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Stack for developers

The AI-native developer stack

For engineers who want agents to do real work — not demos. Pick an open coding agent, give it battle-tested engineering skills and a spec-first workflow, connect up-to-date docs and code intelligence through MCP, and keep the boring utilities one click away.

Open source
17
Agent skills
5
Browser tools
3
Total pieces
30

ZIP: setup README, install helper, the skill folders (with licences) and free prompts.

How it connects

  1. 01

    Spec first

    Write the feature spec with Spec Kit or OpenSpec; the agent plans against it instead of guessing.

  2. 02

    Build with skills

    Superpowers / engineering skills make the agent write tests first, work in small steps and self-review.

  3. 03

    Ground it

    Context7 keeps docs current; the GitHub MCP server and a code graph give it your real codebase and issues.

  4. 04

    Verify and ship

    Run the security-audit skill, test the API in Hoppscotch, review with the checklist, deploy.

1 · Coding agent & editor

Open-source agents and editors you can run locally or point at any model.

2 · Engineering skills & methodology

Skills that teach the agent how good engineers work: plan, test, review, ship.

3 · Context, memory & docs (MCP)

Give the agent the right context: current docs, your codebase graph and your GitHub.

4 · Ship & everyday utilities

Frameworks agents are fluent in, plus the small tools you reach for daily.

Setup checklist

  • Install a coding agent (OpenCode, Claude Code or similar) and connect a model
  • Install the engineering skills (`install.sh` in the kit copies them to ~/.claude/skills)
  • Add Context7 and the GitHub MCP server to your agent's MCP config
  • Initialise Spec Kit or OpenSpec in your repo
  • Keep a CLAUDE.md / AGENTS.md with your project's conventions