💡 摘要
Terma是一个旨在通过使用像Claude Code这样的LLM来增强软件开发流程的库。
🎯 适合人群
🤖 AI 吐槽: “看起来很能打,但别让配置把人劝退。”
风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发)。以最小权限运行,并在生产环境启用前审计代码与依赖。
Terma (གཏེར་མ)
This is a highly-opinionated library of philosophy and process for developing software with LLMs, specifically Claude Code.
Copy/clone the contents of out into ~/.claude/commands to install these across all projects.
Installation
mkdir -p ~/.claude/commands/terma
mkdir -p ~/.claude/agents/terma
ln -s <CHECKOUT>/out/commands ~/.claude/commands/terma
ln -s <CHECKOUT>/subagents ~/.claude/agents/terma
Quick Start
Use /orient to begin each session. Use /research :question to probe the codebase and write a report to /research. Then, use /plan or just /feature to plan a change to the application.
Use /implement to spin up one or more well-instructed subagents to implement the plan.
You may find use for /debug, /code-review, /harden after implementation.
When you are at a known good state (i.e. about to commit) use /progress to write a progress report and update LOG.md, then commit w/ the .md file included. /next-up is like /progress but moves straight on to whatever additional task you provide.
You can use /bug-report to interactiely gather and record context for known issues, and use /resolve to resolve them.
We currently assume a protocol of LOG.md, BUGS.md, SPEC.md, CLAUDE.md etc. but this will and should be customized to fit.
Patterns
-
feature dev:
/orient,/feature,/implement,/progress,/compact(loop)- then:
/code-review
- then:
-
bugs:
/bug-report,/debug,/resolve,/code-review -
tech spike:
/prototype,/debug -
improve codebase architecture:
/orient,/research,/decompose,/code-review
Customizing
The build depends on deno.
You can edit anything in lib or the root and run and use ./build.sh to rebuild all. We use a simple remark transform for text inclusion, nothing fancy.
Trivia
The subagent.md file encourages "ultrathinking", which may burn through usage quickly. Consider customizing it manually until we have variables.
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
优点
- 结构化的软件开发方法
- 与LLM良好集成
- 鼓励全面的文档编写
缺点
- 高度主观,可能不适合所有团队
- 需要对LLM有一定了解
- 可能需要针对特定工作流程进行定制
相关技能
免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。
版权归原作者所有 bfollington.
