Logfire Instrumentation
basicmachines-co/basic-memory
Adds Pydantic Logfire tracing, logging and metrics to Python, JavaScript or TypeScript and Rust projects, with the correct setup order and library extras.
对任意项目进行全面的成熟度评估扫描。当用户说"检查项目成熟度"、"项目评估"、 "maturity assessment"、"代码质量扫描"、"项目健康度"、"项目体检"、 "scan project maturity"、"项目有多成熟"时触发。适用场景：接手新项目前的摸底、 发布前的质量审查、技术尽调、团队内部代码健康度盘点。
Install Project Maturity
$ npx skills add KonghaYao/peri --skill project-maturity -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install KonghaYao/peri project-maturity --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/KonghaYao/peri.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/project-maturity .claude/skills/project-maturity && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "project-maturity" agent skill from https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturity into .claude/skills/project-maturity/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "project-maturity", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturityType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add KonghaYao/peri --skill project-maturity -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install KonghaYao/peri project-maturity --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/KonghaYao/peri.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/project-maturity .agents/skills/project-maturity && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "project-maturity" agent skill from https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturity into .agents/skills/project-maturity/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "project-maturity", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add KonghaYao/peri --skill project-maturity -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install KonghaYao/peri project-maturity --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/KonghaYao/peri.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/project-maturity .cursor/skills/project-maturity && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "project-maturity" agent skill from https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturity into .cursor/skills/project-maturity/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "project-maturity", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/KonghaYao/peri.git --path .claude/skills/project-maturity--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add KonghaYao/peri --skill project-maturity -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install KonghaYao/peri project-maturity --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/KonghaYao/peri.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/project-maturity .gemini/skills/project-maturity && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "project-maturity" agent skill from https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturity into .gemini/skills/project-maturity/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "project-maturity", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install KonghaYao/peri project-maturityInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add KonghaYao/peri --skill project-maturity -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/KonghaYao/peri.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/project-maturity .github/skills/project-maturity && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "project-maturity" agent skill from https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturity into .github/skills/project-maturity/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "project-maturity", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add KonghaYao/peri --skill project-maturity -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install KonghaYao/peri project-maturity --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/KonghaYao/peri.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/project-maturity .opencode/skills/project-maturity && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "project-maturity" agent skill from https://github.com/KonghaYao/peri/tree/main/.claude/skills/project-maturity into .opencode/skills/project-maturity/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "project-maturity", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
project-maturity- GitHub stars
- 223
- Token cost
- ~1.8k tokens
- SKILL.md length
- 399 words
- Files
- 6 (incl. references)
- Skills in repo
- 19
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
对任意项目进行全面的成熟度评估扫描。当用户说"检查项目成熟度"、"项目评估"、 "maturity assessment"、"代码质量扫描"、"项目健康度"、"项目体检"、 "scan project maturity"、"项目有多成熟"时触发。适用场景：接手新项目前的摸底、 发布前的质量审查、技术尽调、团队内部代码健康度盘点。
- Works in 4 steps: 语言检测与 Reference 加载 → 并行收集 8 维度数据 → 综合评分 → …
- DevOps & Cloud work in your project
- SKILL.md covers 工作流概览, Step 1: 语言检测与 Reference 加载, Step 2: 并行收集 8 维度数据 and Step 3: 综合评分, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Project Maturity is an agent skill from KonghaYao/peri. 对任意项目进行全面的成熟度评估扫描。当用户说"检查项目成熟度"、"项目评估"、 "maturity assessment"、"代码质量扫描"、"项目健康度"、"项目体检"、 "scan project maturity"、"项目有多成熟"时触发。适用场景：接手新项目前的摸底、 发布前的质量审查、技术尽调、团队内部代码健康度盘点。
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/generic.md`, `references/go.md` and `references/python.md`).
It sits in DevOps & Cloud. It works with TypeScript, Rust and Python. The repository describes itself as: Lightweight Rust Agent only use 50MB RAM, but Claude Code Plugin compatible, Dynamic Workflow, Goal, Artifacts, Free Web Search, full feature and better support! The licence is Apache-2.0.
