Skip to content

FFengIll/sdlc

Repository files navigation

SDLC-SKill

My prompt for ai coding with intent, harness and feedback

Install

Command (Recommend)

# For claude 
git clone https://github.com/FFengIll/sdlc.git

# /sdlc:sdlc
cp -R sdlc ~/.claude/commands/
# or flatten /sdlc
cp -R sdlc/* ~/.claude/commands/

Plugin / Skill

# For claude 
claude plugin marketplace add ffengill/sdlc
claude plugin install sdlc@sdlc-marketplace

# or in claude
/plugin marketplace add ffengill/sdlc
/plugin install sdlc@sdlc-marketplace

# use
/sdlc your command  

Overview

1. Intent Detection & Auto Routing

  /sdlc "fix login bug" | "add user auth" | "review my changes"
        │
        ▼
  Intent Detection Engine
        │
        ├─ fix|bug    → bugfix workflow   ─┐
        ├─ add|new    → feature workflow   │
        ├─ refactor   → refactor workflow  ├─→ Execute Skill → .sdlc/docs/category-feature-date.type.md
        ├─ review|cr  → action:cr          │
        ├─ understand → understand(cache) ─┘
        └─ commit|pr  → action:commit

2. Direct Action Invocation

  /actions:<action>: understand | spec | coding | test | commit | cr | pr | regression
        │
        ▼
  Action Map
        │
        ├─ understand → .sdlc/arch/overview-*.arch.md
        ├─ spec       → .sdlc/docs/*.spec.md
        ├─ coding     → .sdlc/docs/*.coding.md
        ├─ test       → .sdlc/docs/*.test.md
        ├─ commit     → .sdlc/docs/*.commit.md
        └─ pr         → .sdlc/docs/*.pr.md

3. Workflow Example: Feature Development

  /sdlc add user authentication
        │
        ▼
  Feature Workflow:
  understand → research → spec → coding → test → commit → pr
      │            │        │       │       │       │       │
   .sdlc/       .sdlc/   .sdlc/  .sdlc/  .sdlc/  .sdlc/  .sdlc/
   arch/         docs/    docs/   docs/   docs/   docs/   docs/
  overview-    auth-*   auth-*  auth-*  auth-*  auth-*  auth-*
  *.arch.md   .research  .spec  .coding  .test  .commit   .pr
               .md       .md     .md     .md     .md      .md

Interactive Flow: 继续 / 下一步 → Next phase 跳过测试 → Skip phase 到哪了? → Check status

SDLC with Harness

  • Specifications matter.

  • Trust in the power of process.

    The Software Development Life Cycle (SDLC) may be classical, but it still has much to teach us.

  • Do not attempt to keep every specification constantly updated as the code evolves.

    High-level specifications will inevitably lag behind.

  • Validation specifications are critical.

    We refer to this layer as the Harness.

  • Embrace the practice of maintaining and sharing the Harness:

    • It strengthens code reviews
    • It accelerates debugging
    • It supports safe refactoring
    • ……
  • REMEMBER There is no silver bullet.

    The only constant is change.


  • 规范(SPEC)很重要。

  • 相信流程的力量。

    Software Development Life Cycle (SDLC) 虽然古典,甚至略显传统,但它能教会我们的,远不止流程本身。

  • 不要试图让所有 SPEC 随代码实时同步。

    一般性的 SPEC,天然会滞后,这是常态,而非问题。

  • 验证型 SPEC 更关键。

    我们可以称之为 Harness

  • 主动建设并沉淀 Harness

    • 让 Code Review 更有依据
    • 让 Debug 更高效
    • 让 Refactoring 更安全
    • ……
  • 不存在银弹。

    变化常在。


Harness Showcase

showcase-oauth

SDLC with Feedback

  • 反馈驱动演进。

  • 工作流结束,学习才刚开始。

    每一次通过 /sdlc 完成的任务,都会产生新的洞察。

  • 不要满足于静态流程。

    今天有效的方法,明天可能需要改进。

  • 打分、反思、迭代。

  • 持续改进:

    • 评估哪些有效,哪些无效
    • 基于真实经验更新工作流
    • 让每次迭代为下次提供依据
    • ……
  • 不存在银弹。

    系统在每一次反馈循环中自我完善,人的反馈非常重要且简单。


  • Feedback drives evolution.

  • The workflow completes, but the learning continues.

    Every task executed through /sdlc generates insights.

  • Do not settle for static processes.

    What works today may need refinement tomorrow.

  • Score, reflect, and iterate.

# tasks done with /sdlc

# now we score them and update them
/feedback
  • Embrace continuous improvement:

    • Evaluate what worked and what didn't
    • Update workflows based on real experience
    • Let each iteration inform the next
    • ……
  • REMEMBER There is no silver bullet.

    The system improves itself, but feedback loop is important at a time.


Appendix

About

SDLC - For AI Coding with Harness and Feedback

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors