💡 Summary
Terma is a library designed to enhance software development processes using LLMs like Claude Code.
🎯 Target Audience
🤖 AI Roast: “Powerful, but the setup might scare off the impatient.”
Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress). Run with least privilege and audit before enabling in production.
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.
Pros
- Structured approach to software development
- Integrates well with LLMs
- Encourages thorough documentation
Cons
- Highly opinionated, may not suit all teams
- Requires familiarity with LLMs
- Customization may be needed for specific workflows
Related Skills
pytorch
S“It's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.”
agno
S“It promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.”
nuxt-skills
S“It's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.”
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author bfollington.