When your agent uses it
- DevOps & Cloud work in your project
Example prompts
- “检查项目成熟度”
- “maturity assessment”
- “代码质量扫描”
- “/project-maturity”
Requirements
- Python 3
- Docker
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit d7ee444. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Project Maturity loads about 1.8k tokens when it runs, and up to ~6.9k if it reads all its reference files. Until then it costs about 46 tokens; SKILL.md has 399 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:192
- .env 已 gitignored → 合格
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from KonghaYao/peri at commit d7ee444, republished under its Apache-2.0 licence (© KonghaYao). 399 words, ~1,764 tokens.
Download SKILL.mdSave it as
.claude/skills/project-maturity/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- project-maturity
- description
- 对任意项目进行全面的成熟度评估扫描。当用户说"检查项目成熟度"、"项目评估"、 "maturity assessment"、"代码质量扫描"、"项目健康度"、"项目体检"、 "scan project maturity"、"项目有多成熟"时触发。适用场景：接手新项目前的摸底、 发布前的质量审查、技术尽调、团队内部代码健康度盘点。
Project Maturity Scanner
对任意项目进行 8 维度深度成熟度扫描，产出结构化 Markdown 报告。
工作流概览
语言检测 → 加载 Reference → 并行收集 8 维度数据 → 综合评分 → 输出报告三个核心原则：
- 用数据说话，不做主观猜测 — 每个评分背后都有可复现的命令和数据
- 先收集后评分 — 禁止在信息不全时下结论
- 风险优先 — 高风险项放在报告最前面，方便读者优先关注
Step 1: 语言检测与 Reference 加载
1.1 自动检测
扫描项目根目录，按优先级判断主语言：
| 信号 | 判定 |
|---|---|
Cargo.toml | Rust |
package.json + tsconfig.json | TypeScript |
package.json（无 tsconfig） | JavaScript/Node |
go.mod | Go |
pyproject.toml / setup.py / requirements.txt | Python |
pom.xml / build.gradle | Java/Kotlin |
Gemfile | Ruby |
CMakeLists.txt | C/C++ |
| 以上皆无 | Generic（通用检查） |
多语言项目：按代码量占比识别主语言和次语言，报告中对每种语言分别评估。
1.2 加载语言 Reference
根据检测结果，读对应 reference 文件获取语言特定的检查命令和指标：
references/rust.md— Rust 项目references/typescript.md— TypeScript/JavaScript 项目references/python.md— Python 项目references/go.md— Go 项目references/generic.md— 通用回退
Reference 文件包含的内容：
- 该语言的代码统计命令
- 测试框架识别与运行命令
- 静态分析/lint 工具
- 依赖审计工具
- 语言特定的成熟度阈值
Step 2: 并行收集 8 维度数据
关键：所有收集操作必须并行执行。不要串行逐个询问。
维度 1：项目规模
用语言 reference 提供的命令统计：
✅ 源代码行数（排除依赖/target/node_modules/build）
✅ 源文件数量
✅ 模块/包/crate 数量
✅ 各模块代码分布（最大的 5 个模块）
✅ 按语言拆分的代码量（多语言项目）评价标准：
- 小型 < 5,000 行 | 中型 5k-50k | 大型 50k-200k | 超大型 > 200k
- 模块化程度 = 模块数量是否与代码规模匹配
维度 2：开发活跃度
✅ 总提交数 + 首次/最后提交日期
✅ 近 30 天提交趋势（每日统计）
✅ 贡献者数量 + Top 3 贡献者占比（识别总线因子）
✅ 活跃分支数 + 标签数
✅ 版本标签命名规范度
✅ 合并提交比例（反映协作模式）评价标准：
- 近 30 天日均提交 > 3 → 极度活跃 | 1-3 → 健康 | 0.1-1 → 维护模式 | < 0.1 → 停滞
- 单人贡献占比 > 90% → 总线风险高
- 无版本标签 → 发布不规范
维度 3：测试覆盖
