness",
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        "weight": 0,
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            "key": "ai_agent_context",
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                "code": "weights_renormalized",
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            ],
            "value": 75,
            "inputs": {
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                "AGENTS.md",
                "CLAUDE.md",
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                "autogpt_platform/backend/backend/copilot/graphiti/CLAUDE.md",
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                "autogpt_platform/frontend/CLAUDE.md",
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                "classic/direct_benchmark/CLAUDE.md",
                "classic/forge/CLAUDE.md",
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                "points": 0,
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        ],
        "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": [
    "Could not fetch pypi package 'autogpt-classic' from its registry"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-13T00:53:51.414725Z",
  "schema_version": "0.9.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/s/Significant-Gravitas/AutoGPT.svg",
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  "license_state": "custom",
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}

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 v0.9.0—— 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.