分两层检查：单元测试 + 集成/E2E 测试。
✅ #[test] / it() / def test_* 等测试函数数量
✅ 测试目录结构（tests/ 或 __tests__/ 等）
✅ 运行完整测试套件，统计通过/失败/跳过
✅ 各子模块的测试代码行数 vs 源代码行数
✅ 是否有 E2E/集成测试及框架
✅ 是否有覆盖率工具配置（tarpaulin/istanbul/coverage.py 等）
✅ CI 中是否跑测试评价标准（通用）：
- 测试/源代码比 > 50% → 优秀 | 20-50% → 良好 | 5-20% → 不足 | < 5% → 严重不足
- 核心模块零测试 → 直接标红
- CI 不跑测试 → 扣一档
注意：不同语言/框架的测试文化不同。Rust 项目 5% 测试比可能已经不错（大量类型系统保证），但 JS/Python 项目 5% 是严重不足。具体阈值见各语言 reference。
维度 4：代码质量
✅ 静态分析结果（clippy/eslint/pylint 等）
✅ 构建是否通过（build/compile）
✅ 格式化检查（fmt/format/check）
✅ unsafe/危险模式计数（如 Rust unsafe、Python eval/exec、JS eval）
✅ 错误处理模式（unwrap/panic 计数 vs expect/Result 处理）
✅ TODO/FIXME/HACK/XXX 残留数量
✅ pre-commit hooks 配置（lefthook/husky/pre-commit）评价标准：
- Lint 0 warning → 优秀 | < 10 → 良好 | 10-50 → 需关注 | > 50 → 差
- 构建不通过 → 严重问题
- unwrap 密度 > 30 处/千行 → 错误处理薄弱
- 有 pre-commit → +1 分
维度 5：CI/CD 与 DevOps
✅ CI pipeline 文件（.github/workflows / .gitlab-ci.yml / Jenkinsfile 等）
✅ CI 覆盖的操作系统数
✅ CI 步骤完整性：build / test / lint / audit / bench
✅ 发布流程（release workflow / publish script / Docker）
✅ 多平台/多架构构建支持
✅ 容器化（Dockerfile / docker-compose）
✅ 安装/部署脚本
✅ 版本管理自动化程度评价标准：
- CI 覆盖 3 OS + test + lint + audit → 优秀
- CI 只 build → 基础
- 无 CI → 严重不足
- 有自动化 release + Docker → +1 分
维度 6：文档
✅ README 质量（行数、是否有架构图、快速上手）
✅ CHANGELOG 是否存在及更新频率
✅ 设计文档/架构文档数量
✅ API 文档生成配置（rustdoc/jsdoc/sphinx 等）
✅ 贡献指南（CONTRIBUTING.md）
✅ 开发规范文档（CLAUDE.md / DEVELOPER.md）
✅ License 文件评价标准：
- README > 100 行 + 架构图 → 优秀
- CHANGELOG 维护到最新版 → 良好
- 无 License → 法律风险
- 有 AI 开发规范（CLAUDE.md/AGENTS.md）→ 现代项目加分
维度 7：安全
✅ 依赖审计工具运行结果（cargo audit / npm audit / pip audit / govulncheck）
✅ unsafe 代码块 + 是否有安全注释
✅ 密钥/凭证硬编码检查（.env 文件是否在 .gitignore）
✅ 已知漏洞扫描
✅ 是否有安全策略文档（SECURITY.md）评价标准：
- 0 已知漏洞 → 安全 | 有高危漏洞 → 严重
- .env 已 gitignored → 合格
- 有 SECURITY.md → +1 分
Show full SKILL.md (160 more words)Show less
维度 8：外部集成与生态
✅ 监控/可观测性（tracing/logging/metrics）
✅ 第三方服务集成（数据库、消息队列、API 网关等）
✅ 插件/扩展系统
✅ i18n 国际化
✅ 多环境配置管理
✅ 外部工具链集成评价标准：
- 有结构化日志 → 合格
- 有 tracing/metrics → 优秀
- 有插件系统 → 架构成熟度高
Step 3: 综合评分
3.1 评分方法
每个维度给出 1-5 星评分：
| 星级 | 含义 | 典型特征 |
|---|---|---|
| ★★★★★ | 行业领先 | 所有子项均达到最佳实践 |
| ★★★★☆ | 良好 | 大部分子项达标，有改进空间 |
| ★★★☆☆ | 基本合格 | 核心功能具备，但存在明显短板 |
| ★★☆☆☆ | 不足 | 多个子项缺失，影响项目健康 |
| ★☆☆☆☆ | 严重不足 | 关键维度存在重大缺陷 |
3.2 综合评分计算
综合分 = 各维度加权平均：
| 维度 | 权重 | 理由 |
|---|---|---|
| 测试覆盖 | 20% | 决定代码变更信心 |
| 代码质量 | 20% | 影响维护成本 |
| CI/CD | 15% | 影响交付效率 |
| 文档 | 15% | 影响新人上手 |
| 安全 | 15% | 影响生产可用性 |
| 项目规模 | 5% | 不是越大越好 |
| 活跃度 | 5% | 反映项目生命周期 |
| 外部集成 | 5% | 生态系统成熟度 |
3.3 风险分级
对发现的问题按严重程度分级：
| 级别 | 标识 | 定义 | 示例 |
|---|---|---|---|
| 🔴 高 | 必须修复 | 可能导致生产事故或安全漏洞 | 核心模块 0 测试、有已知高危漏洞、构建失败 |
| 🟡 中 | 建议修复 | 影响开发效率或长期维护 | CHANGELOG 过时、单人开发总线风险、.unwrap() 过多 |
| 🟢 低 | 宜改进 | 锦上添花的优化项 | 缺少 Dockerfile、无 API 文档 |
Step 4: 输出报告
报告格式
保存为 <项目根目录>/maturity-report.md。使用以下模板（严格遵守）：
# 🔬 [项目名] 成熟度评估报告
> 评估日期：YYYY-MM-DD | 主语言：[语言] | 代码规模：[行数]
> 综合评分：★☆☆☆☆ ~ ★★★★★（X.X/5.0）— [一句话定性]
---
## 一、综合概览
[2-3 句话的总体评价，点出核心优势和核心短板]
### 成熟度雷达
[用 8 行 ASCII 文字绘制 8 轴雷达图，格式如下：]
规模 ★★★★★
/\
/ \
CI/CD / \ 活跃度
★★★★ / \ ★★★★★
/ \
/ ★★ \
/ 测试覆盖 \
/ \
文档 ★★★★ ────── ★★★★ 代码质量 ★★★★ 外部集成
总评：[一句话] 最高维度：[维度名] 最低维度：[维度名]
---
## 二、8 维度详解
### 2.1 项目规模 ★★★★★
| 指标 | 数值 | 评价 |
|------|------|------|
| ... | ... | ... |
[如果需要，列出 Top 5 模块代码分布]
---
### 2.2 开发活跃度 ★★★★★
| 指标 | 数值 | 评价 |
|------|------|------|
| ... | ... | ... |
[包含近 30 天提交趋势 ASCII 图]
---
### 2.3 测试覆盖 ★★★★★
| 指标 | 数值 | 评价 |
|------|------|------|
| ... | ... | ... |
[包含各模块测试代码比表格]
⚠️ [如果有零测试模块，在此标注]
---
### 2.4 代码质量 ★★★★★
| 指标 | 数值 | 评价 |
|------|------|------|
| ... | ... | ... |
---
### 2.5 CI/CD 与 DevOps ★★★★★
| 指标 | 状态 |
|------|:--:|
| ... | ... |
---
### 2.6 文档 ★★★★★
| 指标 | 数值 | 评价 |
|------|------|------|
| ... | ... | ... |
---
### 2.7 安全 ★★★★★
| 指标 | 状态 |
|------|:--:|
| ... | ... |
---
### 2.8 外部集成与生态 ★★★★★
| 指标 | 状态 |
|------|:--:|
| ... | ... |
---
## 三、风险清单
### 🔴 高风险（必须修复）
1. **[风险标题]**：[具体描述 + 影响 + 建议修复方案]
### 🟡 中风险（建议修复）
1. **[风险标题]**：[具体描述 + 影响 + 建议修复方案]
### 🟢 改进建议
1. **[建议标题]**：[具体描述 + 预期收益]
---
## 四、改进路线图（可选）
如果发现 3+ 个高中风险，给出优先级排序的改进路线图：
| 优先级 | 改进项 | 预期工作量 | 预期收益 |
|:--:|------|:--:|------|
| 1 | ... | X 天 | 解决 N 个高/中风险 |
| 2 | ... | X 天 | ... |
---输出后行为
- 将报告保存到
<项目根目录>/maturity-report.md - 在对话中展示摘要（总体评分 + 风险数量 + 文件路径）
- 询问用户是否需要深入分析某个维度
注意事项
通用原则
- 命令可复现：报告中引用的每个数据都应来自一个可复现的命令。不要"估计"或"猜测"数值。
- 排除无关目录：统计代码时永远排除
target/、node_modules/、dist/、build/、.git/、worktrees/ - 排除非核心项目：
side-projects/、examples/、demo/中的代码默认不计入主项目统计，但需在报告中标注 - 失败不阻塞：某个检查命令失败时，在报告中标注"未获取"，不要阻塞后续检查
- 区分 main 和子项目：monorepo 中识别主项目，子项目单独统计
数据收集效率
- 所有 Bash 命令并行执行：不要串行执行 10 个 Bash 调用。在一次响应中同时发出多个独立命令。
- 使用 Glob 而非 find：找文件用 Glob，不用 Bash find
- 使用 Grep 而非 grep：搜索内容用 Grep 工具，不用 Bash grep
- 大输出用专用工具：目录遍历用
folder_operations，不用ls -R
评分公平性
- 刚创建 < 3 个月的项目：活跃度默认 +1 星（新项目不要求版本历史丰富）
- 单人项目：不因"总线风险"扣分（小型开源项目的合理状态），但仍需标注
- 非英语项目：文档语言不作为评分因子
- 已有测试但 CI 不跑：测试覆盖扣半星（测试不执行等于没测试）
© KonghaYao, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 5 other files (references) in .claude/skills/project-maturity of KonghaYao/peri.
- SKILL.md
- references/generic.md
- references/go.md
- references/python.md
- references/rust.md
- references/typescript.md
Open the folder on GitHubat commit d7ee444
Compare with similar skills
Project Maturity next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Project Maturity this skillKonghaYao/peri | 223 | — | ~1.8k | Automated safety check: Notes | Apache-2.0 | |
| Logfire Instrumentationbasicmachines-co/basic-memory | 4.1k | — | ~2.3k | Automated safety check: Pass | AGPL-3.0 | |
| Workflow Setupathola/claude-night-market | 342 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Supercov Securitysupercorp-ai/supercov | 150 | 1 repos | ~236 | Automated safety check: Pass | MIT | |
| Logfire Instrumentationpydantic/skills | 140 | — | ~6.1k | Automated safety check: Pass | MIT | |
| Project Initathola/claude-night-market | 342 | — | ~1.2k | Automated safety check: Pass | MIT |
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Categories
Questions about Project Maturity
What does Project Maturity do?
对任意项目进行全面的成熟度评估扫描。当用户说"检查项目成熟度"、"项目评估"、 "maturity assessment"、"代码质量扫描"、"项目健康度"、"项目体检"、 "scan project maturity"、"项目有多成熟"时触发。适用场景：接手新项目前的摸底、 发布前的质量审查、技术尽调、团队内部代码健康度盘点。. Project Maturity is an agent skill from KonghaYao/peri.
When should I use Project Maturity?
Project Maturity fits situations like: devOps & Cloud work in your project.
How do I install Project Maturity in Claude Code?
Run `npx skills add KonghaYao/peri --skill project-maturity -a claude-code`. Or copy the skill folder (.claude/skills/project-maturity in KonghaYao/peri) into .claude/skills/project-maturity in your project. Claude Code loads it when a task matches its description.
How do I install Project Maturity in Codex?
Run `npx skills add KonghaYao/peri --skill project-maturity -a codex`. Or copy the skill folder (.claude/skills/project-maturity in KonghaYao/peri) into .agents/skills/project-maturity in your project. Codex loads it when a task matches its description.
Can I use Project Maturity in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add KonghaYao/peri --skill project-maturity -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/project-maturity, .gemini/skills/project-maturity, .github/skills/project-maturity and .opencode/skills/project-maturity in your project.
What does Project Maturity need to run?
SKILL.md names no scripts, command-line tools or credentials: Project Maturity is instructions for the agent only. Our summary lists: Python 3; Docker.
Does Project Maturity access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Project Maturity safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Project Maturity use?
Project Maturity is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Project Maturity use?
About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.1k tokens, read only when the agent opens those files.
What are the alternatives to Project Maturity?
Skills that share tags, products or a category with Project Maturity: Logfire Instrumentation (basicmachines-co/basic-memory, 4.1k stars), Workflow Setup (athola/claude-night-market, 342 stars), Supercov Security (supercorp-ai/supercov, 150 stars) and Logfire Instrumentation (pydantic/skills, 140 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Project Maturity?
KonghaYao (a GitHub user) maintains it in KonghaYao/peri, which has 223 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on October 8, 2026.
Source: KonghaYao/peri on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.